Gini coefficient

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The Great Leveler: Violence and the History of Inequality From the Stone Age to the Twenty-First Century by Walter Scheidel

agricultural Revolution, assortative mating, basic income, Berlin Wall, Bernie Sanders, Branko Milanovic, British Empire, capital controls, Capital in the Twenty-First Century by Thomas Piketty, classic study, collective bargaining, colonial rule, Columbian Exchange, conceptual framework, confounding variable, corporate governance, cosmological principle, CRISPR, crony capitalism, dark matter, declining real wages, democratizing finance, demographic transition, Dissolution of the Soviet Union, Downton Abbey, Edward Glaeser, failed state, Fall of the Berlin Wall, financial deregulation, fixed income, Francisco Pizarro, full employment, Gini coefficient, global pandemic, Great Leap Forward, guns versus butter model, hiring and firing, income inequality, John Markoff, knowledge worker, land reform, land tenure, low skilled workers, means of production, mega-rich, Network effects, nuclear winter, offshore financial centre, plutocrats, race to the bottom, recommendation engine, rent control, rent-seeking, road to serfdom, Robert Gordon, Ronald Reagan, Second Machine Age, Simon Kuznets, synthetic biology, The Future of Employment, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thomas Malthus, transaction costs, transatlantic slave trade, universal basic income, very high income, working-age population, zero-sum game

424 Appendix: The Limits of Inequality 445 Bibliography 457 Index 495 FIGURES AND TABLES FIGURES I.1Top 1 percent income share in the United States (per year) and references to “income inequality” (three-year moving averages), 1970–2008 1.1General form of the social structure of agrarian societies 3.1Inequality trends in Europe in the long run 3.2Gini coefficients of wealth distribution in Italy and the Low Countries, 1500–1800 3.3Ratio of mean per capita GDP to wages and real wages in Spain, 1277–1850 3.4Inequality trends in Latin America in the long run 3.5Inequality trends in the United States in the long run 4.1Top income shares in Japan, 1910–2010 5.1Top 1 percent income shares in four countries, 1935–1975 5.2Top 0.1 percent income shares in Germany and the United Kingdom 5.3Top 1 percent wealth shares in ten countries, 1740–2011 5.4Ratios of private wealth to national income in France, Germany, the United Kingdom, and the world, 1870–2010 5.5Capital income share in total gross income for top 1 percent of incomes in France, Sweden, and the United States, 1920–2010 5.6The share of government spending in national income in seven countries, 1913–1918 5.7Top marginal tax rates in nine countries, 1900–2006 5.8Average top rates of income and inheritance taxation in twenty countries, 1800–2013 5.9World War I and average top rates of income taxation in seventeen countries 5.10Top 1 percent income share in Germany, 1891–1975 5.11Top 1 percent income share in Sweden, 1903–1975 5.12State marginal income tax rates in Sweden, 1862–2013 5.13Trade union density in ten OECD countries, 1880–2008 6.1Military size and mobilization rates in years of war in great power states, 1650–2000 6.2Gini coefficients of income and top 0.01 percent income share in Spain, 1929–2014 9.1Median house sizes in Britain from the Iron Age to the Early Middle Ages 9.2House size quartiles in Britain from the Iron Age to the Early Middle Ages 9.3Gini coefficients of house sizes in Britain from the Iron Age to the Early Middle Ages 10.1Real wages of urban unskilled workers in Europe and the Levant, 1300–1800 10.2Real wages of urban skilled workers in Europe and the Levant, 1300–1800 10.3Rural real wages measured in terms of grain in England, 1200–1869 10.4Top 5 percent wealth shares and Gini coefficients of wealth distribution in the cities of Piedmont, 1300–1800 10.5Gini coefficients of wealth in Poggibonsi, 1338–1779 10.6Top 5 percent wealth shares in Tuscany, 1283–1792 10.7Top 5 percent wealth shares and Gini coefficients of wealth distribution in Lucca, 1331–1561 11.1Real wages expressed in multiples of bare-bones consumption baskets in central Mexico, 1520–1820 11.2Daily wheat wages of unskilled rural and urban workers in Egypt, third century BCE to fifteenth century CE 11.3Changes in real prices and rents between 100–160s and 190s–260s CE in Roman Egypt 11.4Wealth inequality in Augsburg: number of taxpayers, average tax payments, and Gini coefficients of tax payments, 1498–1702 13.1Gross National Income and Gini coefficients in different countries, 2010 13.2Estimated and conjectured income Gini coefficients for Latin America, 1870–1990 (population-weighted averages for four, six, and sixteen countries) 14.1Counterfactual inequality trends in the twentieth century 15.1Top 1 percent income shares in twenty OECD countries, 1980–2013 A.1Inequality possibility frontier A.2Estimated income Gini coefficients and the inequality possibility frontier in preindustrial societies A.3Extraction rates for preindustrial societies and their counterpart modern societies A.4Inequality possibility frontier for different values of the social minimum A.5Different types of inequality possibility frontiers TABLES 2.1The development of the largest reported fortunes in Roman society and the population under Roman control, second century BCE to fifth century CE 5.1The development of top income shares during the world wars 5.2Variation in the rate of reduction of top 1 percent income shares, by period 6.1Property in 1870 relative to 1860 (1860 = 100), for Southern whites 6.2Inequality of Southern household incomes 8.1Income shares in France, 1780–1866 11.1Share and number of taxable households in Augsburg by tax bracket, 1618 and 1646 15.1Trends in top income shares and income inequality in select countries, 1980–2010 ACKNOWLEDGMENTS The gap between the haves and the have-nots has alternately grown and shrunk throughout the course of human civilization.

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Despite these difficulties, the compilation and online publication of a growing amount of information on top income shares in the “World Wealth and Income Database” has put our understanding of income inequality on a more solid footing and redirected attention from somewhat opaque single-value metrics such as the Gini coefficient to more articulated indices of resource concentration.12 All these problems pale in comparison to those we encounter once we seek to extend the study of income and wealth inequality farther back in time. Regular income taxes rarely predate the twentieth century. In the absence of household surveys, we have to rely on proxy data to calculate Gini coefficients. Prior to about 1800, income inequality across entire societies can be estimated only with the help of social tables, rough approximations of the incomes obtained by different parts of the population that were drawn up by contemporary observers or inferred, however tenuously, by later scholars.

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APPENDIX: THE LIMITS OF INEQUALITY How far can inequality rise? In one important respect, measurements of income inequality differ from those of wealth inequality. There is no limit to how unequally wealth can be distributed within a given population. In theory, one person could own everything there is to own, with everybody else owning nothing but surviving on income from labor or transfers. This distribution would produce a Gini coefficient of ~1 or a top wealth share of 100 percent. In purely mathematical terms, income Ginis might also run from 0, for perfect equality, to ~1, for complete inequality. However, ~1 can never be reached in practice, because everyone needs a minimum amount of income just to stay alive.

The Globalization of Inequality by François Bourguignon

Berlin Wall, Branko Milanovic, Capital in the Twenty-First Century by Thomas Piketty, collective bargaining, Credit Default Swap, deglobalization, deindustrialization, Doha Development Round, Edward Glaeser, European colonialism, Fall of the Berlin Wall, financial deregulation, financial intermediation, gender pay gap, Gini coefficient, Glass-Steagall Act, income inequality, income per capita, labor-force participation, liberal capitalism, low interest rates, minimum wage unemployment, offshore financial centre, open economy, Pareto efficiency, purchasing power parity, race to the bottom, Robert Gordon, Simon Kuznets, structural adjustment programs, The Spirit Level, too big to fail, very high income, Washington Consensus

See also emerging economies development aid, 148–53, 157 development gap, 34–35, 83 Di Bao program, 166 discrimination: ghettos and, 66– 67; immigrants and, 64, 66, 127; labor and, 64–66, 69, 132, 142, 180–81; non-­material inequalites and, 64–66, 69; racial, 65; women and, 64–65, 103 disinflation, 95, 102, 110 distribution, 10n1, 186; capital-­ labor split and, 55–58, 60; efficiency and, 142–45; evolution of inequality and, 41, 42t, 44t, 45, 46t, 48–59, 64, 71–72; fairer globalization and, 148, 153, 156–73, 175, 178; geographical disequilibria and, 83; Gini coefficient and, 18 (see also Gini coefficient); global, 18–19, 25, 29, 39, 41, 46t, 121, 124–38, 141– 45, 156; growth and, 49–50, 188; international, 17–18, 30, 148; median of, 31; OECD countries and, 10–11, 12n3; policy and, 26, 72, 135, 188; range of, 16; real earnings loss and, 78; redistribution and, 4, 7, 37 (see also redistribution); rise in inequality and, 74, 77–79, 82, 85, 90–92, 94–96, 99, 103–4, 106–7, 112, 114–15; Southern perspective on, 82–85; standard of living and, 16, 18 (see also standard of living); taxes and, 37, 92–94 (see also taxes); Theil coefficient and, 18–19, 37–38, 194 distribution (cont.) 52; transfers and, 4, 14, 48, 105, 110, 130, 135–36, 142, 148, 153, 158–67, 170, 175, 181, 183, 187; wage, 3, 78–79, 107 Divided We Stand report, 52 Doha negotiations, 154 drugs, 66, 133 Dubai, 127 Economic Partnership Agreements (EPAs), 156 education, 34, 187; college, 132; evolution of inequality and, 61, 65–68; fairer globalization and, 149, 152, 167–73, 180–81; globalization and, 132, 140, 143; labor and, 168, 180; Millennium Development Goals and, 149– 50; national inequality and, 167–73; poverty and, 24; preschool, 169–70; redistribution and, 149, 152, 167–73; rise in inequality and, 111; taxes and, 167–73; tuition and, 170 efficiency: data transfer technology and, 78; deregulation and, 94, 96, 105, 108; economic, 1, 4, 6, 111, 116, 119, 129–33, 135, 140–45, 158, 164, 167, 171, 181; emerging economies and, 78; equality and, 116, 129–31; fairness and, 8, 129– 31; globalization and, 1, 4, 6, 8, 36, 78, 94, 96, 105, 108, 111, 116, 118–19, 129–35, 140–45, 157–58, 164, 167, 170–71, 175, 180–81, 188; human capital and, 175; import substitution and, 34, 180; inefficiency and, 105, 129–30, 132–33, 135, 140, 170–71, 180, 188; labor Index and, 175; loss of, 142, 164; opportunity and, 142–45; Pareto, 130n5; privatization and, 94, 96, 105, 108; redistribution and, 142–45; rents and, 180; social tensions and, 188; spontaneous redistribution and, 133; taxes and, 170; technology and, 78; weak institutions and, 36; wealth of nations and, 1 elitism, 182; fairer globalization and, 151, 165; globalization and, 127n4, 136, 138; rise in inequality and, 4, 6–7 emerging economies: Africa and, 122–23 (see also Africa); competition and, 178, 187–88; conditional cash transfers and, 165– 66; credit cards and, 165; domestic markets and, 120, 125; efficient data transfer and, 78; evolution of inequality and, 57; fairer globalization and, 147, 154, 158, 165–66, 177–78, 182; global inequality and, 40, 77– 80, 82, 109, 113, 115, 188–89; globalization and, 117, 119–22, 125–27; institutions and, 109– 12; Kuznets curve and, 113; labor and, 77; natural resources and, 127; profits and, 117; rise in inequality and, 109–12; structural adjustment and, 109– 12; taxes and, 165; trends in, 57; Washington consensus and, 109–10, 153 entrepreneurs, 83, 92, 96, 131–32, 135, 143, 170–71, 188 equality: efficiency and, 116, 129– 31; policy for, 184–89; relative gap and, 18, 28, 30, 31–32, 36 Ethiopia, 21–22, 46t, 155 Index195 European Union (EU), 24, 156, 174, 177 Everything But Arms (EBA) initiative, 155 evolution of inequality: Africa and, 46t, 54–55; Brazil and, 46t, 55, 59, 70; capital and, 55–58, 60, 73; China and, 47, 53, 57–60; consumption and, 42t, 44t; convergence and, 65, 69; credit and, 61; crises and, 48, 50, 54, 57, 73–74; developed countries and, 47, 52–53, 56, 59–64, 66; developing countries and, 47, 53–55, 57, 63, 68; distribution and, 41, 42t, 44t, 45, 46t, 48–59, 64, 71– 72; education and, 61, 65–68; elitism and, 4, 6–7, 46t; emerging economies and, 57; exceptions and, 52–53; France and, 46t, 51f, 52–53, 55, 58, 59n8, 62–63, 66, 70–71; ghettos and, 66–67; Gini coefficient and, 39, 42t, 44t, 48, 50, 51f, 53, 58–59; Great Depression and, 48; growth and, 33, 49–50, 54; India and, 54, 57, 59–60; institutions and, 55, 69; investment and, 56; labor and, 55–58, 60; markets and, 48–50, 53–54, 64, 69; national income inequality and, 48–52; non-­monetary inequalities and, 49, 60–70; normalization and, 41, 43–44; opportunity and, 61–62, 68, 70–71; perceptions of inequality and, 69–73; policy and, 55, 72; primary income and, 48–50, 58; production and, 57; productivity and, 63; profit and, 56; reform and, 54, 72; rise in inequality in, 48–52, 73, 77–80, 91–95, 97–98, 102–8; risk and, 63, 66; standard of living and, 41, 43– 45, 46t, 53–55, 58, 60–62, 67, 69, 73; surveys and, 42t, 43–45, 56, 68n17, 69–71; taxes and, 12–14, 37, 48, 50, 56n5; Theil coefficient and, 42; United Kingdom and, 46t, 50, 51f, 59, 67, 68n17; United States and, 2, 4–6, 9, 11, 21, 33, 46t, 47–50, 51f, 58, 59n9, 66–70, 73; wealth and, 58–60 executives, 73, 88–89, 97, 174 expenditure per capita, 13, 15, 42t, 44t exports: deindustrialization and, 76, 82; fairer globalization and, 147, 154–55, 176, 178; globalization and, 124, 128; rise in inequality and, 76, 82–84 fairer globalization: Africa and, 147, 151, 154–56, 179, 183; African Growth Opportunity Act (AGOA) and, 155; Bolsa Familia and, 166; Brazil and, 150, 154, 166–68, 173; capital and, 158–62, 167, 171, 175, 182; China and, 150, 154, 165–66, 172, 178; competition and, 155, 169, 173, 176–79, 182; consumers and, 177–78; consumption and, 159, 177; convergence and, 146–47, 157; correcting national inequalities and, 158–80; credit and, 164–65, 172, 180; crises and, 163, 176; deregulation and, 173; developed countries and, 150, 154–57, 160, 162, 164, 168–72, 176, 178–79, 181; developing countries and, 154, 166; development aid and, 196 fairer globalization (cont.) 148–53, 157; Di Bao program and, 166; distribution and, 148, 153, 156–73, 175, 178; Economic Partnership Agreements (EPAs) and, 156; education and, 149, 152, 167–73; 180–81; elitism and, 151, 165; emerging economies and, 147, 154, 158, 165–66, 177–78, 182; Everything But Arms (EBA) initiative and, 155; exports and, 147, 154–55, 176, 178; France and, 147, 159–61, 164, 169, 175, 177; Gini coefficient and, 156, 166; goods and services sector and, 180; growth and, 147–52, 155, 162, 167–68, 171, 177, 180, 183; health issues and, 152, 166; imports and, 154, 177–78, 180; India and, 150, 154, 165– 66, 172; inheritance and, 170– 73; institutions and, 151, 168, 174–75; international trade and, 176–77; investment and, 150, 155, 157, 160, 170, 174, 179; liberalization and, 156, 179; markets and, 147–48, 154–58, 168, 173–75, 178–81; Millennium Development Goals and, 149–50; national inequality and, 147, 158; opportunity and, 155, 167, 170, 172; policy and, 147–53, 157, 167–73, 175, 177, 179–83; poverty and, 147–52, 164, 166, 175; prices and, 147– 48, 176, 178, 182; primary income and, 158, 163n10, 167, 173; production and, 155–57, 167, 176, 178–79; productivity and, 155, 177–78; profit and, 173, 176; Progresa program and, Index 166; protectionism and, 7, 147, 154, 157, 176–79; redistribution and, 148, 153, 156–73, 175, 178; reform and, 151, 161, 163, 168–69; regulation and, 152, 173–76, 181–82; risk and, 148, 154, 156, 159, 164, 171, 174–75, 178; standard of living and, 146–48, 154, 156–58, 160, 165, 168–69; surveys and, 169; taxes and, 148, 158–73, 175, 181–83; technology and, 156, 173; TRIPS and, 156; United Kingdom and, 163, 169; United States and, 155, 159–61, 163– 64, 169, 174–75, 182; wealth and, 162, 164, 167, 170–73 Fitoussi, Jean-­Paul, 14 France: evolution of inequality and, 46t, 51f, 52–53, 55, 58, 59n8, 62–63, 66, 70–71; fairer globalization and, 147, 159–61, 164, 169, 175, 177; Gini coefficient of, 20; global inequality and, 2, 9, 11, 20–21; offshoring and, 81; rise in inequality and, 80, 88, 92–93, 95, 97, 99, 103; soccer and, 87; wage deductions and, 159 G7 countries, 56 G20 countries, 182 Garcia-­Panalosa, Cecilia, 107 Gates, Bill, 5–6, 70, 150 Germany, 2, 21, 46t, 50, 51f, 80, 88, 92 Ghana, 46t, 54 ghettos, 66–67 Giertz, Seth, 160–61 Gini coefficient: Brazil and, 22; Current Population Survey and, 21; evolution of inequality and, Index197 39, 42t, 44t, 48, 50, 51f, 53, 58– 59; fairer globalization and, 156, 166; France and, 20; historical perspective on, 27–28; meaning of, 18–19; purchasing power parity and, 28; rise in inequality and, 110; United States and, 21; wealth inequality and, 58–60 Glass-­Steagall Act, 174n15 global distribution, 18–19, 25, 29, 39, 41, 46t, 121, 156 global inequality: Africa and, 16, 21, 23, 30–31, 34, 36; between countries, 2–3, 5, 7, 9, 16–19, 23, 33, 36, 38–39, 42–45, 47, 53, 58, 68, 90–91, 107, 117–19, 123, 128, 153; Brazil and, 21– 23; crises and, 20, 38–41; cross-­ country heterogeneity and, 13; definition of, 3–4, 9–10, 25–26, 30–32, 39; developed countries and, 10–11, 21, 34–39; developing countries and, 10–11, 13, 21, 32, 34–39; effects of, 38–40; emerging economies and, 40, 77–80, 82, 109, 113, 115, 188– 89; at the end of the 2000s, 20– 25; evolution of inequality and, 41 (see also evolution of inequality); expenditure per capita and, 13, 15, 42t, 44t; France and, 2, 9, 11, 20–21; globalization and, 117–18, 121–23, 128; great gap and, 33–36; historic turning point for, 25–32; Human Development Report and, 25; institutions and, 36; measuring, 10– 20; Millennium Development Goals and, 149–50, 185; normalization and, 13, 15, 22–23, 26, 29; OECD Database on Household Income Distribution and Poverty and, 11–12; policy and, 185–89; Povcal database and, 10, 12, 42t, 43, 44t; prices and, 27–28, 74, 80, 84, 91–92, 94, 97, 110; profit and, 13; reduction of, 2, 185–86; relative gap and, 18, 28, 30–32, 36; rise of, 2–4, 7; risk and, 20; standard of living and, 10–26, 29, 31–33, 36, 39; surveys on, 10, 12–15, 20n10, 21–22, 29, 42t, 43–45; technology and, 3–4, 34–35; trend reversal in, 37–38; within countries, 2, 5–7, 9, 16, 30, 33, 35–45, 47, 113–14, 118, 124– 29, 184–85, 189 globalization: Africa and, 122–23, 126–27; Asian dragons and, 34, 82; Brazil and, 127, 133; capital and, 117, 125–26, 132, 137; China and, 120–22, 128; competition and, 117–18, 130, 186 (see also competition); as complex historical phenomenon, 1–2; consumption and, 137–39; convergence and, 120–22, 125; credit and, 131–32, 137–40; crises and, 119–22, 125, 135–39, 142; debate over, 1; deindustrialization in developed countries and, 75–82; democratic societies and, 135–36; deregulation and, 95–99; developed countries and, 117, 119, 121, 127n4, 128, 133, 143; developing countries and, 121, 127n4, 128, 132, 143; education and, 132, 140, 143; efficiency and, 1, 4, 6, 8, 36, 78, 94, 96, 105, 108, 111, 116, 118–19, 129–35, 140–45, 157–58, 164, 167, 170–71, 175, 180–81, 188; elitism and, 127n4, 136, 138; 198 globalization (cont.) emerging economies and, 117, 119–22, 125–27; exports and, 124, 128; fairer, 146–83 (see also fairer globalization); future of inequality between countries and, 119–22; global inequality and, 117–18, 121–23, 128; goods and services sector and, 127, 130; growth and, 118–29, 134–39; health issues and, 140– 41, 144; Heckscher-­Ohlin model and, 76; imports and, 119, 124; inequality within countries and, 124–29; inheritance and, 144–45; institutions and, 124; as instrument for modernization, 1; international trade and, 3, 75–76, 78–79, 83, 112, 114, 176–77; investment and, 119, 130, 134–35, 143; laissez-­faire approach and, 118, 129; markets and, 118, 120–21, 124–37, 140, 143–44; as moral threat, 1; national inequality and, 119; negative consequences of inequality and, 131–42; opportunity and, 133–34, 139, 142–44; as panacea, 1; policy and, 118–19, 124, 126, 128–31, 139, 143–44; poverty and, 117, 123, 126–27, 134, 144; prices and, 118, 122, 126, 136–38; primary income and, 135, 143–44; production and, 119, 124, 126, 129, 131, 133, 137; productivity and, 120, 125, 127, 144; profit and, 117; redistribution and, 121, 124–38, 141–45; reform and, 124, 126–27, 138; regulation and, 136; rise in inequality and, 117–18; risk and, 127–28, Index 137–39, 144; shocks and, 38, 55, 91–92, 175; Southern perspective on, 82–85; standard of living and, 120–23, 126, 138, 143; surveys and, 127n4, 141n15; taxes and, 74, 89n10, 91–94, 104, 114–15, 129–30, 135–36, 142–45; technology and, 86–91, 118–20, 125; trends and, 118; United States and, 135–39; wealth and, 74, 95, 98, 125, 127, 129, 131–32, 139, 143–45 Great Depression, 48 Greece, 46t, 135 gross domestic product (GDP) measurement: Current Population Survey and, 21; evolution of inequality and, 41–45, 56–57; fairer globalization and, 123, 127, 165–66, 176; global inequality and, 13–15, 20–21, 23, 26, 27f, 29–30, 39; normalization and, 29, 41, 43–45; rise in inequality and, 94; Sen-­Stiglitz-­ Fitoussi report and, 14 Gross National Income (GNI), 148–49 Growing Unequal report, 52 growth, 4; African Growth Opportunity Act (AGOA) and, 155; constraints and, 35; consumption and, 13–15, 42t, 44t, 80, 137–39, 159, 177; convergence and, 16; determinants of, 34; distribution and, 49–50, 188; emerging economies and, 125 (see also emerging economies); evolution of inequality and, 33, 49–50, 54; fairer globalization and, 147–52, 155, 162, 167–68, 171, 177, 180, 183; GDP mea- Index199 surement of, 30, 39 (see also gross domestic product (GDP) measurement); globalization and, 118–29, 134–39; great gap in, 33–36; import substitution and, 34, 180; inflation and, 50, 95, 102, 110; negative, 31; political reversals and, 36; poverty and, 28–29; production and, 3, 34–35, 57, 74, 76–81, 84–86, 119, 124, 126, 129, 131, 133, 137, 155–57, 167, 176, 178–79; rate of, 15, 29–35, 79, 125, 185; recession and, 6, 31, 99, 120; relative gap and, 18, 20, 30–32, 36; rise in inequality and, 75, 79, 82, 84, 109–12; trends in, 40, 121 health issues, 24, 187; fairer globalization and, 152, 166; globalization and, 140–41, 144; public healthcare and, 37, 111, 140 Heckscher-­Ohlin model, 76 Hong Kong, 34, 82, 174 housing, 12, 61, 137 human capital, 74, 167, 175 Human Development Report, 25 Ibrahimovich, Zlata, 87 IKEA, 172 immigrants, 64, 66, 127 imports: fairer globalization and, 154, 177–78, 180; globalization and, 119, 124; import substitution and, 34, 180; rise in inequality and, 80 income: average, 9, 18, 21, 29–30, 43, 72; bonuses and, 87, 174; convergence and, 16; currency conversion and, 11; definition of, 45; deindustrialization and, 75–82; developed/developing countries and, 5, 36; disposable, 20, 22, 24, 48, 50, 51f, 74, 91, 163; distribution of, 3 (see also distribution); executives and, 73, 88–89, 97, 174; family, 10; financial operators and, 87–88, 90–91; gap in, 3, 5–6, 27f, 33– 36, 42t, 44t, 149; GDP measurement and, 13–15, 20–21, 23, 26, 27f, 29–30, 39, 41–45, 56–57, 94, 123, 127, 165–66, 176; high, 50, 52, 56, 85–93, 97–99, 140, 143, 158–62, 164, 189; household, 10–12, 43, 45, 50, 58, 105, 107, 137, 163, 177; inequality in, 2, 4, 41, 48–50, 56–64, 68, 70, 72–73, 83, 98, 102–3, 107–8, 114, 125, 132– 34, 137, 140–41, 143–44, 163; inflation and, 50, 95, 102, 110; international scale for, 17–18, 23, 30; lawyers and, 89–90; mean, 17, 20n10, 27f, 42t, 44t; median, 6, 49, 71, 102–3, 106; minimum wage and, 52–53, 100, 102–8, 175, 177; national, 7, 16–19, 30, 43, 48–52, 60, 73, 84n6, 125, 149, 153, 172; OECD Database on Household Income Distribution and Poverty and, 11; opportunity and, 5; payroll and, 53, 93, 100, 104, 107, 175; pension systems and, 167; per capita, 20, 25, 29–30, 42t, 45, 48, 55–56, 120; portfolios and, 88; poverty and, 1, 11, 15n6, 19–20, 22–25, 28–29, 32, 44t, 109, 117, 123, 126–27, 134, 144, 147–52, 164, 166, 175; primary, 48–50, 58, 135, 143–44, 158, 163n10, 167, 173; 200 income (cont.) purchasing power and, 11, 13, 19–24, 27f, 28, 50, 80, 144, 158, 178; real earnings loss and, 78; relative gap and, 18, 28, 30, 31– 32, 36; superstars and, 85–87, 89–90; taxes and, 37, 89n10, 92–93, 145, 159, 161–65, 170 (see also taxes); technology and, 34, 180; virtual, 12; wage inequality and, 51–53, 79, 101–3, 106, 108; wage ladder effects and, 78–79; wealth inequality and, 58–60; women and, 64– 65, 103 India: evolution of inequality and, 54, 57, 59–60; fairer globalization and, 150, 154, 165– 66, 172; household consumption and, 15; international trade and, 75; Kuznets hypothesis and, 113; rise in inequality and, 2, 15–16, 19, 30, 34, 46t, 75, 83, 90, 112–13; taxes and, 165 Indonesia, 30, 46t, 54, 111, 127 industrialization: deindustrialization and, 1, 75–82, 102, 120, 188; labor and, 1, 26, 29, 33, 35, 54, 82, 84, 102, 113, 120, 127, 179, 188 Industrial Revolution, 26, 29, 33, 35 inequality: between countries, 2–3, 5, 7, 9, 16–19, 23, 33, 36, 38– 39, 42–45, 47, 53, 58, 68, 90– 91, 107, 117–19, 123, 128, 153; efficiency and, 1, 4, 6, 8, 36, 78, 94, 96, 105, 108, 111, 116, 118– 19, 129–35, 140–45, 157–58, 164, 167, 170–71, 175, 180–81, 188; Gini coefficient and, 18 (see Index also Gini coefficient); income, 2, 4, 41, 48–50, 56–64, 68, 70, 72–73, 83, 98, 102–3, 107–8, 114, 125, 132–34, 137, 140–41, 143–44, 163; international, 17; inverted U curve and, 54, 113; measurement of, 18; negative consequences of, 131–42; non-­ monetary, 49, 60–70; perceptions of, 69–73; social tensions and, 188; standard of living and, 18 (see also standard of living); Theil coefficient and, 18–19, 37–38, 42; wealth, 58–60; within countries, 2, 5–7, 9, 16, 30, 33, 37–45, 47, 113–14, 118, 124–29, 184–85, 189 infant mortality, 150 inflation, 50, 95, 102, 110 inheritance: fairer globalization and, 170–73; globalization and, 144–45; rise in inequality and, 93 institutions: deregulation and, 91– 112 (see also deregulation); disinflation and, 95, 102, 110; emerging economies and, 109– 12; evolution of inequality and, 55, 69; fairer globalization and, 151, 168, 174–75; global inequality and, 36; globalization and, 124; markets and, 91–92; privatization and, 94–109; reform and, 91–112; rise in inequality and, 91–112, 114; structural adjustment and, 109– 12; taxes and, 92–94; “too big to fail” concept and, 174–75; Washington consensus and, 109–10, 153 International Development Association, 149 Index201 international income scale, 17–18, 23, 30 International Labor Organization, 51 International Monetary Fund (IMF), 54, 57, 84, 90, 109–10 international trade: capital mobility and, 74; China and, 75; de­ industrialization and, 75–76, 78–79; effect of new players, 75–76; Heckscher-­Ohlin model and, 76; India and, 75; offshoring and, 81–82; rise in inequality and, 75–76, 78–79, 83, 112, 114; Soviet Union and, 75; theory of, 76; wage ladder effects and, 78–79 inverted U curve, 54, 113 investment: direct, 76, 79; evolution of inequality and, 56; fairer globalization and, 150, 155, 157, 160, 170, 174, 179; foreign, 83, 85, 112, 155, 157, 160, 179; globalization and, 119, 130, 134– 35, 143; production and, 119; public services and, 143; re-­ investment and, 56; rise in inequality and, 76, 79, 82–83, 85, 92, 97–98, 112; taxes and, 92 Ivory Coast, 54 Japan, 34, 46t, 51f, 103 job training, 34, 181, 187 Kenya, 46t, 54 kidnapping, 133 Kuznets, Simon, 113, 126 labor: agriculture and, 12, 82, 84, 122–23, 127–28, 132, 155; artists and, 86–87; bonuses and, 87, 174; capital and, 3–4, 55– 58, 60, 158, 161n7, 185; capital mobility and, 3; cheap, 77, 117; costs of, 81, 100, 104–5, 117, 176, 187; decline in share of national income and, 73; deindustrialization and, 75–82; demand for, 168; deregulation and, 99– 109; discrimination and, 64–66, 69, 132, 142, 180–81; distribution of income and, 175 (see also distribution); education and, 168, 180; efficiency and, 96–97, 175; emerging economies and, 77; entrepreneurs and, 83, 92, 96, 131–32, 135, 143, 170–71, 188; evolution of inequality and, 55–58, 60; excess, 81, 83; executives and, 73, 88–89, 97, 174; goods and services sector and, 13, 73, 80, 85, 91, 102, 127, 130, 180; growth and, 154, 179; immigrant, 64, 66, 127; increased mobility and, 90–91; industrialization and, 1, 26, 29, 33, 35, 54, 80, 82, 84, 102, 113, 120, 127, 179, 188; inflation and, 50, 95, 102, 110; International Labor Organization and, 51; job training and, 34, 181, 187; manufacturing and, 57, 80–82, 84, 123, 154–55, 157; median wage and, 49, 71, 102– 3, 106; minimum wage and, 52– 53, 100, 102–8, 175, 177; mobility of, 185; offshoring and, 81–82; payroll and, 53, 93, 100, 104, 107, 175; pension systems and, 167; portfolios and, 88; poverty and, 1, 11, 15n6, 19– 20, 22–25, 28–29, 32, 44t, 109, 117, 123, 126–27, 134, 144, 147–52, 164, 166, 175; 202 labor (cont.) privatization and, 99–109; productivity and, 63, 79, 81–82, 89, 100, 102, 104, 114, 120, 125, 127, 144, 155, 177–78; protectionism and, 7, 147, 154, 157, 176–79; real earnings loss and, 78; reserve, 84; security and, 133; skilled, 76–78, 82–83, 86, 90, 114, 117, 126, 176; standard of living and, 69 (see also standard of living); superstars and, 85, 87, 89–90; supply of, 130– 31, 164; taxes and, 159–60, 171; technology and, 85–91 (see also technology); unemployment and, 37, 39, 53, 62–63, 66, 69, 77, 94, 100–108, 164, 175–76; unions and, 100–106, 108, 156, 179; unskilled, 3, 76–77, 79, 83, 105, 117, 154; wage inequality and, 51–53, 79, 101–3, 106, 108; wage ladder effects and, 78–79; women and, 64–65, 103, 114; writers and, 86–87 Lady Gaga, 5–6 laissez-­faire approach, 118, 129 Latin America, 9, 34, 36, 54–55, 58, 109–11, 155, 165–66, 168, 180 lawyers, 89–90 liberalization: capital and, 96; customs, 156; deregulation and, 96–99, 108–9, 112 (see also deregulation); fairer globalization and, 156, 179; mobility of capital and, 115; policy effects of, 97–99; Reagan administration and, 91; recession and, 6, 31, 99, 120; rise in inequality and, 76, 91, 93, 96–99, 108–9, 112, 115; tax rates and, 93 Luxembourg, 16, 19 Index Madonna, 71 Malaysia, 127 manufacturing: deindustrialization and, 75–82, 84, 123; emerging economies and, 57, 84; fairer globalization and, 154–55, 157; France and, 81; offshoring and, 81–82; United Kingdom and, 80; United States and, 80 markets: competition and, 76–77, 79–82, 84, 86, 94–98, 102, 104, 115–18, 130, 155, 169, 173, 176–79, 182, 186–88; credit, 131; deindustrialization and, 1, 75–82, 102, 120, 188; deregulation and, 91–92, 99–109 (see also deregulation); development gap and, 34–35, 83; Economic Partnership Agreements (EPAs) and, 156; effect of new players, 75–76; emerging economies and, 120 (see also emerging economies); entrepreneurs and, 83, 92, 96, 131–32, 135, 143, 170–71, 188; evolution of inequality and, 48–50, 53–54, 64, 69; exports and, 76, 82–84, 124, 128, 147, 154–55, 176, 178; fairer globalization and, 147–48, 154–58, 168, 173–75, 178–81; GDP measurement and, 13–15, 20–21, 23, 26, 27f, 29–30, 39, 41–45, 56–57, 94, 123, 127, 165–66, 176; globalization and, 35, 118, 120–21, 124–37, 140, 143–44; Heckscher-­Ohlin model and, 76; housing, 12, 61, 137; imports and, 1, 34, 80, 119, 124, 154, 177–78, 180; institutions and, 91–112; international trade and, 3, 75–76, 78–79, 83, 112, 114, 176–77; labor and, Index203 144 (see also labor); liberalization and, 112 (see also liberalization); monopolies and, 94, 111, 127, 136; offshoring and, 81– 82; protectionism and, 7, 147, 154, 157, 176–79; purchasing power and, 11, 13, 19–24, 27f, 28, 50, 80, 144, 158, 178; reform and, 54 (see also reform); regulation and, 74 (see also regulation); rise in inequality and, 74, 76– 79, 83, 86, 90–112, 114; shocks and, 38, 55, 91–92, 175; single market and, 76; South-­South exchange and, 35; TRIPS and, 156 median wage, 49, 71, 102–3, 106 Mexico, 46t, 57, 59, 109–10, 133, 166, 172 middle class, 51, 71, 93, 109, 133– 34, 136, 140 Milanovic, Branko, 4–5, 17n8, 29n16 Millennium Development Goals, 149–50, 185 minerals, 84, 127 minimum wage, 52–53, 100, 102– 8, 175, 177 monopolies, 94, 111, 127, 136 Morocco, 173 Morrisson, Christian, 28 movies, 87 Murtin, Fabrice, 28 national inequality, 2–4; correcting, 158–80; education and, 167–73; fairer globalization and, 147, 158; Gini coefficient and, 27 (see also Gini coefficient); globalization and, 119; market regulation and, 173–75; protectionism and, 147, 157, 176–79; redistribution and, 158–73, 175, 178; rise in, 6, 48– 52, 115, 204; taxes and, 158–73, 175, 181–83 natural resources, 84–85, 92, 122, 126–28, 127, 151 Netherlands, 46t, 50, 66, 70, 102 Nigeria, 9, 46t, 54, 127, 151 non-­monetary inequalities: access and, 61, 67–68; capability and, 61; differences in environment and, 66–68; discrimination and, 64–66, 69; employment precariousness and, 63–64; evolution of inequality and, 49, 60–70; intergenerational mobility and, 68; opportunities and, 49, 60– 70; social justice and, 60, 70; unemployment and, 62–63 normalization: evolution of inequality and, 41, 43–44; GDP measurement and, 29, 41, 43– 45; global inequality and, 13, 15, 22–23, 26, 29 Occupy Wall Street movement, 6, 135 OECD countries, 27t; evolution of inequality and, 42t, 43, 44t, 50– 52, 64, 65n13; fairer globalization and, 149, 159, 162, 164– 65; Gini coefficient and, 51; income distribution and, 51; relaxation of regulation and, 99; restrictive, 64; rise in inequality and, 50–51, 94, 99, 102, 106n18, 107; social programs and, 94; standard of living and, 11–12, 43, 50–52, 64, 94, 99, 102, 107, 120, 149, 159, 162, 164–65; U-­shaped curve on income and, 50 OECD Database on Household 204 Income Distribution and Poverty, 11–12 offshoring, 81–82 oil, 92, 127 opportunity, 5; African Growth Opportunity Act (AGOA) and, 155; as capability, 61; efficiency and, 142–45; evolution of inequality and, 61–62, 68, 70–71; fairer globalization and, 155, 167, 170, 172; globalization and, 133–34, 139, 142–44; redistribution and, 142–45; rise in inequality and, 102 Pakistan, 46t, 111 Pareto efficiency, 130n5 Pavarotti, Luciano, 86–87 payroll, 53, 93, 100, 104, 107, 175 Pearson Commission, 149 pension systems, 167 Perotti, Roberto, 134 Philippines, 46t, 111 Pickett, Kate, 140 Piketty, Thomas, 4, 48, 59n8, 60, 89n10, 125, 160n4 PISA survey, 169–70 policy, 4; adjustment, 109, 153; Cold War and, 149, 153; convergence and, 147–48; development aid and, 148–53; distributive, 26, 72, 135, 188; educational, 149, 152, 167–73; evolution of inequality and, 55, 72; fairer globalization and, 147–53, 157–58, 167–73, 175–83; Glass-­Steagall Act and, 174n15; global inequality and, 185–89; globalization and, 118–19, 124, 126, 128–31, 139, 143–44; globalizing equality and, 184–89; import substi- Index tution and, 34; Millennium Development Goals and, 149– 50, 185; poverty reduction and, 147–48; protectionist, 7, 99– 100, 107–8, 147, 154, 157, 176–79; reform and, 74 (see also reform); rise in inequality and, 34, 74–75, 85, 94, 97, 99– 100, 104, 106–11, 114–16; social, 7; standard of living and, 147–48 population growth, 28–29, 110, 183 portfolios, 88 Povcal database, 10, 12, 42t, 43, 44t poverty, 1, 44t, 109; Collier on, 23; convergence and, 147–48; criminal activity and, 133–34; definition of, 24; development aid and, 147–52; fairer globalization and, 147–52, 164, 166, 175; ghettos and, 66–67; global inequality and, 11, 15n6, 19–20, 22–25, 28–29, 32; globalization and, 117, 123, 126–27, 134, 144; growth and, 28–29; measurement of, 23–24; Millennium Development Goals and, 149– 50, 185; OECD Database on Household Income Distribution and Poverty and, 11–12; reduction policies for, 147–48; traps of, 144, 150, 164 prices: commodity, 84, 182; exports and, 178; factor, 74, 126; fairer globalization and, 147–48, 176, 178, 182; global inequality and, 27–28, 74, 80, 84, 91–92, 94, 97, 110; globalization and, 118, 122, 126, 136–38; imports and, 80; international compari- Index205 sons of, 11; lower, 94, 137; oil, 92; rise in inequality and, 74, 80, 84, 91–92, 94, 97, 110; rising, 110, 122, 178; shocks and, 38, 55, 91–92, 175; statistics on, 11, 27; subsidies and, 109–10, 175 primary income: evolution of inequality and, 48–50, 58; fairer globalization and, 158, 163n10, 167, 173; globalization and, 135, 143–44 privatization: deregulation and, 94–112; efficiency and, 94, 96, 105, 108; globalization of finance and, 95–99; institutions and, 94–109; labor market and, 99–109; reform and, 94–109; telecommunications and, 111 production: deindustrialization and, 75–82; evolution of inequality and, 57; fairer globalization and, 155–57, 167, 176, 178–79; globalization and, 119, 124, 126, 129, 131, 133, 137; growth and, 3, 34–35, 57, 74, 76–81, 84–86, 119, 124, 126, 129, 131, 133, 137, 155–57, 167, 176, 178–79; material investment and, 119; North vs.

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But we can also try to take into account the differences observed at intermediate levels. Various synthetic methods of measuring inequality do this in different ways. In this book, I will use basically four measures of inequality: the share that goes to the richest (1%, 5%, or 10%), the relative gap between standards of living in the extreme deciles (the richest 10% and the poorest 10%), the Gini coefficient, and the Theil coefficient. The Gini coefficient is probably the most frequently employed measure of inequality. It takes into account the entirety of the distribution rather than just the extremes and can be defined as (half ) the average absolute difference between two individuals chosen at random in the population, in relation to the average standard of living of the population as a whole.

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An almost identical rise took place in the United Kingdom, but the concentration of wealth changed only slightly in other European countries, with the notable exception of Sweden.8 When it comes to emerging and developing economies, we have periodic estimates of wealth distribution for only some of them. The numbers that we have show very high levels of inequality, comparable to developed countries. The Gini coefficient for wealth was estimated to be 0.55 in China, 0.65 in India, and 0.78 in Brazil and Mexico in the late 1990s or early 2000s. We know a lot less about its evolution over time. At the very least, we can think that, due to intra-­and intergenerational accumulation, wealth inequality will also rise in countries in which income inequality has risen significantly. Thus, a recent study found that the Gini coefficient for wealth increased by almost 10 percentage points in China between 1995 and 2002,9 but that India’s levels were quasi-­stable between 1991 and 2002.10 8 Thomas Piketty and Gabriel Zucman report a change in the top 1% share from 22% to 24% between 1970 and 2010 in France, and from 18% to 20% in Sweden (“Wealth and Inheritance in the Long-­Run,” in Anthony B.

The Haves and the Have-Nots: A Brief and Idiosyncratic History of Global Inequality by Branko Milanovic

Berlin Wall, Branko Milanovic, colonial rule, crony capitalism, David Ricardo: comparative advantage, deglobalization, Deng Xiaoping, endogenous growth, Fall of the Berlin Wall, financial deregulation, full employment, Gini coefficient, high net worth, illegal immigration, income inequality, income per capita, Joseph Schumpeter, means of production, open borders, Pareto efficiency, plutocrats, purchasing power parity, Simon Kuznets, very high income, Vilfredo Pareto, Washington Consensus, zero-sum game

Communist Party and economic cycles and education and employment and Gini coefficient for income distribution in innovation and interpersonal inequality and proletariat revolution and wages and workers and Society capitalism and class and intercountry inequality and Socrates Solidarity Somalia South Africa South Dakota South Korea Soviet Union collapse of communism, end of and GDP per capita in global inequality and household surveys in intercountry inequality and interpersonal inequality and interrepublican inequality in See also Russia Spain global inequality and migration and soccer clubs in Stalinism Stalinization Standard of living migration and Sudan Sussman, Nathan Sweden Switzerland Tacitus, Cornelius Taiwan Tajikstan Tanzania Taxation capitalism and direct disposable income and economic growth and education and government spending and income distribution and interpersonal inequality and investment and poor and voting and workers and Technology developed countries and economic development and economic growth and embedded globalization and Newton principle and poor countries and Tennessee Texas Thailand Thatcher, Margaret A Theory of Justice (Rawls) Third World Tianjin, China Tiberius (Emperor) Tibet, China Tocqueville, Alexis de Tolstoy, Leo Trade Trajan (Emperor) Tripoli Trotsky, Leon Tunisia Turkey Twain, Mark Ukraine Unemployment United Kingdom.

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society and taxation and wages and welfare Carnegie, Andrew Cassius Dio Cavafy, Constantine Center of Reception and Emergency Aid, Italy Chad Charity Chávez, Hugo Chelsea soccer club Chiang Kai-shek Chile China direct foreign investment in economic growth in GDP per capita in Gini coefficient for global inequality and growth rate in household surveys in income distribution in intercountry inequality and interpersonal inequality and population in price level in Chongqing, China Christianization Citizenship Clark, Gregory Class income distribution and interpersonal inequality and society and solidarity and Clinton, Bill Cohen, Joshua Collins, Reverend William Colquhoun, Robert Commodus (Emperor) Communism intercountry inequality and interpersonal inequality and The Communist Manifesto (Marx) Communist Party Congo Constantine the Great (Emperor) Coprosperity sphere Corsica Cosmopolitans (in political philosophy) Crassus, Marcus Croesus, Greek King Cuba Cultural Revolution (China) Czech Republic Czechoslovakia Dalton, Hugh Darcy, Mr.

…

Das Kapital (Marx) De Silva, Lula Deglobalization See also Globalization Democracy Democratic Party, Democrats Deng Xiaoping Denmark Developed countries household surveys and interpersonal inequality and technology and Discrimination Disney Productions Djilas, Milovan Domestic Servant Pocket Register Dominican Republic Dostoyevsky, Fyodor Dreams from My Father (Obama) East Germany Economic development in China education and income distribution and in India interpersonal inequality and social monopoly and taxation and technology and Economics geopolitics and income distribution and neoclassical Edgeworth, Francis Education economic development and interpersonal inequality and poor and socialism and taxation and wealth and Egypt “80/20 Law,” El Salvador Elites communist income distribution and interpersonal inequality and Employment government socialism and Engels, Friedrich England. See Great Britain Epicureanism, Epicureans Equal purchasing power. See PPP Equally distributed equivalent income Estonia Ethics Ethiopia EU. See European Union Europe communism, end of and global inequality and income divergence in intercountry inequality and soccer clubs in European Court of Justice European Union (EU) GDP per capita in Gini coefficient for global inequality and income inequality in interpersonal inequality and soccer clubs and United States vs.

Global Inequality: A New Approach for the Age of Globalization by Branko Milanovic

Asian financial crisis, assortative mating, Berlin Wall, bitcoin, Black Swan, Branko Milanovic, Capital in the Twenty-First Century by Thomas Piketty, centre right, colonial exploitation, colonial rule, David Ricardo: comparative advantage, deglobalization, demographic transition, Deng Xiaoping, discovery of the americas, European colonialism, Fall of the Berlin Wall, Francis Fukuyama: the end of history, full employment, Gini coefficient, Gunnar Myrdal, income inequality, income per capita, invisible hand, labor-force participation, liberal capitalism, low skilled workers, Martin Wolf, means of production, military-industrial complex, mittelstand, moral hazard, Nash equilibrium, offshore financial centre, oil shock, open borders, open immigration, Paul Samuelson, place-making, plutocrats, post scarcity, post-industrial society, profit motive, purchasing power parity, Ralph Nader, Robert Solow, Second Machine Age, seigniorage, Silicon Valley, Simon Kuznets, special economic zone, stakhanovite, trade route, transfer pricing, very high income, Vilfredo Pareto, Washington Consensus, women in the workforce

Figure 2.2 shows the relationship: for a mean income level equal to subsistence, the maximum Gini coefficient is 0. It then gradually increases as mean income exceeds subsistence, and when it exceeds it by 15–20 times, the maximum Gini coefficient is close to 1 (or to 100 if expressed in percent).6 FIGURE 2.2. Inequality possibility frontier: the locus of maximum feasible Gini coefficients as a function of mean income level This graph shows the maximum feasible inequality (measured by the Gini coefficient) for various levels of average per capita income. Maximum feasible inequality is defined as maximum inequality under the condition that no person has an income lower than subsistence.

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It could perhaps be said that inequality during that period followed the usual pattern of increase with capitalist development (similar to what is happening today), but that explanation implies that inequality in a capitalist system inexorably rises unless it is checked by wars, other calamities, or political action, a statement which is manifestly at odds with reality: periods of decreasing inequality driven by economic forces have occurred under capitalism. Even technically, inequality (whether estimated by top income shares or by Gini coefficients), is, unlike GDP per capita, bounded from above and cannot keep on rising forever. More realistically (not simply because the Gini coefficient ranges in value from 0 to 1), it is bounded from above by such factors as the complexity of modern societies, social norms, large social transfer systems funded by taxation, and the threat of rebellion.

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This idea underlies the “inequality possibility frontier” as defined by Milanovic, Lindert, and Williamson (2011): when the mean income is just slightly above subsistence and we “require” that population not decline, then the surplus above subsistence must be small, and even if entirely taken by the elite, it cannot result in huge inequality (measured across the entire population). This is because all but a tiny elite will have the same income. But as the mean income rises, the surplus above the subsistence level increases as well, and the possible, or feasible, inequality becomes greater. The inequality possibility frontier is a locus of maximum feasible inequality levels (measured by the Gini coefficient) that obtain for different values of mean income. The frontier is concave: maximum feasible inequality increases with mean income but at a decreasing rate. Figure 2.2 shows the relationship: for a mean income level equal to subsistence, the maximum Gini coefficient is 0.

Termites of the State: Why Complexity Leads to Inequality by Vito Tanzi

accounting loophole / creative accounting, Affordable Care Act / Obamacare, Alan Greenspan, Andrei Shleifer, Andrew Keen, Asian financial crisis, asset allocation, barriers to entry, basic income, behavioural economics, bitcoin, Black Swan, Bretton Woods, business cycle, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, Cass Sunstein, central bank independence, centre right, clean water, crony capitalism, David Graeber, David Ricardo: comparative advantage, deindustrialization, Donald Trump, Double Irish / Dutch Sandwich, experimental economics, financial engineering, financial repression, full employment, George Akerlof, Gini coefficient, Gunnar Myrdal, high net worth, hiring and firing, illegal immigration, income inequality, indoor plumbing, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Jean Tirole, John Maynard Keynes: Economic Possibilities for our Grandchildren, Kenneth Arrow, Kenneth Rogoff, knowledge economy, labor-force participation, libertarian paternalism, Long Term Capital Management, low interest rates, market fundamentalism, means of production, military-industrial complex, moral hazard, Naomi Klein, New Urbanism, obamacare, offshore financial centre, open economy, Pareto efficiency, Paul Samuelson, Phillips curve, price stability, principal–agent problem, profit maximization, pushing on a string, quantitative easing, rent control, rent-seeking, Richard Thaler, road to serfdom, Robert Shiller, Robert Solow, Ronald Coase, Ronald Reagan, Second Machine Age, secular stagnation, self-driving car, Silicon Valley, Simon Kuznets, synthetic biology, The Chicago School, The Great Moderation, The Market for Lemons, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, transfer pricing, Tyler Cowen: Great Stagnation, universal basic income, unorthodox policies, urban planning, very high income, Vilfredo Pareto, War on Poverty, Washington Consensus, women in the workforce

The cited IMF study reported that in recent years popular support for redistribution policies has increased especially in countries, such as China, Finland, Germany, and several Eastern European countries, where the Gini coefficient has increased the most, while that support has declined in countries, such as Bulgaria, Mexico, Peru, and Ukraine, where the Gini coefficient has decreased. The evidence for the United States is more ambiguous, at least as indicated by surveys and, perhaps, by the results of the 2016 elections. If governmental intervention is called for to deal with the growing income inequality, at what costs should that intervention take place? What instruments should the government use? And what results should it aim to achieve?

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., 99, 305–6 Heller, Walter, 56 Hemingway, Ernest, 399 Hicks, John, 378 High net worth individuals (HNWIs) marginal tax rates for, 373–75 taxation of, 368 tax avoidance by, 370, 382 Hitler, Adolf, 2–3, 27 Hobbes, Thomas, 7–8, 90 Hollande, François, 113–14 Hong Kong public spending in, 121–22 taxation in, 381 Hoover, Herbert, 24–25 Hoover Dam, 241, 256 Housing mortgage crisis, 107–8, 116, 140–41 as public good, 180–81 Hugo, Victor, 358–59 Hull, Cordell, 25 Human capital, income redistribution and, 193 Hume, David, 71 IBM, 347, 377 “Idea factories,” 344–45 “Image rights,” 347–49 Immigration, 262 Implementing regulations, 333 Import duties, 15–16, 34 434 Index Incentives income redistribution and, 306 intellectual property and, 362–63, 365 in Italy, 381 marginal tax rates and, 83 as policy tool, 135 public spending as disincentive, 74–75 social norms versus, 398 tax incentives, 135, 380–81 Income effect, 372–73 Income inequality generally, 205–6 overview, 315 in Argentina, 221 in bonuses, 82–83, 85–86 in Brazil, 221 in China, 221, 227, 322 conservatives and, 394–95 “crony capitalism” and, 343 debate regarding, 322 democracy and, 400 dependent workers and, 221, 316, 387 economic aristocracy and, 117–18 envy and, 319–21 in executive compensation, 82–83, 85–86, 105–6 ex post income distribution and, 118, 119 externalities and, 321 in France, 306 Gini coefficient. See Gini coefficient as government failure, 225 Hayek on, 227 importance of, 393 increase in, 316 in India, 221, 227 intellectual property, effect of, 343–45 justification of, 105, 117 Keynes on, 320 lack of confidence caused by, 387 legal rules and, 257, 323 “luck” and, 321–23 market fundamentalism and, 342–43 middle class and, 206–7 national governments, limitations of, 393–94 negative effects on, 389 “new aristocracy” resulting from, 399 Pareto Welfare Criterion and, 318–19 progressive taxes, and decline in, 343–44 psychological effects of, 319–21 public spending and, 228–29 relative income hypothesis, 319 removal of conditions of, 118–19 role of government, 317 in Russia, 306, 322 “safety nets,” 207–8 Smith on, 305, 306, 320, 321 social acceptance of, 398 social costs of, 206, 305–6 spending habits and, 216–17 taxation and, 368–69, 382 in UK, 315 undesirable effects of market on, 322 unions, and decline in, 342 urbanization and, 206 in US, 161–62, 208–9, 221, 224, 227, 315–16, 389, 391–92 working class and, 206–7 Income redistribution allocation of resources versus, 220, 224 athletes and, 204–5 basic minimum income, 212 Burke on, 215, 219, 300, 312–13 certifications and, 193 composers and, 203 debate regarding, 209, 219, 317 democracy and, 223 in Denmark, 210 dependency and, 209–10 deregulation and, 197 economic freedom and, 159–60 education and, 193 effects on, 191–92 explicit government actions, 192, 200–1.

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These developments would have important economic ramifications in future years. Perhaps not unrelated to these developments, and indicating how the world was changing at that time, in 1912 an Italian statistician, Corrado Gini, had proposed a way to measure income inequality in countries. The use of the so-called Gini coefficient, which soon became a popular statistic, may indicate that income inequality had become a serious social concern by that time. Workers’ associations and labor unions were being created in various countries and were pushing for more rights and better working conditions for workers. Some of the labor unions would acquire increasing political and economic power with the passing of time, especially, but not only, in Europe.

Unsustainable Inequalities: Social Justice and the Environment by Lucas Chancel

"World Economic Forum" Davos, Anthropocene, behavioural economics, biodiversity loss, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, carbon tax, centre right, clean water, COVID-19, disinformation, Donald Trump, energy security, energy transition, financial deregulation, Francis Fukuyama: the end of history, Gini coefficient, green new deal, income inequality, Indoor air pollution, job satisfaction, low skilled workers, offshore financial centre, oil shock, price stability, purchasing power parity, Ronald Reagan, Simon Kuznets, The Spirit Level, The Theory of the Leisure Class by Thorstein Veblen, Thorstein Veblen, trade liberalization, Tragedy of the Commons, transaction costs, urban planning, very high income, Washington Consensus

For the moment, the few studies that do make use of individual-level data do not suffice to decide the matter one way or the other.17 Even so, Wilkinson and Pickett offer a cogent explanation of the connection between inequality and public health that deserves to be taken very seriously. Figure 1.1. Income inequality and social well-being. Disposable income inequality measured in terms of the Gini coefficient. In Japan, where the level of inequality is low, health and social well-being scores are the highest among OECD countries. Data for 2005. Sources and series: Wilkinson and Pickett (2010); www.lucaschancel.info/hup. INEQUALITY, HEALTH, AND ANXIETY How does economic inequality affect the physical and mental health of individuals? Wilkinson and Pickett insist on the cardinal importance of public services. The high quality of such services in the least inegalitarian societies, especially in connection with health care, has positive effects that are almost universally felt.

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A few countries have managed to resist this trend: Belgium, France, and the Netherlands have done better than most of their European neighbors—even if income and wealth differentials have widened in these same countries over the past three decades. The Gini coefficient has one advantage by comparison with other measures: its panoramic view. The Gini coefficient tells us about changes in inequality in society as a whole—or, more precisely, it yields a composite picture of inequality in the distribution of income in a given society. It has the disadvantage, however, of failing to capture deepening inequality at the bottom and the top of the social pyramid. Moreover, it can mask significant developments in the middle, notably the inability of middle-class incomes in recent decades to keep pace with the gains registered by other segments of society.

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The Historical Evolution of Inequality The Gini coefficient is a composite measure of inequality having a value of zero when there is perfect equality and a value of one (or 100 percent) when there is perfect inequality, that is, when only one person owns all available resources. Let us begin by considering Gini coefficients of income inequality for different countries, which since the beginning of the twentieth century have never fallen below 20 percent and never exceeded 68 percent. Changes in the coefficient’s value over the past thirty years reveal a sustained rise in income inequality in almost all developed countries, with the most pronounced increases occurring in the United States and in Scandinavia, a region that had a low level of inequality at the beginning of the 1980s.

A Pelican Introduction Economics: A User's Guide by Ha-Joon Chang

"there is no alternative" (TINA), Affordable Care Act / Obamacare, Alan Greenspan, Albert Einstein, antiwork, AOL-Time Warner, Asian financial crisis, asset-backed security, bank run, banking crisis, banks create money, Bear Stearns, Berlin Wall, bilateral investment treaty, borderless world, Bretton Woods, British Empire, call centre, capital controls, central bank independence, Charles Babbage, collateralized debt obligation, colonial rule, Corn Laws, corporate governance, corporate raider, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, David Ricardo: comparative advantage, deindustrialization, discovery of the americas, Eugene Fama: efficient market hypothesis, eurozone crisis, experimental economics, Fall of the Berlin Wall, falling living standards, financial deregulation, financial engineering, financial innovation, flying shuttle, Ford Model T, Francis Fukuyama: the end of history, Frederick Winslow Taylor, full employment, George Akerlof, Gini coefficient, Glass-Steagall Act, global value chain, Goldman Sachs: Vampire Squid, Gordon Gekko, Great Leap Forward, greed is good, Gunnar Myrdal, Haber-Bosch Process, happiness index / gross national happiness, high net worth, income inequality, income per capita, information asymmetry, intangible asset, interchangeable parts, interest rate swap, inventory management, invisible hand, Isaac Newton, James Watt: steam engine, Johann Wolfgang von Goethe, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, joint-stock company, joint-stock limited liability company, Joseph Schumpeter, knowledge economy, laissez-faire capitalism, land bank, land reform, liberation theology, manufacturing employment, Mark Zuckerberg, market clearing, market fundamentalism, Martin Wolf, means of production, Mexican peso crisis / tequila crisis, Neal Stephenson, Nelson Mandela, Northern Rock, obamacare, offshore financial centre, oil shock, open borders, Pareto efficiency, Paul Samuelson, post-industrial society, precariat, principal–agent problem, profit maximization, profit motive, proprietary trading, purchasing power parity, quantitative easing, road to serfdom, Robert Shiller, Ronald Coase, Ronald Reagan, savings glut, scientific management, Scramble for Africa, search costs, shareholder value, Silicon Valley, Simon Kuznets, sovereign wealth fund, spinning jenny, structural adjustment programs, The Great Moderation, The Market for Lemons, The Spirit Level, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, Thorstein Veblen, trade liberalization, transaction costs, transfer pricing, trickle-down economics, Vilfredo Pareto, Washington Consensus, working-age population, World Values Survey

In many societies, people with a ‘wrong’ caste, ethnicity, religion, gender, sexuality or ideology have been denied access to things like political office, university places or high-status jobs. Measuring inequality: the Gini coefficient and the Palma ratio Of all these inequalities, only income and wealth inequalities are readily measurable. Of these two, the data on wealth are much poorer, so most of the information on inequality we see is in terms of income. Income inequality data are sometimes derived from surveys on consumption, rather than actual incomes, which are harder to capture. There are number of different ways of measuring the extent to which income is unequally distributed.5 The most commonly used measure is known as the Gini coefficient, named after the early twentieth-century Italian statistician Corrado Gini.

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REAL-LIFE NUMBERS In theory, the Gini coefficient can be anything between 0 and 1. In practice, these extreme values are impossible. No society, however egalitarian it may be in spirit and policies, can make everyone exactly equal, which is what is needed for a Gini coefficient of 0. In a society with a Gini of 1, everyone except one person who has everything will soon be dead.* In real life, no country has a Gini coefficient below 0.2 and none has one above 0.75. Lowest and highest inequalities: Europe vs. Southern Africa and Latin America Gini coefficients can differ quite a lot even for the same country, depending on the estimate you look at.

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Known as the Palma ratio, this number overcomes the Gini coefficient’s over-sensitivity to the changes in the middle of the income distribution, where it is more difficult to make a difference through policy intervention anyway.8 Inequality among whom? Most inequality figures, like the Gini coefficient, are calculated for individual countries. However, with increasing integration of national economies through globalization, people have become more interested in the changes in the income distribution for the world as a whole. This is known as the global Gini coefficient and calculated by treating each individual in the world as if they are the citizens of the same country. Some people, myself included, think that the global Gini coefficient is really not terribly relevant, as the world is not (at least yet) a true community. Income inequality matters only because we have feelings – positive, negative, solidaristic, murderous – in relation to those others who are included in the statistics; this is known as the reference group.

99%: Mass Impoverishment and How We Can End It by Mark Thomas

"there is no alternative" (TINA), "World Economic Forum" Davos, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, additive manufacturing, Alan Greenspan, Albert Einstein, anti-communist, autonomous vehicles, bank run, banks create money, behavioural economics, bitcoin, business cycle, call centre, Cambridge Analytica, central bank independence, circular economy, complexity theory, conceptual framework, creative destruction, credit crunch, CRISPR, declining real wages, distributed ledger, Donald Trump, driverless car, Erik Brynjolfsson, eurozone crisis, fake news, fiat currency, Filter Bubble, full employment, future of work, Gini coefficient, gravity well, income inequality, inflation targeting, Internet of things, invisible hand, ITER tokamak, Jeff Bezos, jimmy wales, job automation, Kickstarter, labour market flexibility, laissez-faire capitalism, Larry Ellison, light touch regulation, Mark Zuckerberg, market clearing, market fundamentalism, Martin Wolf, Modern Monetary Theory, Money creation, money: store of value / unit of account / medium of exchange, Nelson Mandela, Nick Bostrom, North Sea oil, Occupy movement, offshore financial centre, Own Your Own Home, Peter Thiel, Piper Alpha, plutocrats, post-truth, profit maximization, quantitative easing, rent-seeking, Robert Solow, Ronald Reagan, Second Machine Age, self-driving car, Silicon Valley, smart cities, Steve Jobs, The Great Moderation, The Wealth of Nations by Adam Smith, Tyler Cowen, warehouse automation, wealth creators, working-age population

This is the concept behind the Gini coefficient, which is defined as the area between the grey cumulative wealth curve and the black equal distribution line divided by the area of the triangle. The Gini coefficient for a population with perfect equality would be zero, and the coefficient for a population with perfect inequality would be 1.00. The lower the Gini coefficient the lower the inequality and vice versa. Figure 9: Wealth distribution in a population of 10 people The levels of income (as opposed to wealth) inequality, as measured by the Gini coefficient, for some of the leading countries in the world are shown in the table below.

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This difference goes some way to explaining the large disparity between average wealth and median wealth in the United States. GINI COEFFICIENT One of the most widely-used measures of inequality is the Gini coefficient. The Gini coefficient is best understood graphically: Figure 9 overleaf shows the same data as Figure 6 above. The black line represents a perfectly equal distribution of wealth, and the grey line represents the actual distribution taken from the table above. The gap between the two is a measure of inequality. Perfect inequality would see the line run flat along the bottom until we reach Person 10 at which point it would shoot up vertically. The lines of perfect equality and perfect inequality together make a triangle.

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Figure 9: Wealth distribution in a population of 10 people The levels of income (as opposed to wealth) inequality, as measured by the Gini coefficient, for some of the leading countries in the world are shown in the table below. Figure 10: Income inequality by country Country Gini Coefficient USA 0.39 UK 0.351 Greece 0.34 Spain 0.335 Italy 0.327 France 0.306 Germany 0.289 Switzerland 0.285 Sweden 0.274 Finland 0.26 Norway 0.253 Denmark 0.249 Source: OECD8 Clearly no country has perfect income equality – which would correspond to a Gini coefficient of zero. In fact, almost all countries have a Gini coefficient of above 0.25. Equally, no country has perfect inequality – which would correspond to a Gini coefficient of 1.0 and mean that one person had all the wealth.

Democracy and Prosperity: Reinventing Capitalism Through a Turbulent Century by Torben Iversen, David Soskice

Andrei Shleifer, assortative mating, augmented reality, barriers to entry, Big Tech, Bretton Woods, business cycle, capital controls, Capital in the Twenty-First Century by Thomas Piketty, central bank independence, centre right, clean tech, cloud computing, collateralized debt obligation, collective bargaining, colonial rule, confounding variable, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, deindustrialization, deskilling, Donald Trump, first-past-the-post, full employment, general purpose technology, gentrification, Gini coefficient, hiring and firing, implied volatility, income inequality, industrial cluster, inflation targeting, invisible hand, knowledge economy, labor-force participation, liberal capitalism, low skilled workers, low-wage service sector, means of production, middle-income trap, mirror neurons, mittelstand, Network effects, New Economic Geography, new economy, New Urbanism, non-tariff barriers, Occupy movement, offshore financial centre, open borders, open economy, passive investing, precariat, race to the bottom, radical decentralization, rent-seeking, RFID, road to serfdom, Robert Bork, Robert Gordon, Silicon Valley, smart cities, speech recognition, tacit knowledge, The Future of Employment, The Great Moderation, The Rise and Fall of American Growth, the strength of weak ties, too big to fail, trade liberalization, union organizing, urban decay, vertical integration, Washington Consensus, winner-take-all economy, working-age population, World Values Survey, young professional, zero-sum game

Indeed, we argue in this book that the reforms that enabled the knowledge economy to take off created huge inequalities, yet were supported by a majority of voters. Those left out of the new economy are generally also weak in the political system. Indeed, a recurrent theme of this book is that democracy, not capitalism, is to blame for the rise of low-end inequality. Phrased positively, greater equality is a democratic choice, which is little constrained by capital. FIGURE 1.1. Measures of distribution of income, 2010 vs. 1985. (a) Gini coefficients of market (circles) and disposable (squares) household income; (b) Disposable income of median relative to disposable income of mean (working-age population).

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No matter what measure is used, inequality has risen significantly since the 1980s across all ACDs. For example, Piketty shows that the top decile share of US national income rose from about thirty-five percent in 1980 to about forty-seven percent in 2010 (Piketty 2014, 24). Goldin and Katz (2007) show a similar rise in US wage inequality. Across twenty-two ACDs the Gini coefficient of market household income has risen an average of eleven percent from 1985 to 2014, according to data from Solt (2016), and the disposable income Gini (after taxes and transfers) increased a more modest seven percent. (The pattern is illustrated in figure 1.1, panel a.) Yet there has been no corresponding decline in the YD/Ȳ ratio if we proxy YD by median disposable income and Ȳ by mean disposable income.

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., 223, 226 Hong Kong, 4, 26, 279n3 housing, 41, 79, 177, 197, 200, 201, 203, 206, 225–26, 231, 275 Hovenkamp, Herbert, 153 human capital, 3, 53, 58, 101, 206, 229, 281n18 IBM, 175, 186 immigrants: closing access to, 43; democracy and, 88–89, 275; education and, 45, 89, 194, 217, 223, 226, 283n13; knowledge economies and, 136, 160, 193–94, 206, 215–17, 223, 226–27, 234, 237, 249; outsourcing and, 118, 193–94, 222; populism and, 45, 216–17, 223, 226–27, 234, 237, 239, 249; squattocracy and, 88 income distribution, 21, 25, 56, 116, 181, 221, 252, 274 industrialization: capitalism and, 4, 37–38, 53, 58, 60, 101, 124, 203; deindustrialization and, 18, 43, 103, 117–20, 124, 134–35, 180, 203, 224; democracy and, 4, 37, 53–62, 65–66, 79, 83, 88–92, 98, 101; feeder towns and, 108–9, 224; Fordism and, 103, 108, 117–20, 124, 134–35; growth and, 68, 92, 111, 115, 177, 181; knowledge economies and, 180–81, 203, 224; Nazism and, 75, 77; populism and, 224; protocorporatist countries and, 60–62, 65, 79, 89–90, 98, 101; urban issues from, 83–84 Industrial Relations and European State Traditions (Crouch), 58 industrial revolution, 5, 12, 58, 293, 295 inequality: capitalism and, 1, 5, 9, 20, 22, 24–26, 40–41, 125, 139, 261, 268, 273–74, 282n22; fall in, 5, 35; Fordism and, 107, 116–20, 125, 213; globalization and, 1, 3, 22, 26; Italy and, 36; knowledge economies and, 41–45, 139–41, 192, 197, 219–23, 228; majoritarianism and, 22; middle class and, 3, 20, 22–23, 41–43, 140, 222–23, 228, 273, 281; populism and, 219–23, 228; poverty and, 3, 5, 18–19, 25, 43, 47, 109, 117, 142, 221, 237; redistribution and, 1, 3, 20, 40–46, 140, 220, 222, 273; rise in, 1, 3, 9, 23, 40–46, 282n25; Robin Hood Paradox and, 220; undeserving poor and, 43, 142, 160, 216, 222, 227; United Kingdom and, 36; upper class and, 41, 158, 261; welfare and, 3, 8, 18–21, 31, 39–40, 42, 43, 115, 123–25, 128, 131, 137, 223, 261, 273, 282n22 inflation: capitalism and, 253, 285n9; Fordism and, 120–21; knowledge economies and, 151–52, 153, 163, 168–73, 176, 178, 202, 207, 234 Information and Communication Technology (ICT): capitalism and, 261, 266, 276; decentralization and, 3, 163, 186, 190, 276; democracy and, 261, 266, 276; Denmark and, 175; Fordism and, 102, 118; France and, 182; Germany and, 176, 180; globalization and, 198; knowledge economies and, 136–44, 156, 163, 171, 175–76, 180–90, 193, 195, 198, 214, 238, 249; outsourcing and, 118, 193–94, 222; physical skills and, 193; populism and, 238, 249; revolution of, 3, 5, 102, 136–43, 156, 163, 171, 176, 182–88, 193, 195, 198, 214, 238, 249, 276; routine tasks and, 193; shocks and, 136, 138, 214; skilled labor and, 41, 102, 185–86, 190, 193, 195, 198, 218, 276; smart cities and, 194–95; societal transformation and, 138–43 Inglehart, Ronald, 235, 246, 287n1 innovation: assembly lines and, 104, 108; capitalism and, 2, 6–12, 19, 31–34, 47, 128, 131, 157, 206, 258, 281n18; competition and, 6, 10–12, 31–35, 47, 128, 131, 173, 182–83, 258, 285; democracy and, 87, 258, 262, 267, 271; Fordism and, 104, 128, 131; knowledge economies and, 141, 152, 157–58, 173–75, 180–83, 196, 198, 205–7; manufacturing and, 33; middle-income trap and, 27; multinational enterprises (MNEs) and, 2, 40, 279n1; patents and, 7, 12–15, 26, 27, 145, 201, 281n15, 285n6; political economy and, 2, 7–8, 34, 183; production and, 10, 40, 262, 271; productivity and, 19, 34; public goods and, 35, 258; research and, 2, 12, 40; skilled labor and, 2, 6–12, 19, 27, 31–34, 104, 128, 141, 174, 196, 198, 258, 262, 271, 281n18; specialization and, 8, 14, 198, 267, 271 institutional frameworks: capitalism and, 31–34, 47–49, 128–29, 131, 146; comparative advantage and, 31, 33, 49, 51, 131; democracy and, 97; Fordism and, 128–31; knowledge economies and, 138, 146, 150, 156; unions and, 32–33 intellectual property, 31, 128, 131, 145 Internal Revenue Service (IRS), 42 International Accounting Standards Board (IASB), 208 International Monetary Fund (IMF), 38, 149–50 Ireland: capitalism and, 4; democracy and, 62, 282n2; Fordism and, 106, 121; Gini coefficients and, 36; knowledge economies and, 147–48, 150, 154, 166, 170, 230, 233; laborist unionism and, 62; middle-income trap and, 26; patents and, 27; taxes and, 17 Israel, 4, 25, 26, 28, 36, 81, 85, 96, 166 ISSP data, 165, 168 Italy: capitalism and, 4, 77, 148; democracy and, 77, 91, 99, 276, 282n2; education and, 166, 248; Five Star Movement and, 248, 276; Fordism and, 106, 120–21, 132; Gini coefficents for, 25, 36; inequality and, 36; knowledge economies and, 147–48, 150, 154, 166, 221, 233, 236, 242, 245, 248; Lega and, 248, 276; median income and, 25; Mussolini and, 77; populism and, 221, 233, 236, 242, 245, 248; postwar, 4; taxes and, 17 Iversen, Torben, 124, 135, 168, 211, 229, 251, 281n14 Japan: Abe and, 218; authoritarianism and, 279n2; capitalism and, 4, 11, 49, 55, 148, 282n2; education and, 166, 232, 241, 284n4; Fordism and, 106, 109, 284n4; Gini coefficients and, 25, 36; Keiretsu and, 182; knowledge economies and, 147–48, 150, 154, 166, 182, 207, 209, 218, 221, 232, 233, 236, 239, 241, 242, 244, 284n4; LDP and, 218; median income and, 25; populism and, 218, 221, 232, 233, 236, 239, 241, 242, 244; postwar, 4; tertiary educational spending and, 231–32 Johnson, Simon, 282n22 journeymen, 61, 65 Kalyvas, Stathis N., 92, 95 Katz, Jonathan N., 133 Katznelson, Ira, 62–63, 70, 283n13 Kees Koedijk, Jeroen Kremers, 154–55 Keynesianism, 115, 121, 145, 201, 207, 286n12 Kitschelt, Herbert, 234 knowledge economies: analytic skills and, 186; Asia and, 142, 144, 222, 229, 235, 241, 243; Australia and, 147–48, 150, 153, 166, 221, 233, 236, 242; Austria and, 230, 233, 245; Belgium and, 147–48, 150, 154, 233, 245; big-city agglomerations and, 194–200; Canada and, 147–48, 150, 154, 166, 221, 233, 236, 242, 245; centralization and, 146, 151–52, 156, 173, 186, 202, 209, 231, 243, 252; changing skill sets and, 184–94; colocation and, 159, 185–88; competition and, 139, 146, 149, 152–56, 162–63, 166–69, 173, 177, 181–82, 186, 194, 198, 208, 218, 222–23, 226, 236, 285n5, 285n6, 285n9; conservatism and, 169–72, 218–19; cooperative labor and, 152–56; Coordinated Market Economies (CMEs) and, 152, 169, 171–81, 198, 232; decentralization and, 3, 18, 138, 144, 146–52, 156, 163, 172–74, 180, 183–84, 186, 190, 193, 196, 212, 217, 225, 234, 275; Denmark and, 147–48, 150, 154, 166, 169, 171–76, 181, 203, 221, 233, 245; deregulation and, 145, 173, 183; economic geography and, 138, 140, 144–47, 159, 161, 185, 188, 191–92, 195–97, 200–6; education and, 138–48, 156–68, 174–81, 184–86, 191–200, 204, 214, 217, 219, 222–25, 228–47, 250–52, 255–56, 284n2, 284n4, 285n9, 286n11, 286n12, 287n1; electoral systems and, 163–68, 212, 217–18, 228; elitism and, 9, 141, 158, 179, 184, 214, 216, 226, 235, 243–44, 248–51, 287n3; embedded, 137–38, 143–56, 161–83, 185, 188, 191–92, 195, 205, 214, 225, 251; financial crisis and, 177, 206–14; financialization and, 149–51; Finland and, 147–48, 150, 154, 166, 221, 233, 236, 241, 242, 245; first-order effects and, 120, 129, 132–33, 216; Fordism and, 140, 142–43, 146–49, 152, 154, 160, 169, 181–82, 189, 192, 194, 200–1, 214, 216, 219–25, 237–38, 240, 248–49, 277; foreign direct investment (FDI) and, 139, 145, 147, 148, 154, 163, 193, 198–99, 200, 284n3, 285n5, 285n9; France and, 147–48, 150, 154, 166, 169, 177, 181–83, 202, 221, 233, 236, 239, 242, 245, 248; Germany and, 142, 147–48, 150, 154, 166, 169, 176–81, 191, 207, 209, 219, 221, 230, 232, 233, 236, 242, 245; globalization and, 137, 142–44, 148–49, 151, 156, 198, 206, 234, 245; Great Gatsby Curve (GGC) and, 220–23, 227–28, 247, 259, 275–76; growth and, 51, 142, 156, 162–64, 168, 170–71, 177, 179, 181, 192, 194, 218, 221, 226, 237, 247–48, 285n8, 285n9; human capital and, 206, 229; immigrants and, 136, 160, 193–94, 206, 215–17, 223, 226–27, 234, 237, 249; industrialization and, 180–81, 203, 224; inequality and, 41–45, 139–41, 192, 197, 219–23, 228; inflation and, 151–52, 153, 163, 168–73, 176, 178, 202, 207, 234; Information and Communication Technology (ICT) and, 3, 5, 136–43, 156, 163, 171, 175–76, 180–90, 193, 195, 198, 214, 238, 249; innovation and, 141, 152, 157–58, 173–75, 180–83, 196, 198, 205–7; institutional frameworks and, 138, 146, 150, 156; Ireland and, 147–48, 150, 154, 166, 170, 230, 233; Italy and, 147–48, 150, 154, 166, 221, 233, 236, 242, 245, 248; Japan and, 147–48, 150, 154, 166, 182, 207, 209, 218, 221, 232, 233, 236, 239, 241, 242, 244, 284n4; Korea and, 284n4; labor market and, 140, 152, 173–78, 183, 186, 190, 223, 229; liberalism and, 137–38, 141–56, 159, 161–83, 207–14, 228–29, 232, 241, 243, 250, 284n3, 286n11; Liberal Market Economies (LMEs) and, 152, 169, 181, 198, 230, 232; low-skilled labor and, 180, 194, 200, 212–13, 218, 223, 238, 249; macroeconomic management and, 151–52; majoritarianism and, 213, 217, 243–44, 251; manufacturing and, 142, 169, 182, 194, 197, 200–3, 224, 241; middle class and, 140, 142, 158, 163, 168, 201, 203, 218–28, 234–51; mobility and, 145, 207, 214, 217–23, 227–32, 239–42, 247, 249; modernization and, 174; multinational companies (MNCs) and, 7, 145, 147, 193, 200, 267–68, 271; multinational enterprises (MNEs) and, 2–3, 15, 40, 139, 154, 192; nation-states and, 139, 159, 161, 206, 213, 215; Netherlands and, 147–48, 150, 154, 166, 230, 232, 233, 236, 242, 245; Norway and, 147–48, 150, 154, 166, 221, 233, 236, 242, 245; OECD countries and, 153–54, 175, 196, 230–32, 233, 250; open financial markets and, 152; outsourcing and, 118, 193–94, 222; party system and, 21, 44, 51–52; physical skills and, 193; political construction of, 161–83; political decisions leading to, 156–61; political economy and, 51, 164–68, 181, 220, 226, 235; populism and, 136, 138, 140–42, 146, 161, 171, 175, 181–85, 195, 202, 205, 214–23, 226–28, 235–53, 254–56; privatization and, 154, 173; production and, 143, 152, 161, 180, 183, 224–25, 234–35, 247, 249; proportional representation (PR) systems and, 132–34, 135, 212, 217, 229, 251; public goods and, 52, 143–48, 152, 157, 167, 225; reconfigurability and, 185, 191, 214, 224; redistribution and, 48, 137, 140, 158, 168, 220, 222, 225, 234–37, 241; regulation index and, 285n5; relational skills and, 187; reputation and, 158, 163–64, 182–83, 188, 190–91; research and, 139, 146, 159, 164–65, 179, 187, 189, 196, 200, 204, 234, 285n9; routine tasks and, 193; second-order effects of, 129, 216; segregation and, 43, 107, 140, 161, 185, 192, 195, 197, 200–6, 214, 231; semiskilled labor and, 142, 172–73, 212, 238–40; shocks and, 136–40, 143, 156–59, 181, 185, 194, 214; skill clusters and, 139, 141, 144–48, 183, 185, 190–98, 200, 223; skilled labor and, 137–49, 157–58, 172–200, 211–13, 217–35, 238–41, 246, 249–52, 255–56; smart cities and, 194–95; socialism and, 137, 181–82, 215, 218; social networks and, 139, 145, 185, 188, 191–92, 195–97, 200, 204–6, 217, 225, 246; societal transformation from, 138–43; socioeconomic construction of, 183–99; South Korea and, 147–48, 150, 154, 156, 166, 232, 233, 236, 239, 241, 242; Spain and, 154, 166, 201, 221, 233, 236, 242, 248; specialization and, 139, 144–47, 161, 190–93, 198, 200, 281n21; Sweden and, 147–48, 150, 153–54, 166, 173, 221, 233, 236, 242, 245; Switzerland and, 147–48, 150, 154, 166, 221, 233, 236, 242, 245; tacit knowledge and, 2, 39, 145, 263; taxes and, 141, 157–58, 165, 167, 172, 206, 221–22, 225, 231, 281n21; technology and, 138–44, 147, 154–62, 175–76, 184–86, 192–94, 198–99, 214, 222, 226, 232, 234, 238, 246, 249, 284n1, 284n3, 285n6; trade and, 142, 145, 153–55, 163, 172–73, 180, 211–13, 218, 250; unemployment and, 170–72, 174, 178, 180, 207, 248–49, 255–56, 285n8; unions and, 152, 169–83, 212, 228, 251; United Kingdom and, 142, 147–48, 150, 152, 154, 161–63, 166, 169–77, 180–81, 194, 200–1, 204, 206, 209, 218, 232, 233, 236, 242, 245, 250; United States and, 141–42, 147–56, 162, 166, 169, 171, 177, 186, 194–95, 198, 202, 209, 215, 218–23, 230, 232, 236, 241, 244, 277; unskilled workers and, 193, 246, 255; voters and, 24, 138, 140, 158–59, 163–64, 167–68, 183, 213–19, 234–36, 245, 247; wages and, 151, 160, 172–76, 181, 196, 211–12, 219, 222–23, 227, 229; welfare and, 137, 146, 167, 176, 214, 223, 234, 249, 285n6, 285n8, 287n1; women and, 141, 151, 174, 176, 184, 195, 238; working class and, 201, 225, 231, 239, 251; World Values Survey (WVS) and, 168, 235–36, 245 knowledge-intensive businesses (KIBs), 187–90, 190 Kristal, Tali, 119 Krueger, Alan B., 220 Kulturkampf, 94–95 Kurzweil, Raymond, 264 Labor and Monopoly Capitalism: The Degradation of Work in the Twentieth Century (Braverman), 186 labor market: active labor market programs (ALMPs) and, 126–27, 135, 284n1; analytic skills and, 186; apprentices and, 61, 64–65, 68, 71, 104, 110, 127, 179–80, 230; artificial intelligence (AI) and, 260–72; artisans and, 61, 63–65, 70, 79, 94–95, 98; assembly lines and, 104, 108; big-city agglomerations and, 194–200; capitalism and, 1, 6, 12, 31, 38, 46–47, 122, 125, 128, 152, 186, 229, 258; Catholicism and, 56, 61, 63, 68, 77, 83, 87, 92, 94–95; collective bargaining and, 67, 69, 73, 92, 103, 107, 137, 176, 179; comparative advantage and, 31, 49, 51, 128, 131, 268; competition and, 12 (see also competition); craft skills and, 32, 53, 61–71, 79, 82, 90–91, 96, 98, 101, 104, 172; democracy and, 64, 66, 96–98, 260, 266, 268, 273; deregulation and, 1, 96, 122, 183; dualism and, 282n25; education and, 12, 28, 31, 41, 53–54, 60, 70, 72, 83, 89–90, 96, 98, 104, 128, 165, 174, 177, 191, 223, 225, 229, 260; flexicurity and, 174; Fordism and, 103, 118, 122–28; globalization and, 162–63 (see also globalization); guild systems and, 59, 63–64, 69–70, 90–91, 93, 96, 98; immigrants and, 45, 88–89, 136, 160, 193–94, 206, 215–17, 223, 226–27, 234, 237, 249, 275, 283n13; journeymen and, 61, 65; knowledge economies and, 140, 152, 173–78, 183, 186–90, 223, 229; laziness and, 222, 237, 254; manual jobs and, 76, 78, 226, 238–40, 246, 255–56, 264–65; mobility and, 8, 13, 59 (see also mobility); monopolies and, 6, 24, 47, 54, 64, 68, 87, 99, 114, 155, 186; outsourcing and, 118, 193–94, 222; pensions and, 41, 92, 178–79; politics of future and, 272–77; populism and, 223, 229; relational skills and, 187; retirement and, 110, 151, 201; revisionist history and, 283n9; robots and, 18, 141, 143, 184, 193, 260–66, 273; rules for, 6, 10, 12, 28, 38; semiskilled labor and, 12 (see also semiskilled labor); September Compromise and, 66; skilled labor and, 2–3, 12 (see also skilled labor); strikes and, 73, 75, 108, 116; tacit knowledge and, 2, 39, 145, 263; trade and, 17, 155 (see also trade); training and, 7, 10, 14, 31, 44, 82, 89–90, 101, 104, 109, 111, 128, 131, 174, 176, 179, 181, 204, 223, 228–29, 232–33, 241–43, 252, 257, 275, 277, 280n10; undeserving poor and, 43, 142, 160, 216, 222, 227; unemployment and, 16, 282n22, 284n2, 285n8 (see also unemployment); unions and, 6 (see also unions); vocational learning and, 31, 44, 68, 82, 89, 92, 104, 109, 113, 127–28, 131, 174, 176, 179, 228–30, 233, 242–43, 251–52, 257; welfare and, 31, 46, 96, 118, 120, 122–23, 125, 128, 176, 223, 279n5; women and, 5, 174, 176 Labour Party, 68, 169, 171 Landesbanken, 176–77 landowners, 38, 57, 80–89, 95, 98, 158 Lange, David, 171 Lapavitsas, Costas, 150 Latin America, 29, 56, 257 laziness, 222, 237, 254 Lega, 248, 276 Lehmann Brothers, 210 Le Pen, Marine, 183 Lewis-Black, Michael S., 164, 167, 285n8 liberalism: capitalism and, 1–2, 32, 49, 60, 97, 100–1, 137, 143, 213–14, 228; democracy and, 56–62, 67–71, 79–90, 96–101, 282n3, 283n14; education and, 45, 60, 71, 79, 82–83, 89–90, 101, 104, 138, 143, 156, 175, 208, 212–14, 228–29, 232, 241, 243, 284n3, 286n11; embedded, 51, 97, 137–38, 143–56, 159–83, 214; financial crisis and, 207–13; Fordism and, 103–5, 115, 125, 127; globalization and, 1, 51, 142, 155, 162–63, 208, 213; knowledge economies and, 137–38, 141–56, 159, 161–83, 207–14, 228–29, 232, 241, 243, 250, 284n3, 286n11; majoritarianism and, 33, 49, 60, 71, 97, 100–3, 125, 213, 243; middle class and, 2, 60, 71–72, 90, 96–97, 100–1, 115, 286n11; neoliberalism and, 1–2, 286n11; populism and, 228–29, 232, 241, 243, 250; protoliberal countries and, 59–61, 68, 90, 97, 100–1, 228; public goods and, 79–90; regulated, 143, 149; trade, 51, 62, 142, 155, 163, 173, 213, 250, 284n3; United Kingdom and, 32 Liberal Market Economies (LMEs): Fordism and, 103, 112, 125, 127–29; knowledge economies and, 152, 169, 181, 198, 230, 232; populism and, 230, 232 libertarians, 45, 225, 234, 237, 240, 249 Lib-Lab political parties, 62–63 Lindblom, Charles, 5–6, 11, 19, 34, 280n9 Lindert, Peter H., 81, 220, 283n11 Lipset, Seymour Martin, 4, 37, 55, 71–72, 79, 113 Lizzeri, A., 79–80, 86 LO, 19, 66, 108 loans, 110, 148, 173, 209–11 Local Government Act, 86 Louca, Francisco, 5 low-skilled labor: capitalism and, 265–66; democracy and, 97–98, 265–66; Fordism and, 119–20, 126; knowledge economies and, 180, 194, 200, 212–13, 218, 223, 238, 249; populism and, 218, 223, 238, 249; robots and, 18; unions and, 19, 47, 50, 66, 70–71, 96, 98–99, 119, 127, 181 low-wage countries, 18–19, 28 Luddites, 226 Luebbert, Gregory, 62, 69, 282n3 Lutheran Church, 72 Maastricht Treaty, 122 McAfee, A., 260 machine-based technological change (MBTC), 262 Macron, Emmanuel, 183 majoritarianism: capitalism and, 22; cross-class parties and, 125; decommodification and, 9; democracy and, 60, 71, 91–93, 97–98, 100–1; Fordism and, 103, 112–13, 124–32; inequality and, 22; institutional patterns and, 33, 49, 132, 251; knowledge economies and, 213, 217, 243–44, 251; liberalism and, 33, 49, 60, 71, 97, 100–3, 125, 213, 243; populism and, 217, 243–44, 251; proportional representation (PR) systems and, 19, 44–45, 60, 93, 100–1, 124–26, 128, 132, 217, 251; taxes and, 24, 44, 113, 124; Westminster systems and, 19 Manning, Alan, 193 Manow, Philip, 44, 92–93, 95–96, 124 manual labor, 76, 78, 226, 238–40, 246, 255–56, 264–65 manufacturing: Asian, 5, 14, 241; capitalism and, 2, 14, 33, 142, 203; democracy and, 80; feeder towns and, 108–9, 224; Fordism and, 103, 108–9, 118; innovation and, 33; knowledge economies and, 142, 169, 182, 194, 197, 200–3, 224, 241; populism and, 200–3, 224, 241; research and, 15, 200; skilled labor and, 15, 33, 44–45, 109, 118, 194, 224 Marketcraft: How Governments Make Markets Work (Vogel), 11 Marks, Gary, 68 Martin, Cathie Joe, 63 Marxism, 11, 34, 46, 62, 279n4, 280n8, 280n9 materialism, 217, 234–35, 238 median income, 23, 25 Medicare, 24, 42 Melitz model, 211–12 Meltzer-Richard model, 3 Mezzogiorno, 93 microprocessors, 14, 140, 284n1 Microsoft, 155, 186, 262 middle class: capitalism and, 2–3, 20, 22, 41, 53, 97, 101, 162, 225, 227, 257–58, 273; democracy and, 3, 20, 22–23, 35, 44, 53–55, 60, 63, 71–74, 84–85, 90, 96–101, 115, 158, 163, 168, 257–58, 273–74; education and, 3, 20, 24, 41–43, 53–55, 60, 71, 84, 90, 98, 101, 128, 158, 168, 203, 222–25, 235, 238–40, 243–44, 249, 251, 257–58, 273–74, 286n11, 287n1; encapsulation and, 227, 243, 249; Fordism and, 43, 112, 115, 117, 123, 125, 128, 142, 160, 201, 219, 222–25, 238, 248; Gini coefficients and, 23; Great Gatsby Curve (GGC) and, 220, 221, 227–28, 247, 259, 275–76; growth and, 2–3, 97, 115, 163, 168, 226; hollowing out of, 160, 219, 222, 238; inequality and, 3, 20, 22–23, 41–43, 140, 222–23, 228, 273, 281; knowledge economies and, 24, 140, 142, 158, 163, 168, 201, 203, 218–28, 234–51; liberalism and, 2, 60, 71–72, 90, 96–97, 100–1, 115, 286n11; lower, 22, 35, 42, 63, 72, 90, 98, 124, 128, 142, 158, 201, 223, 235, 238, 244, 248, 251, 273; Medicare and, 42; middle-income trap puzzle and, 8, 26–30; neoliberalism and, 2; new, 3, 43, 218, 222, 224–27, 234, 238–41, 246, 247; old, 3, 43, 140, 142, 203, 219, 222–28, 234, 237–40, 243–44, 247, 249, 287n1; populism and, 218–28, 234–51; rebirth of cities and, 224–27; redistribution and, 3, 20, 35, 42, 60, 71, 90, 98, 100, 112, 115, 123–25, 140, 158, 168, 220, 222, 225, 234, 237, 241, 273–74; skilled labor and, 3, 20, 27, 30, 35, 41–44, 71, 85, 90, 96–101, 112, 115, 123, 125, 142, 158, 193, 222, 224, 235, 239–41, 249; Social Security and, 42; taxes and, 21, 42, 124, 158, 222, 225; technology and, 3, 21, 29–30, 41, 117, 139, 222, 226, 249; upper, 2, 41–44, 72, 125, 158, 168; voters and, 2–3, 20–22, 44, 90, 96–100, 125, 140, 158, 168, 273 military, 8, 28, 33, 73, 75, 86–87, 279n2, 281n18 Mittelstand, 68, 92, 95, 179, 191 Mitterrand, François, 182 mobility: capital, 8, 16, 30, 35, 50, 145, 280n11; democracy and, 59, 258, 275–76; economic geography and, 2, 8, 18, 20, 39–40; Fordism and, 16, 118, 124, 221; France and, 59; Great Gatsby Curve (GGC), 220–23, 227–28, 247, 259, 275–76; growth and, 13, 30, 247, 276; implicit social contract and, 221–22; income classes and, 220–22; intergenerational, 13, 21, 124, 219–22, 228, 230, 232, 241–42, 275–76; knowledge economies and, 145, 207, 214, 217–23, 227–32, 239–42, 247, 249; populism and, 217–32, 239–42, 247, 249; skilled labor and, 8, 13, 20–21, 39, 124, 217, 222, 228, 232, 239, 249; as strengthening state, 50–51; taxes and, 221 modernization, 19; democracy and, 55, 57, 66, 70, 79–83, 87, 89, 98; elitism and, 38, 57, 79–80, 83, 89, 98; Fordism and, 104, 109, 114; knowledge economies and, 174; protocorporatist countries and, 79, 83; Whigs and, 80 monarchies, 72–73, 81, 87 monopolies, 6, 24, 47, 54, 64, 68, 87, 99, 114, 155, 186 Morrison, Bruce, 80 mortgages, 151, 173, 209 Muldon, Rob “Piggy”, 171 multinational companies (MNCs): artificial intelligence (AI) and, 267–68, 271; democracy and, 267–68, 271; knowledge economies and, 7, 145, 147, 193, 200, 267–68, 271; technology and, 48 multinational enterprises (MNEs): changing roles of, 279n1; competition and, 154; economic geography and, 2–3, 40, 192, 279n1; globalization and, 2–3, 15, 18, 25, 28, 40, 139, 154, 192, 279n1; immobility of, 2; innovation and, 1, 40, 279n1; knowledge economies and, 2–3, 15, 40, 139, 154, 192; skill clusters and, 192–93; skilled labor and, 28; specialization and, 192–93 Municipal Corporations Act, 86 Mussolini, Benito, 77 Nannestad, Peter, 164 nanotechnology, 141, 184 nationalism, 216, 218, 227 National Reform League, 86 nation-states: advanced capitalist democracies (ACD) and, 9–11; capitalism and, 4–13, 30, 46–50, 77, 136, 139, 159, 161, 206, 249, 261, 267–68, 272, 279n4; democracy and, 4–5, 8, 13, 46, 136, 159, 161, 213, 215, 249, 261, 267–68, 272, 279; FDI globalization and, 40; knowledge economies and, 139, 159, 161, 206, 213, 215; skilled labor and, 8, 30, 48, 139, 261; strong role of, 9–11; symbiotic forces and, 5–9, 20, 32, 53–54, 130–31, 159, 206, 249–53, 259 Nazism, 75, 77, 99, 219, 279n2 neoliberalism, 1–2, 286n11 Netherlands: democracy and, 56, 57, 61, 62–63; Fordism and, 106, 121; Gini coefficients and, 25, 36; knowledge economies and, 147–48, 150, 154, 166, 230, 232, 233, 236, 242, 245; median income and, 25; populism and, 230, 232, 233, 236, 242, 245; protocorporatist countries and, 62–63; taxes and, 17; tertiary educational spending and, 231–32 New South Wales, 94–95 New Zealand: Acts of Parliament and, 88; democracy and, 38, 56–57, 61, 62, 87–89, 283n8; Douglas and, 171; Education Act and, 89; Fordism and, 106, 132; Gini coefficients and, 25, 36; knowledge economies and, 147–48, 150, 153, 166, 171, 221, 233, 236, 242; Lange and, 171; male suffrage and, 89; Muldoon and, 171; as outlier, 23; patents in, 27 Nolan, Mary, 65–66 Nord, Philip, 59 Norris, Pippa, 235, 246, 287n1 North American Free Trade Agreement (NAFTA), 155 Norway: democracy and, 56, 57, 61, 62, 282n3; Fordism and, 106, 130; Gini coefficients and, 25, 36; knowledge economies and, 147–48, 150, 154, 166, 221, 233, 236, 242, 245; median income and, 25; populism and, 221, 233, 236, 242, 245; taxes and, 17 October Revolution, 75–76 OECD countries, 25, 38; education and, 14; Fordism and, 107, 117, 125, 133; knowledge economies and, 153–54, 175, 196, 230–32, 233, 250, 286n13; populism and, 230–32, 233, 250; taxes and, 17, 280n13 Oesch, Daniel, 234 oil crisis, 120, 171, 181 ordinary least squares (OLS) regression, 132 Osborne, Michael A., 260 outliers, 23, 232, 241 outsourcing, 118, 193–94, 222 overlapping generation (OLG) logic, 7 Paldam, Martin, 164 Panduro, Frank, 203 Paris Commune, 86 parliamentarianism, 58 partisanship, 32, 47, 91, 112, 129, 164, 171, 174 party system: democracy and, 93, 101; Fordism and, 113, 123–24; knowledge economies and, 21, 44, 51, 51–52; voters and, 21 (see also voters) patents, 7, 12–15, 26, 27, 145, 201, 281n15, 285n6 pegging, 121 pensions, 41, 92, 178–79 Persico, N., 80, 86 physical skills, 193 Pierson, Paul, 282n22 Piketty, Thomas, 1, 16, 20, 22, 30, 41–42, 117, 137, 139, 141, 163, 261, 273, 280n11, 282n22 PISA scores, 196 plantations, 38, 84 police, 96, 173–75 political economy: broad concepts of markets and, 46; capitalism and, 2–9, 12, 17, 24, 34, 45–48, 97, 112, 129, 131, 137, 160, 167, 214, 227, 251, 275; democracy and, 59, 97; economic geography and, 2–3, 8, 48–49, 140; innovation and, 2, 7–8, 34, 183; knowledge economies and, 51, 164–68, 181, 220, 226, 235; literature on, 2, 4, 6–8, 48, 114, 164, 167, 281n19; populism and, 45; spatial anchors and, 48–49 Politics Against Markets (Esping-Andersen), 30 populism: Austria and, 230, 233, 245; Belgium and, 233, 245; centralization and, 231, 243, 252; competition and, 218, 222–23, 226, 236; conservatism and, 218–19; Coordinated Market Economies (CMEs) and, 232; cross-national variance and, 241–44; decentralization and, 217, 225, 234; democracy and, 13, 45, 129, 136, 215, 217, 226, 228, 248–51, 275; Denmark and, 221, 233, 245; economic geography and, 224; education and, 217, 219, 222–25, 228–47, 250–52, 287n1; electoral systems and, 217–18, 228, 251; elitism and, 216, 226, 235, 243–44, 248–51, 287n3; Fordism and, 113, 130, 216, 218–25, 237–40, 248–49; France and, 183, 221, 233, 236, 239, 242, 245, 248; Germany and, 181, 219, 221, 230, 232, 233, 236, 242, 245; globalization and, 234, 245; Great Gatsby Curve (GGC) and, 220–23, 227–28, 247, 259, 275–76; growth and, 218, 221, 226, 237, 247–48; immigrants and, 45, 216–17, 223, 226–27, 234, 237, 239, 249; importance of economic progress and, 247–48; industrialization and, 224; inequality and, 219–23, 228; Information and Communication Technology (ICT) and, 238, 249; Italy and, 221, 233, 236, 242, 245, 248; Japan and, 218, 221, 232, 233, 236, 239, 241, 242, 244; knowledge economies and, 136, 138, 140–42, 146, 161, 171, 175, 181–85, 195, 202, 205, 214–23, 226–28, 235–53, 254–56; labor market and, 223, 229; laziness and, 222, 237, 254; liberalism and, 228–29, 232, 241, 243, 250; Liberal Market Economies (LMEs) and, 230, 232; libertarians and, 45, 225, 234, 237, 240, 249; low-skilled labor and, 218, 223, 238, 249; majoritarianism and, 217, 243–44, 251; manufacturing and, 200–3, 224, 241; materialism and, 217, 234–35, 238; middle class and, 218–28, 234–51; mobility and, 217–23, 227–32, 239–42, 247, 249; nationalism and, 216, 218, 227; national variation and, 228–34; Netherlands and, 230, 232, 233, 236, 242, 245; new materialism and, 234–35; Norway and, 221, 233, 236, 242, 245; OECD countries and, 230–32, 233, 250; political alignment and, 219–27; political cleavage and, 146, 181, 183, 228, 236–39, 241; political economy and, 45; postmaterialism and, 234–35; proportional representation (PR) systems and, 217, 229, 251; public goods and, 225; rebirth of cities and, 224–27; redistribution and, 220, 222, 225, 234–37, 241; regression analysis and, 236, 239–40, 246, 254–55; Republicans and, 218, 244–45; research and, 234; Robin Hood Paradox and, 220; root cause of, 13; rural areas and, 218, 224, 238–41, 287n1; semiskilled labor and, 238–40; sexuality and, 216–18, 225, 237, 243, 249, 254; skilled labor and, 52, 217–35, 238–41, 246, 249–52, 255–56; social contract and, 221–27; socialism and, 218; social networks and, 217, 225, 246; South Korea and, 232, 233, 236, 239, 241, 242; Sweden and, 221, 233, 236, 242, 245; Switzerland and, 221, 233, 236, 242, 245; symbiotic forces and, 249–53; taxes and, 221–22, 225, 231; technology and, 222, 226, 232, 234, 238, 246, 249; trade and, 218, 250; Trump and, 215, 218–20, 237, 243–45, 248; undeserving poor and, 43, 142, 160, 216, 222, 227; unemployment and, 248–49, 255–56; unions and, 228, 251; United Kingdom and, 13, 218, 232, 233, 236, 242, 245, 250; United States and, 13, 130, 171, 195, 215, 218–23, 230, 232, 236, 241, 244, 275; unskilled workers and, 246, 255–56; upper class and, 222, 227, 237, 253; values and, 239–41; voters and, 217–19, 234–36, 244–47, 250, 256; wages and, 219, 222–23, 227, 229; welfare and, 45, 223, 234, 249, 287n1; women and, 238; working class and, 225, 231, 239, 251; World Values Survey (WVS) and, 235–36, 245 postmaterialism, 234–35 Poulantzas, Nicos, 6, 9, 11, 19, 39, 279n4 poverty, 3, 5, 18–19, 25, 43, 47, 109, 117, 142, 221, 237 Power, Anne, 200 privatization, 1, 18, 154, 173 production: artificial intelligence (AI) and, 263; assembly lines and, 104, 108; broad market notions and, 46; clusters and, 40, 49, 183, 270–71; democracy and, 54, 60, 64–66, 69, 72–73, 83, 93–94, 258, 262–63, 267–71; feeder towns and, 108–9, 224; Fordism and, 43, 103–4, 108–11, 115–17, 123, 127; globalization and, 5, 40, 51, 258; innovation and, 10, 40, 262, 271; knowledge economies and, 143, 152, 161, 180, 183, 224–25, 234–35, 247, 249; skilled labor and, 10, 18, 35, 43, 49–50, 60, 64–65, 69, 104–5, 115, 123, 127, 180, 183, 225, 249, 258, 262, 267, 271; specialization and, 51, 108, 161, 258, 267–71; Vernon’s life-cycle and, 18 productivity, 19, 34, 118–19, 247, 261, 272 proportional representation (PR) systems: Christian democratic parties and, 44; democracy and, 19, 34, 44–45, 60–61, 91, 93, 97, 100–1, 112–13, 125–28, 132, 134, 135, 212, 217, 229, 251; Fordism and, 112–13, 124–28; green parties and, 45; knowledge economies and, 132–34, 135, 212, 217, 229, 251; liberalism and, 97; majoritarianism and, 19, 101; multiparty, 34, 44; negotiation-based environment and, 93; populism and, 217, 229, 251; redistribution and, 91; Westminster system and, 19 protectionism, 28, 41, 169 Protestantism, 61, 68 protocorporatist countries: Austria, 59, 62–63, 77, 99; Belgium, 62–63; Catholicism and, 56, 61, 63, 68, 77, 83, 87, 92, 94–95; democracy and, 59–72, 74, 77, 79, 82–83, 89–92, 98–101, 228, 283n11; entrepreneurs and, 65; France and, 59, 62; Germany and, 62–63, 65, 68 71, 74, 77, 99, 238n11; industrialization and, 60–62, 65, 79, 89–90, 98, 101; Marx and, 62; modernization and, 79, 83; Netherlands, 62–63; skilled labor and, 60, 64–66, 79, 90, 98, 101; Ständestaat group and, 59–60, 65–66, 70, 90–91, 93; Switzerland, 62–63; working class and, 60–79 protoliberal countries, 59–61, 68, 90, 97, 100–1, 228 Prussia, 72, 93 public goods: democracy and, 54, 60, 79–90, 98, 258, 275; Fordism and, 113; innovation and, 35, 258; knowledge economies and, 52, 143–48, 152, 157, 167, 225; liberalism and, 79–90; populism and, 225; role of state and, 10 Public Health Acts, 86 race to the bottom, 51, 122 Rasmussen, Poul Nyrup, 173 recession, 5, 206, 214, 247–50, 276 reconfigurability, 185, 191, 214, 224 redistribution: capitalism and, 1, 18–20, 31–32, 35, 37, 39–40, 47, 51, 55, 124, 128–31, 137, 261, 273; democracy and, 1, 8, 18–20, 32, 35, 37, 40, 55–56, 60, 69–71, 74–79, 90–91, 95–100, 115, 124, 158, 221, 259–62, 273–74, 282n3, 284n2; Fordism and, 103, 111–12, 115, 123–25, 128–29; Gini coefficients and, 22–23, 25, 36, 117, 118, 141, 221; inequality and, 1, 3, 20, 40–46, 140, 220, 222, 273; knowledge economies and, 48, 137, 140, 158, 168, 220, 222, 225, 234–37, 241; middle class and, 3, 20, 35, 42, 60, 71, 90, 98, 100, 112, 115, 123–25, 140, 158, 168, 220, 222, 225, 234, 237, 241, 273–74; populism and, 220, 222, 225, 234–37, 241; proportional representation (PR) systems and, 91; skilled labor and, 8, 20, 31, 35, 37, 47, 71, 90, 98–100, 103, 115, 123, 125, 128, 158, 220, 222, 241, 259, 261; social insurance and, 8; taxes and, 35, 40, 51, 124, 158, 221–22, 225; voters and, 3, 19–21, 32, 43, 90, 98, 100, 125, 140, 158, 273; welfare and, 3, 8, 18–21, 31, 39–40, 43, 115, 123–24, 128, 131, 137, 261, 273 Reform Acts, 56, 80–81, 85–86 Reform Crisis 1865–7, The (Searle), 85 Reform League, 86 Reform Party, 88 regional theory, 11 regression, 99–100, 132–35, 236, 239–40, 246, 254–55 Rehn-Meidner model, 19 relational skills, 187 Republicans, 38, 57, 59, 87, 218, 244–45, 282n24 reputation: colocation and, 267; consultants and, 286n15; Fordism and, 112–13; knowledge economies and, 158, 163–64, 182–83, 188, 190–91; Liberal Market Economies (LMEs) and, 112; political, 4, 12, 29, 32, 34, 112–13, 158, 163–64, 182–83, 188, 190, 258, 259, 280n9; skill clusters and, 190–91; social networks and, 191; subconscious signals and, 190 research: capitalism and, 2, 10, 12, 37, 48, 139, 159, 165, 234; democracy and, 55, 66–67, 72, 262, 264, 268, 287n1; education and, 10, 12, 20–21, 28, 48, 55, 72, 146, 159, 165, 234, 262; Fordism and, 103, 108, 110; innovation and, 2, 12, 40; knowledge economies and, 139, 146, 159, 164–65, 179, 187, 189, 196, 200, 204, 234, 285n9; manufacturing and, 15, 200; populism and, 234; skilled labor and, 2, 12, 21, 28, 37, 39, 48, 66–67, 139, 179, 187, 196, 268 retirement, 110, 151, 201 Robin Hood Paradox, 220 Robinson, James, 9, 35, 37, 56, 58, 71–72, 74, 76, 85–86, 99, 282n3 robots, 18; artificial intelligence (AI) and, 260–62; great technology debate and, 260–66; knowledge economies and, 141, 143, 184, 193; politics of future and, 273 Rodrik, Dani, 16, 22, 128 Rokkan, Stein, 66, 94, 97, 100, 113 Rueda, D., 45, 282n25 Rueschemeyer, Dieter, 56, 72–73, 75, 77, 280n6, 283n7 Ruggie, John G., 51, 143 rust belt, 224 Scheve, Kenneth, 221 Schlüter, Poul, 172 Schumpter, Joseph A., 6, 9, 11, 279n4 Scotland, 283n12 Searle, G., 85 segregation: centripetal and centrifugal forces in, 200–6; cultural choices and, 205–6; educational, 43, 119, 140, 161, 192, 195, 197, 200–6, 214, 231; Fordism and, 109, 119; geographic, 109, 140, 161, 185, 195, 197, 200–6; health and, 204–5; knowledge economies and, 43, 140, 161, 185, 195, 197, 200–6, 214, 231; private services and, 203–4; social networks and, 205–6; transport systems and, 201–3 semiskilled labor: capitalism and, 261; democracy and, 61, 64–65, 68–69, 261; Fordism and, 12, 102–5, 112, 115, 118–20, 123–24, 127, 129; knowledge economies and, 142, 172–73, 212, 238–40; populism and, 238–40; segmentation of, 43–44; technology and, 41, 43, 65, 102–5, 118–19, 127, 238, 261; undeserving poor and, 43; unions and, 61, 64–65, 68–69, 105, 119–20, 123, 172–73 September Compromise, 66 service sectors, 16, 31, 44, 51, 119, 157, 194, 200, 204, 219, 285n5 settler colonies, 84–90 sexuality, 52, 216–18, 225, 237, 243, 249, 254, 269 Sherman Act, 153 shocks: capitalism and, 6, 10, 30, 54, 125, 136, 138, 140, 156, 159, 214; democracy and, 54; Fordism and, 125–27, 132–35; Information and Communication Technology (ICT) and, 136, 138, 214; knowledge economies and, 136–40, 143, 156–59, 181, 185, 194, 214; supply, 30; technology and, 6, 30, 136, 138, 140, 143, 159, 185, 194 Simmons, Beth, 161 Singapore, 4, 26–28, 221, 282n3 Single European Act, 145, 170–71 Single Market, 122 skill-biased technological change (SBTC), 41, 238, 262, 265–66 skill clusters: big-city agglomerations and, 194–200; capitalism and, 2, 7, 49, 145, 185, 192, 261; colocation and, 2–3, 7, 15–16, 185, 261; democracy and, 261; education and, 2–3, 7, 139, 141, 145, 148, 185, 190–95, 198, 223, 261; knowledge economies and, 139, 141, 144–48, 183, 185, 190–98, 200, 223; multinational enterprises (MNEs) and, 2, 192–93; reputation and, 190–91; social networks and, 28, 139, 191–92; specialization and, 190–91; sub-urbanization and, 141 skilled labor: analytic skills and, 186; artificial intelligence (AI) and, 261–62, 265–68, 271–72; capitalism and, 2–3, 6–8, 12–15, 19–20, 30–34, 37–38, 47–50, 53–54, 58, 60, 97, 101–2, 128, 137, 139, 144–47, 157–58, 172, 185–86, 192, 218, 250–51, 258, 261, 280n6; centralization and, 53, 58, 67, 69, 96, 99, 101, 110, 119–20, 173, 186, 279n1; colocation and, 2, 7, 261, 272; competition and, 6, 12, 18, 21, 30–34, 66, 96, 119, 128, 146, 157, 181, 186, 194, 198, 218, 222–23, 258; cospecificity and, 7–15, 20, 37, 47–50, 69, 99, 101, 115, 123, 196, 259, 261; craft skills and, 32, 53, 61–71, 79, 82, 90–91, 96, 98, 101, 104, 172; decentralization and, 96, 123, 138, 144, 146, 148, 172, 183–86, 190, 193, 212, 225, 262, 276; democracy and, 3, 6, 8, 12, 20, 31, 37–38, 44, 53–54, 58–71, 79, 84–85, 90, 96–101, 115, 158, 185–86, 250, 258–62, 265–68, 271–72, 276–77; economic geography and, 2–3, 7–8, 15, 20, 31, 48, 109, 116, 144–47, 185, 191–92, 195–96, 276–77; education and, 7, 12, 20–21, 31, 37–38, 41, 54, 60, 70–71, 79, 84, 90, 101–4, 119, 127–30, 139, 142, 158, 174–76, 179–81, 184–85, 191–95, 198, 217, 222–25, 228–35, 238–40, 246, 250–52, 266; Fordism and, 12, 14, 16, 102–5, 109–12, 115–30, 222–25, 277; foreign direct investment (FDI) and, 3, 139, 145, 147, 193, 198; growth and, 8, 13, 31, 68, 97, 110, 115–16, 218, 261; Information and Communication Technology (ICT) and, 41, 102, 185–86, 190, 193, 195, 198, 218, 276; innovation and, 2, 6–12, 19, 27, 31–34, 104, 128, 141, 174, 196, 198, 258, 262, 271, 281n18; knowledge economies and, 137–49, 157–58, 172–200, 211–13, 217–35, 238–41, 246, 249–52, 255–56; manufacturing and, 15, 33, 44–45, 109, 118, 194, 224; middle class and, 3, 20, 27, 30, 35, 41–44, 71, 85, 90, 96–101, 112, 115, 123, 125, 142, 158, 193, 222, 224, 235, 239–41, 249; mobility and, 8, 13, 20–21, 39, 124, 217, 222, 228, 232, 239, 249; nation-states and, 8, 30, 48, 139, 261; overlapping generation (OLG) logic and, 7; physical skills and, 193; politics of future and, 272–77; populism and, 52, 217–35, 238–41, 246, 249–52, 255–56; production and, 10, 18, 35, 43, 49–50, 60, 64–65, 69, 104–5, 115, 123, 127, 180, 183, 225, 249, 258, 262, 267, 271; protocorporatist countries and, 60, 64–66, 79, 90, 98, 101; rebirth of cities and, 224–27; redistribution and, 8, 20, 31, 35, 37, 47, 71, 90, 98–100, 103, 115, 123, 125, 128, 158, 220, 222, 241, 259, 261; relational skills and, 187; research and, 2, 12, 21, 28, 37, 39, 48, 66–67, 139, 179, 187, 196, 268; social insurance and, 8, 35, 50, 67, 123, 125, 127, 192; social networks and, 2, 28, 48, 139, 145, 185, 191–92, 195, 197, 225, 258, 261, 267–68, 271; specialization and, 14 (see also specialization); tacit knowledge and, 2, 39, 145, 263; technology and, 3, 7, 10–14, 20, 30–31, 37, 41, 43, 48, 50, 70, 96, 102–5, 118–19, 127–28, 138–40, 144, 147, 157, 175–76, 185–86, 192–94, 198–99, 222, 232, 238, 261, 268, 277; unions and, 6, 19, 33, 47, 50, 53, 58, 60–71, 96–101, 105, 110, 119–20, 123, 127, 172–73, 176, 181, 186, 251; upper class and, 43–44, 125; upskilling and, 102, 123, 129, 174–75, 178, 228, 232, 250–51; wages and, 6, 18, 33, 41, 50, 61, 64, 67, 104–5, 110, 115, 118–24, 127, 172–76, 181, 212, 222–23, 229, 266 Slomp, Hans, 62 smart cities, 194–95 social contract, 161, 221–27 social democratic parties: Denmark and, 76–77, 181; Germany and, 62–63, 68, 72–77, 181; Norway and, 282n3; Sweden and, 19, 72, 74, 76; unions and, 6, 19, 61–63, 67–68, 72, 74, 76, 114, 181, 282n3 Social Democratic Party (SPD) [Germany], 68, 74, 76–77, 78 Social Democratic Party (Sweden), 19 social insurance, 21; democracy and, 67; Fordism and, 111; skilled labor and, 8, 35, 50, 67, 123–25, 127, 192 socialism: competition and, 11; democracy and, 11, 56, 61–63, 68, 71, 75, 94, 97, 100, 137, 181–82, 215, 218; knowledge economies and, 137, 181–82, 215, 218; populism and, 218 social justice, 115, 237 social networks: cultural choices and, 205–6; democracy and, 258, 261, 268, 270–71, 274–75; economic geography and, 48–49, 185, 195, 274; education and, 2, 51–52, 139, 145, 185, 191–99, 204–5, 217, 225, 234, 261, 270–71, 274–75; growth and, 51, 92; knowledge economies and, 139, 145, 185, 188, 191–92, 195–97, 200, 204–6, 217, 225, 246; populism and, 217, 225, 246; reputation and, 191; segregation and, 205–6; skilled labor and, 2, 28, 48, 139, 145, 185, 191–92, 195, 197, 225, 258, 261, 267–68, 271 Social Security, 24, 42, 50, 118, 174, 184 socio-optimists, 260, 266, 275 socio-pessimists, 260, 266 Sokoloff, Kenneth L., 80, 84, 89 Soskice, David, 124, 135, 211 South Korea: capitalism and, 4, 26, 148; democracy and, 78; education and, 26, 28, 166, 231–32, 241, 284n4; Gini coefficients and, 36; knowledge economies and, 147–48, 150, 154, 156, 166, 232, 233, 236, 239, 241, 242, 284n4; middle-income trap and, 26; military and, 28; patents and, 27; populism and, 232, 233, 236, 239, 241, 242; skilled labor and, 28 Soviet Union, 139, 142, 156, 186, 241, 285n7 Spain: Gini coefficients and, 36; knowledge economies and, 154, 166, 201, 221, 233, 236, 242, 248; patents and, 27; taxes and, 17 Sparkassen, 176–77 specialization: advanced capitalist democracies (ACD) and, 14–17; Asia and, 267; capitalism and, 2, 6, 8, 17, 40, 139, 145, 147, 161, 192, 258, 267, 270–71, 276–77; cospecificity and, 14–17; cross-country comparison and, 39; democracy and, 67, 258, 267, 270–71, 276–77; economic geography and, 8, 14–17, 39, 144, 146–47, 192, 276–77; education and, 14, 191, 271; Fordism and, 108; globalization and, 3, 8, 17, 40, 51, 198, 258; heterogenous institutions and, 6; innovation and, 8, 14, 198, 267, 271; knowledge economies and, 2–3, 139, 144–47, 161, 190–93, 198, 200, 281n21; location cospecificity and, 14–17; multinational enterprises (MNEs) and, 192–93; patterns of, 192–93; production and, 51, 108, 161, 258, 267–71; skill clusters and, 190–91; as strengthening state, 50–51 Ständestaat group, 59–60, 65–66, 70, 90–91, 93 Standing, Guy, 142 Stasavage, David, 221 Stegmaier, Mary, 164, 167, 285n8 Steinmo, Sven, 16 Stephens, Evelyne Huber, 56, 229 Stephens, John, 56, 229, 280n6 Streeck, Wolfgang, 1, 16, 22, 30, 137, 163, 206, 281n17, 282n22 strikes, 73, 75, 108, 116 suffrage, 72–74, 76, 80, 87–89 Susskind, Daniel, 260 Susskind, Richard, 260 Swank, Duane, 16, 39, 101 Sweden: capitalism and, 19, 39, 49, 148; democracy and, 56, 57, 61, 62, 67, 71–76, 78; Fordism and, 106, 107, 117, 120, 129; Gini coefficients and, 25, 36; knowledge economies and, 147–48, 150, 153–54, 166, 173, 221, 233, 236, 242, 245; median income and, 25; populism and, 221, 233, 236, 242, 245; Social Democratic Party and, 19; taxes and, 17 Swenson, Peter, 108 Switzerland: democracy and, 56, 57, 61, 62–63, 282n3; Gini coefficient of, 36; knowledge economies and, 147–48, 150, 154, 166, 221, 233, 236, 242, 245; populism and, 221, 233, 236, 242, 245; protocorporatist countries and, 62–63; taxes and, 280n13; unions and, 106 symbiotic forces: democracy and, 5–9, 14, 20, 32, 53–54, 102, 130–31, 159, 165, 206, 249–53, 258, 259, 270, 272; Fordism and, 102, 130–31; knowledge economies and, 159, 165, 206, 249–53; populism and, 249–53 tacit knowledge, 2, 39, 145, 263 Taiwan, 4, 26–28, 78, 156 tariffs, 89, 114, 285n5 taxes: capitalism and, 16–17, 24, 34–35, 40, 51, 73, 167, 206, 261, 280n12; democracy and, 73, 261, 267–68, 271; Fordism and, 110–13, 124; Gini coefficients and, 22, 141; government concessions and, 18; Internal Revenue Service and, 42; knowledge economies and, 141, 157–58, 165, 167, 172, 206, 221–22, 225, 231, 281n21; majoritarianism and, 24, 44, 113, 124; middle class and, 21, 42, 124, 158, 222, 225; mobility and, 221; populism and, 221–22, 225, 231; redistribution and, 35, 40, 51, 124, 158, 221–22, 225; Republican reform and, 282n24; rich and, 22, 24, 261, 280n13; shelters and, 280n13; transfer systems and, 21–22, 112, 158; United Kingdom and, 17, 141, 206; United States and, 16–17, 24, 42, 141; upper class and, 42; value added, 34, 206; welfare and, 16–17, 21, 40, 42, 167 technology: artificial intelligence (AI) and, 260–72; assembly lines and, 104, 108; biotechnology and, 141, 175, 184; change and, 5, 13, 40–45, 50, 124, 138–41, 155, 162, 192, 199, 222, 232, 246, 249, 259, 262; codifiable, 7, 12, 14–15, 238; colocation and, 261, 266–72; cospecificity and, 7, 12, 14, 20, 37, 48, 50, 103, 159, 261–66; debates over future, 259–72; democracy and, 70, 92, 259–63, 267–72, 277; Fordism and, 5, 7, 14–15, 50, 102–6, 109, 117–19, 124, 127–28, 131, 140–43, 154, 192, 194, 222, 277; growth and, 3, 5, 13, 38, 162, 194, 226, 261; ICT and, 3 (see also Information and Communication Technology (ICT)); income distribution and, 21, 40; industrial revolution and, 5, 12, 58, 293, 295; investment in, 3, 20, 30, 37–38, 50, 109, 142, 147, 156, 175, 272; knowledge economies and, 138–44, 147, 154–62, 175–76, 184–86, 192–94, 198–99, 214, 222, 226, 232, 234, 238, 246, 249, 284n1, 284n3, 285n6; Luddites and, 226; manual jobs and, 264–65; microprocessors and, 14, 140, 284n1; middle class and, 3, 21, 29–30, 41, 117, 139, 222, 226, 249; multinational companies (MNCs) and, 48; nanotechnology, 141, 184; outsourcing and, 118, 193–94, 222; overlapping generation (OLG) logic and, 7; patents and, 7, 12–15, 26, 27, 145, 201, 281n15, 285n6; populism and, 222, 226, 232, 234, 238, 246, 249; robots and, 18, 141, 143, 184, 193, 260–66, 273; self-driving vehicles and, 265; semiskilled labor and, 41, 43, 65, 102–5, 118–19, 127, 238, 261; shocks and, 6, 30, 136, 138, 140, 143, 159, 185, 194; skilled labor and, 3, 7, 10–14, 20, 30–31, 37, 41, 43, 48, 50, 70, 96, 102–5, 118–19, 127–28, 138–40, 144, 147, 157, 175–76, 185–86, 192–94, 198–99, 222, 232, 238, 261, 268, 277; smart cities and, 194–95; trade and, 3, 7, 31, 50, 128, 131, 142, 284n3; transfer and, 18, 31, 38, 48, 128, 131; vocational training and, 31, 44, 68, 82, 89, 92, 104, 109, 113, 127–28, 131, 174, 176, 179, 228–30, 233, 242–43, 251–52, 257; voters and, 6, 13, 20, 159, 234, 260, 272 techno-optimists, 260, 269–70, 275, 277 techno-pessimists, 260–61 Teece, David J., 7, 12 Thatcher, Margaret, 33, 149, 163, 169–71, 182, 209 Thelen, Kathleen, 62–64, 219 Third Republic, 57, 81, 86–87 Tiebout, Charles M., 252 Tories, 87 trade: barriers to, 50, 114, 154, 285n5; competition and, 26, 31, 128, 131, 153–55, 218, 285n5, 285n9; democracy and, 258, 267; FDI and, 154, 163, 284n3, 285n5, 285n9; Fordism and, 114, 128, 131; free, 17, 155; knowledge economies and, 142, 145, 153–55, 163, 172–73, 180, 211–13, 218, 250; liberalism and, 51, 62, 142, 155, 163, 173, 213, 250, 284n3; NAFTA and, 155; open, 27, 154; populism and, 218, 250; protectionism and, 28, 41, 169; technology and, 3, 7, 31, 50, 128, 131, 142, 284n3 Trans-Pacific Partnership Agreement (TPP), 155–56 transport systems, 201–3 Trump, Donald, 130, 156, 211, 215, 218–20, 237, 243–45, 248, 276 Über, 265 undeserving poor, 43, 142, 160, 216, 222, 227 unemployment: automatic disbursements and, 133, 284n2; capitalism and, 51, 117, 172, 282n22; countercyclical policies and, 16; democracy and, 74–77, 92, 96; Fordism and, 105, 107, 110, 117, 120–21, 124–27, 133, 135, 284n2; knowledge economies and, 170–72, 174, 178, 180, 207, 248–49, 255–56, 285n8; social protection and, 51 unions: centralization and, 49, 53, 58, 63, 67, 69–70, 73, 96, 99, 101, 105, 107–10, 113, 116, 119, 122–23, 152, 156, 172, 174, 283n8; centralization/decentralization issues and, 49–50, 53, 58, 63, 67–70, 73, 96, 99, 101, 105–10, 113, 116, 119, 122–23, 152, 172, 174, 186, 283n8; competition and, 6, 33, 66, 68, 80, 96, 119, 152, 169–72, 177, 181, 186; craft, 61, 63, 67–71, 101, 172; democracy and, 53, 58–80, 90–92, 95–101, 274, 282n3, 283n8; exclusion of, 67, 70, 98; Fordism and, 105–16, 119–23, 127, 284n3; hostile takeovers and, 33; institutional frameworks and, 32–33; knowledge economies and, 152, 169–83, 212, 228, 251; laborist unionism and, 62; low-skilled labor and, 19, 47, 50, 66, 70–71, 96, 98–99, 119, 127, 181; polarized unionism and, 62; populism and, 228, 251; power and, 32, 66–67, 69, 73–76, 99, 105, 108, 112–13, 119, 169, 172, 186; predatory, 6; Rehn-Meidner model and, 19; segmented, 62, 105, 113; semiskilled labor and, 61, 64–65, 68–69, 105, 119–20, 123, 172–73; September Compromise and, 66; skilled labor and, 6, 19, 33, 47, 50, 53, 58, 60–71, 96–101, 105, 110, 119–20, 123, 127, 172–73, 176, 181, 186, 251; social democratic parties and, 6, 19, 61–63, 67–68, 72, 74, 76, 114, 181, 282n3; solidaristic, 62, 105, 172; strikes and, 73, 75, 108, 116; trade, 62–64, 170 United Kingdom: Blair and, 33, 171, 209; Brexit and, 130, 245, 248, 250, 276; British disease and, 172; British North American Act and, 87–88; Callaghan and, 169, 171; capitalism and, 10, 13, 19, 32, 38, 148, 152, 172, 206, 209; centralization and, 49; Confederation of British Industry (CBI) and, 169–70; Conservative Party and, 32, 81, 85, 88, 169, 218–19; democracy and, 38, 54–65, 73, 80–90, 277, 283n9; Disraeli and, 81, 85, 96; education and, 38, 130, 166, 177, 231–32, 277; enfranchisement and, 84–90; Fordism and, 105–8, 120, 123, 130; Forster Elementary Education Act and, 86; Gini coefficents for, 25, 36; Healey and, 169; health and, 204–5; Hyde Park Riots and, 85; inequality and, 36; knowledge economies and, 142, 147–48, 150, 152, 154, 161–63, 166, 169–77, 180–81, 194, 200–1, 204, 206, 209, 218, 232, 233, 236, 242, 245, 250; labor co-operation and, 152; laborist unionism and, 62; Labour Party and, 68, 169, 171; Liberals and, 32; Local Government Act and, 86; median income and, 25; modernization and, 19; Municipal Corporations Act and, 86; patents and, 27; populism and, 13, 218, 232, 233, 236, 242, 245, 250; postwar, 11; Prior and, 169–70; Public Health Acts and, 86; Reform Acts and, 56, 80–81, 85–86; Reform Party and, 88; segregation and, 200–3; settler colonies and, 84–90; taxes and, 17, 141, 206; Thatcher and, 33, 149, 163, 169–71, 182, 209; Tories and, 87; Victorian reformers and, 82; Whigs and, 80 United States: capitalism and, 13, 16–17, 24–25, 38, 47, 148, 152, 186, 209, 275, 277; Civil War and, 57; Clayton Act and, 153; Cold War and, 78, 111; decentralization and, 49; democracy and, 13, 24, 38, 55–57, 59, 62–64, 70, 83, 88, 96, 107, 147–48, 186, 215, 220, 275, 277; education and, 24, 38, 55, 70, 83, 109, 127, 130, 166, 177, 195, 223, 230–32, 241, 275; Fordism and, 105–9, 117–20, 123, 127, 130; inequality and, 24, 36, 42, 107, 117, 118, 123, 220, 282n22; knowledge economies and, 141–42, 147–56, 162, 166, 169, 171, 177, 186, 194–95, 198, 202, 209, 215, 218–23, 230, 232, 236, 241, 244, 277; labor market and, 56 (see also labor market); NAFTA and, 155; populism and, 13, 130, 171, 195, 215, 218–23, 230, 232, 236, 241, 244, 275; Sherman Act and, 153; taxes and, 16–17, 24, 42, 141; Trans-Pacific Partnership Agreement (TPP) and, 155–56 unskilled workers: democracy and, 62–63, 67–71, 96–97, 101; Fordism and, 104–5, 118; knowledge economies and, 193, 246, 255; populism and, 246, 255–56 upper class: capitalism and, 4, 6; democracy and, 35; education and, 43; as gaming the system, 222; global distribution and, 27–29; Great Gatsby Curve (GGC) and, 220, 221, 227–28, 247, 259, 275–76; inequality and, 41, 158, 261; political influence of, 24, 41–43, 253; populism and, 222, 227, 237, 253; skilled labor and, 43–44, 125; taxes and, 22, 42, 261, 280n13; voters and, 2 upskilling, 102, 123, 129, 174–75, 178, 228, 232, 250–51 urbanization, 37, 92; big-city agglomerations and, 194–200; effects of, 83–84; feeder towns and, 108–9, 224; knowledge economies and, 141, 194–95, 201–3, 224–27, 239, 241; rebirth of cities and, 224–27; segregation and, 200–6 (see also segregation); smart cities and, 194–95; transport systems and, 201–3 US Patent and Trademark Office, 26–27 value-added sectors, 206–9 Van Kersbergen, Kees, 44, 92, 95, 124 Verily Life Sciences, 262 Vernon, Raymond, 18 VET system, 176, 179–80 Vliet, Olaf van, 133 Vogel, Steven, 11 Von Hagen, Jürgen, 121, 151 Von Papen, Franz, 77 voters: advanced capitalism and, 2, 6, 11–14, 19–22, 30–32, 38, 46–47, 112, 158–59, 167, 215, 247, 273; aspirational, 6, 12–13, 20–21, 32, 167, 214, 219, 272; decisive, 2–3, 6, 11–14, 19–23, 32, 38, 43, 158–59; democracy and, 75, 81, 90, 96–100, 111–13, 125, 129–30, 133, 260, 272–73; economic, 164; education and, 12–13, 21, 38, 45, 90, 158, 164, 167–68, 219, 234, 247, 273; electoral politics and, 21–22, 46, 100, 111, 158, 183, 217, 272; growth and, 2, 13, 23, 32, 111, 113, 164, 168, 247; knowledge economies and, 24, 138, 140, 158–59, 163–64, 167–68, 183, 213–19, 234–36, 245, 247; median, 3, 21, 23, 44, 96–97, 100, 125, 168, 213; Meltzer-Richard model and, 3; middle class, 2–3, 20–22, 44, 90, 96–100, 125, 140, 158, 168, 273; mobilizing, 75; neoliberalism and, 2; politics of the future and, 272–73; populism and, 217–19, 234–36, 244–47, 250, 256; prospective, 164; PR systems and, 19, 34, 100, 217; redistribution and, 3, 19–21, 32, 43, 90, 98, 100, 125, 140, 158, 273; retrospective, 164; suffrage and, 72–74, 76, 80, 87–89; technology and, 6, 13, 20, 159, 234, 260, 272; upper class and, 2; welfare and, 3, 21–22, 43, 45–46, 111, 167, 214, 234, 273 wages: bargaining and, 49–50, 61, 105–10, 119–21, 127, 151, 172, 176; coordination and, 49–50, 106–7, 120, 123, 172, 229; cospecificity and, 49–50; democracy and, 266, 268, 273; Fordism and, 104–24, 127, 284n2; Great Gatsby Curve (GGC) and, 220, 221, 227–28, 247, 259, 275–76; knowledge economies and, 151, 160, 172–76, 181, 196, 211–12, 219, 222–23, 227, 229; monopoly, 6; populism and, 219, 222–23, 227, 229; restraint and, 18, 110, 113, 120–21, 151, 176, 211–12; skilled labor and, 6, 18, 33, 41, 50, 61, 64, 67, 104–5, 110, 115, 118–24, 127, 172–76, 181, 212, 222–23, 229, 266 Wajcman, Judy, 260 Wallerstein, Michael, 105 Washington Consensus, 38 Waymo, 265 Weimar Republic, 75–77 welfare: Bismarckian, 176; capitalism and, 8, 16–19, 31, 39–40, 46, 122, 125, 128, 131, 137, 167, 234, 261, 279n5, 282n22; cash transfers and, 21; competition and, 31, 40, 52, 122, 128, 131, 223, 285n6; cospecificity and, 49–50; democracy and, 94, 96, 261, 273; education and, 31, 42, 45, 52, 94, 96, 116, 128, 131, 146, 167, 223, 234, 261, 287n1; Fordism and, 110–11, 115–28, 131; free riders and, 127; Golden Age of, 127; inequality and, 3, 42, 125, 223, 282n22; Keynesianism and, 115; knowledge economies and, 137, 146, 167, 176, 214, 223, 234, 249, 285n6, 285n8, 287n1; labor market and, 31, 46, 96, 118, 120, 122–23, 125, 128, 176, 223, 279n5; populism and, 45, 223, 234, 249, 287n1; power resources theory and, 280n6; public services and, 21; redistribution and, 3, 8, 18–21, 31, 39–40, 43, 115, 123–24, 128, 131, 137, 261, 273; skilled labor and, 45; social insurance and, 21; taxes and, 16–17, 21, 40, 42, 167; trade protectionism and, 51; undeserving poor and, 43; voters and, 3, 21–22, 43, 45–46, 111, 167, 214, 234, 273; wage coordination and, 49–50 Westminster systems, 19 Whigs, 80 Winters, J.

The Data Detective: Ten Easy Rules to Make Sense of Statistics by Tim Harford

Abraham Wald, access to a mobile phone, Ada Lovelace, affirmative action, algorithmic bias, Automated Insights, banking crisis, basic income, behavioural economics, Black Lives Matter, Black Swan, Bretton Woods, British Empire, business cycle, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, Charles Babbage, clean water, collapse of Lehman Brothers, contact tracing, coronavirus, correlation does not imply causation, COVID-19, cuban missile crisis, Daniel Kahneman / Amos Tversky, data science, David Attenborough, Diane Coyle, disinformation, Donald Trump, Estimating the Reproducibility of Psychological Science, experimental subject, fake news, financial innovation, Florence Nightingale: pie chart, Gini coefficient, Great Leap Forward, Hans Rosling, high-speed rail, income inequality, Isaac Newton, Jeremy Corbyn, job automation, Kickstarter, life extension, meta-analysis, microcredit, Milgram experiment, moral panic, Netflix Prize, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, opioid epidemic / opioid crisis, Paul Samuelson, Phillips curve, publication bias, publish or perish, random walk, randomized controlled trial, recommendation engine, replication crisis, Richard Feynman, Richard Thaler, rolodex, Ronald Reagan, selection bias, sentiment analysis, Silicon Valley, sorting algorithm, sparse data, statistical model, stem cell, Stephen Hawking, Steve Bannon, Steven Pinker, survivorship bias, systematic bias, TED Talk, universal basic income, W. E. B. Du Bois, When a measure becomes a target

But moving a dollar from a richer person to a poorer person, no matter how rich or poor either of them might be, will reduce the Gini coefficient. One big problem with the Gini coefficient, however, is getting an intuitive feel for what it actually means. It’s easy enough to picture a country with a Gini coefficient of zero—there, everyone gets exactly the same income. Likewise, we can readily imagine a country in which the Gini coefficient is 100 percent—there, the despotic president has cornered all the income and everyone else gets precisely nothing. But what would it be like to live in a country where the Gini coefficient of income is, say, 34 percent? As it happens, if you live in the UK, you can answer that question.7 But even a specialist in income distribution would probably understand a Gini coefficient of 34 percent only in reference to the Gini coefficients of other countries.

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We can get useful context from other kinds of comparison, too. Let’s return to our case study of income inequality from the previous chapter, where we learned there are many plausible ways to measure it—such as the 50/10 ratio, or the income share of the top 1 percent. What if we could produce some sort of composite measure that summarizes the whole of the income distribution? These composite measures exist, and we’ve already mentioned the most famous—the Gini coefficient, named after the early-twentieth-century Italian statistician Corrado Gini. Like any other measure of inequality, the Gini coefficient doesn’t tell us everything. On a global scale, the coefficient has been falling—that is, incomes are becoming more equal.

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It’s unclear whether counting state pensions as assets would increase measured inequality (since many of the poorest people lack them) or reduce measured inequality (since a state pension represents a substantial asset for the poorer people in richer countries). I’m guessing things would look less unequal if state pensions were included, but it is just a guess. I might be quite wrong. Around the world, a third of older people have no pension of any kind. *Another popular measure of inequality—one we’ll encounter in the next chapter—is the Gini coefficient. This measure was telling the same story of falling inequality in the wake of the crisis.

Rethinking the Economics of Land and Housing by Josh Ryan-Collins, Toby Lloyd, Laurie Macfarlane

agricultural Revolution, asset-backed security, balance sheet recession, bank run, banking crisis, barriers to entry, basic income, book value, Bretton Woods, business cycle, Capital in the Twenty-First Century by Thomas Piketty, collective bargaining, Corn Laws, correlation does not imply causation, creative destruction, credit crunch, debt deflation, deindustrialization, falling living standards, financial deregulation, financial innovation, Financial Instability Hypothesis, financial intermediation, foreign exchange controls, full employment, garden city movement, George Akerlof, ghettoisation, Gini coefficient, Hernando de Soto, housing crisis, Hyman Minsky, income inequality, information asymmetry, knowledge worker, labour market flexibility, labour mobility, land bank, land reform, land tenure, land value tax, Landlord’s Game, low interest rates, low skilled workers, market bubble, market clearing, Martin Wolf, means of production, Minsky moment, Money creation, money market fund, mortgage debt, negative equity, Network effects, new economy, New Urbanism, Northern Rock, offshore financial centre, Pareto efficiency, place-making, Post-Keynesian economics, price stability, profit maximization, quantitative easing, rent control, rent-seeking, Richard Florida, Right to Buy, rising living standards, risk tolerance, Robert Solow, Second Machine Age, secular stagnation, shareholder value, subprime mortgage crisis, the built environment, The Great Moderation, The Market for Lemons, The Spirit Level, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, Thomas Malthus, transaction costs, universal basic income, urban planning, urban sprawl, working poor, working-age population

Table 6.2 Net property wealth between 1995 and 2005, selected percentiles (Great Britain) Source: Bastagli and Hills (2012) Note: Figures in 2005 prices. In all of these studies housing wealth inequality as measured by the Gini coefficient is found to have declined slightly over the relevant time periods, largely driven by the increase in the proportion of housing assets held by households in the middle part of the distribution.3 However, measuring the effect of these trends on inequality using conventional measures of inequality such as the Gini coefficient is problematic. As noted previously, the Gini coefficient indicates the spread of the wealth distribution or deviation from the mean, and is therefore very sensitive to changes in the middle of the distribution and less sensitive to changes at the very top and the very bottom of the distribution.

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Another common way to measure income inequality is the Gini coefficient. The Gini coefficient is a measure of statistical dispersion intended to represent the income distribution of a nation’s residents. It is represented as a number between 0 and 1, where 0 corresponds with perfect equality (where everyone has the same income) and 1 corresponds with perfect inequality (where one person has all the income and everyone else has zero income). On this measure the UK is currently the fifth most unequal country in the OECD (2016). However, because the Gini coefficient indicates the spread of the income distribution or deviation from the mean, it is particularly sensitive to income changes in the middle of the income distribution and less sensitive to changes at the very top and the very bottom of the income distribution.

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However, in the late 1980s the cost of renting increased sharply relative to incomes, whereas the cost of owning with a mortgage remained broadly stable (Belfield et al., 2014). As a result, the cost of housing has increased disproportionately for those in rented accommodation, which tend to be households on lower incomes.5 This has had the effect of exacerbating inequalities in ultimate spending power and living standards. Figure 6.8 shows the Gini coefficient for income inequality both before and after housing costs. It shows that income inequality was largely unaffected by housing costs during the 1960s and 1970s, but from 1979 onwards there has been a growing divergence between the two measures. This indicates that over the past thirty years housing costs have become a significant contributor towards widening gaps in ultimate spending power and, therefore, living standards.

Good Times, Bad Times: The Welfare Myth of Them and Us by John Hills

Brexit referendum, Capital in the Twenty-First Century by Thomas Piketty, credit crunch, Donald Trump, falling living standards, full employment, Gini coefficient, income inequality, income per capita, longitudinal study, meritocracy, mortgage debt, pension reform, plutocrats, precariat, quantitative easing, Right to Buy, unpaid internship, very high income, We are the 99%, working-age population, World Values Survey

2.4 ‘Should government spend more money on welfare benefits for the poor, even if it leads to higher taxes?’ 2.5 Pen’s parade of incomes in the UK, 2012–13 2.6 Inequality in disposable incomes in industrialised countries, 2013 (Gini coefficients, %) 2.7 Distribution of household incomes, 2013–14 2.8 Inequality of market incomes in industrialised countries, 2013 (Gini coefficients, %) 2.9 Inequality before and after redistribution in the UK and Sweden, 2013 (Gini coefficients, %) 2.10 Taxes and benefits by household income group, 2013–14 2.11 Preferences for taxation and cash benefits, 2008 (%) 2.12 The poor cost more?

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Only Ireland, Greece and Portugal had more inequality before the state intervened. Figure 2.8: Inequality of market incomes in industrialised countries, 2013 (Gini coefficients, %) The difference between inequality in market incomes and in disposable incomes gives one measure of how much redistribution the direct tax and benefit systems achieve. In these terms the UK does quite a lot. The difference in inequality between the indexes shown in Figures 2.8 and 2.6 was greater in the UK than the average for the 35 countries shown, with only 15 of them doing more.34 Taxes and benefits narrowed income inequality in the UK more than in archetypal egalitarian countries such as Sweden and Norway.

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As Figure 2.9 comparing the UK and Sweden shows, inequality ends up much higher in the UK than in Sweden, because it starts so much higher, despite the UK’s somewhat greater redistributive effort. Figure 2.9: Inequality before and after redistribution in the UK and Sweden, 2013 (Gini coefficients, %) Our problem as a country is that, if we want to achieve a relatively equal result, the inequality in market incomes means that so much redistribution is needed. Despite our greater than average redistributive effort, we still end up as one of the most unequal countries in the rich world because there is so much inequality in the incomes people receive from the market compared with elsewhere.

The Inequality Puzzle: European and US Leaders Discuss Rising Income Inequality by Roland Berger, David Grusky, Tobias Raffel, Geoffrey Samuels, Chris Wimer

"World Economic Forum" Davos, Bear Stearns, Branko Milanovic, business cycle, Caribbean Basin Initiative, Celtic Tiger, collective bargaining, corporate governance, corporate social responsibility, double entry bookkeeping, equal pay for equal work, fear of failure, financial innovation, full employment, Gini coefficient, hiring and firing, illegal immigration, income inequality, invisible hand, Long Term Capital Management, long term incentive plan, microcredit, military-industrial complex, Money creation, offshore financial centre, principal–agent problem, profit maximization, proprietary trading, rent-seeking, shareholder value, Silicon Valley, Silicon Valley startup, time value of money, very high income

Wimer We begin, then, by examining the overall level of income inequality within 30 OECD countries. As shown in Figure 1, there’s substantial variability across these countries in the extent of income inequality, with of course the Nordic countries, especially Denmark and Sweden, registering the lowest levels of inequality. The middling ranks include such countries as France, Germany, Austria, Canada, and Japan, while the most extreme inequality appears in such countries as Italy, the United States, Turkey, and Mexico. The Gini coefficient, a commonly used indicator of inequality, has been applied in Figure 1,3 but much the same conclusions would be reached with other measures. 0.50 0.45 0.40 0.35 0.30 0.20 Denmark Sweden Luxembourg Austria Czech Republic Slovakia Finland Belgium Netherlands Switzerland Norway Iceland France Hungary Germany Australia OECD-30 Korea Canada Spain Japan Greece Ireland New Zeeland Great Britain Italy Poland USA Portugal Turkey Mexico 0.25 Figure 1: Gini coefficients of income inequality in OECD countries, mid-2000s (Source: OECD income distribution questionnaire) What about trends in income inequality?

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7 point since the 1980s, although there are of course important differences across countries in the timing and extent of such change.5 Mid-1980s to Mid-1990s Mid-1990s to Mid-2000s Cumulative change Mid-1980s to Mid-2000s -0.08 -0.04 0.00 0.04 0.08 -0.08 -0.04 0.00 0.04 0.08 -0.08 -0.04 0.00 0.04 0.08 Australia Austria Belgium Canada Czech Republic Denmark Finland France Germany Greece Hungary Ireland Italy Japan Luxembourg Mexico Netherlands New Zeeland Norway Portugal Spain Sweden Turkey Great Britain USA OECD-24 OECD-22 Figure 2: Trends in income inequality: Point changes in the Gini coefficient over different time periods (Source: Computations from OECD income distribution questionnaire) These overall inequality trends cannot tell us whether certain sectors of the income distribution account for most of the changes when inequality rises or falls. We can better understand why income inequality has risen in cer- 5 Brandolini, A., and T.M. Smeeding, “Patterns of Economic Inequality in Western Democracies: Some Facts on Levels and Trends,” Political Science and Politics (January 2006), pp. 21-26.

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The Gini coefficient, a commonly used indicator of inequality, has been applied in Figure 1,3 but much the same conclusions would be reached with other measures. 0.50 0.45 0.40 0.35 0.30 0.20 Denmark Sweden Luxembourg Austria Czech Republic Slovakia Finland Belgium Netherlands Switzerland Norway Iceland France Hungary Germany Australia OECD-30 Korea Canada Spain Japan Greece Ireland New Zeeland Great Britain Italy Poland USA Portugal Turkey Mexico 0.25 Figure 1: Gini coefficients of income inequality in OECD countries, mid-2000s (Source: OECD income distribution questionnaire) What about trends in income inequality? In the same report, the OECD observed that income inequality rose at a “moderate but significant” pace, with the data suggesting an average increase across countries of approximately two Gini points in the last 20 years (see Figure 2). Likewise, data from the Luxembourg Income Study,4 perhaps the best comparative resource on income and inequality in rich countries, show that most countries have experienced at least a modest rise in income inequality at some 3 The Gini coefficient for income measures the dispersion or spread of income across a society.

Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence by Jerry Kaplan

Affordable Care Act / Obamacare, Amazon Web Services, asset allocation, autonomous vehicles, bank run, bitcoin, Bob Noyce, Brian Krebs, business cycle, buy low sell high, Capital in the Twenty-First Century by Thomas Piketty, combinatorial explosion, computer vision, Computing Machinery and Intelligence, corporate governance, crowdsourcing, driverless car, drop ship, Easter island, en.wikipedia.org, Erik Brynjolfsson, estate planning, Fairchild Semiconductor, Flash crash, Gini coefficient, Goldman Sachs: Vampire Squid, haute couture, hiring and firing, income inequality, index card, industrial robot, information asymmetry, invention of agriculture, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, Kiva Systems, Larry Ellison, Loebner Prize, Mark Zuckerberg, mortgage debt, natural language processing, Nick Bostrom, Own Your Own Home, pattern recognition, Satoshi Nakamoto, school choice, Schrödinger's Cat, Second Machine Age, self-driving car, sentiment analysis, short squeeze, Silicon Valley, Silicon Valley startup, Skype, software as a service, The Chicago School, The Future of Employment, Turing test, Vitalik Buterin, Watson beat the top human players on Jeopardy!, winner-take-all economy, women in the workforce, working poor, Works Progress Administration

Census Bureau uses it to measure income inequality.41 In 1970, the Gini coefficient for income stood at .394. By 2011, it had climbed to .477. That doesn’t have an intuitive ring to it, but it’s pretty bad. The same objective measure can be applied to the beneficial ownership of any asset. Suppose you and three friends decide to go in together on a rental property. If you each have one-quarter ownership, that’s a Gini coefficient of 0. On the other hand, suppose you put up all the money but decide to cut in your friends for 1 percent each because you’re a nice person. That’s a Gini coefficient close to 1. But suppose that the arrangement doesn’t work out because your friends act like they own the place, when for all practical purposes you do.

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Institutional Shareholder Services (ISS) issues a widely used measure of corporate governance covering board structure, shareholder rights, compensation practices, and audit quality. What we need to lay the groundwork for addressing income inequality is a new government measure of just how broadly assets are owned. Luckily, we can take one off the shelf, dust it off, and polish it up a bit. In 1912, an Italian statistician named Corrado Gini published a paper titled “Variabilità e mutabilità” or, in English, “Variability and Mutability.”40 In it, he proposed a clever measure of dispersion which has come to be known as the Gini coefficient. Basically, you feed in a bunch of data, and the Gini coefficient will tell you just how “even” the series is, expressed as 0 for smooth and equal, and 1 for incredibly skewed.

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But suppose that the arrangement doesn’t work out because your friends act like they own the place, when for all practical purposes you do. So you buy out their interests. The Gini coefficient goes back to 0, because all the owners (that is, just you) have equal shares. As you can see, just applying the Gini coefficient to an asset doesn’t get at what we want to measure. Instead, we have to make a small adjustment. First we need to define some population, say, adult U.S. citizens. Then assume for calculation purposes that people in the group who don’t own any of the assets have a 0 percent interest. Now the Gini coefficient reflects how widely owned the asset is across the population of interest.

The Great Divergence: America's Growing Inequality Crisis and What We Can Do About It by Timothy Noah

air traffic controllers' union, Alan Greenspan, assortative mating, autonomous vehicles, Bear Stearns, blue-collar work, Bonfire of the Vanities, Branko Milanovic, business cycle, call centre, carbon tax, collective bargaining, compensation consultant, computer age, corporate governance, Credit Default Swap, David Ricardo: comparative advantage, Deng Xiaoping, easy for humans, difficult for computers, Erik Brynjolfsson, Everybody Ought to Be Rich, feminist movement, Ford Model T, Frank Levy and Richard Murnane: The New Division of Labor, Gini coefficient, government statistician, Gunnar Myrdal, income inequality, independent contractor, industrial robot, invisible hand, It's morning again in America, job automation, Joseph Schumpeter, longitudinal study, low skilled workers, lump of labour, manufacturing employment, moral hazard, oil shock, pattern recognition, Paul Samuelson, performance metric, positional goods, post-industrial society, postindustrial economy, proprietary trading, purchasing power parity, refrigerator car, rent control, Richard Feynman, Ronald Reagan, shareholder value, Silicon Valley, Simon Kuznets, Stephen Hawking, Steve Jobs, subprime mortgage crisis, The Spirit Level, too big to fail, trickle-down economics, Tyler Cowen, Tyler Cowen: Great Stagnation, union organizing, upwardly mobile, very high income, Vilfredo Pareto, War on Poverty, We are the 99%, women in the workforce, Works Progress Administration, Yom Kippur War

The most common measure, the Gini coefficient, is named for an Italian statistician named Corrado Gini (1884–1965).3 It measures distribution—of income or anything else—on a scale that goes from 0 to 1. Let’s imagine, for instance, that we had fifty marbles to distribute among fifty children. Perfect equality of distribution would be if each child got one marble. The Gini coefficient would then be 0. Perfect inequality of distribution would be if one especially pushy child ended up with all fifty marbles. The Gini coefficient would then be 1.4 As of 2005, the United States’ Gini coefficient was 0.38, which on the income-equality scale ranked this country twenty-seventh of the thirty OECD nations for which data were available. The only countries with more unequal income distribution were Portugal (0.42), Turkey (0.43), and Mexico (0.47).

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We already know from census data that in 2010 income share for the bottom 40 percent fell and that the poverty rate climbed to its highest point in nearly two decades.7 In addition to having an unusually high level of income inequality, the United States has seen income inequality increase at a much faster rate than most other countries. Among the twenty-four OECD countries for which Gini-coefficient change can be measured from the mid-1980s to the mid-aughts, only Finland, Portugal, and New Zealand experienced a faster growth rate in income inequality. Of these, only Portugal ended up with a Gini rating worse than the United States’. Another important point of comparison is that some OECD countries saw income inequality decline during this period. France, Greece, Ireland, Spain, and Turkey all saw their Gini ratings go down (though the OECD report’s data for Ireland and Spain didn’t extend beyond 2000).

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A 2008 report by the Organisation for Economic Co-operation and Development, which represents thirty-four market-oriented democracies, concluded that since the mid-1980s, income inequality had increased in two thirds of the twenty-four OECD countries for which data were available, which included most of the world’s leading industrial democracies.2 But the level and growth rate of income inequality in the United States has been particularly extreme. There are various ways to measure income distribution, and by all of them the United States ranks at or near the bottom in terms of equality. The most common measure, the Gini coefficient, is named for an Italian statistician named Corrado Gini (1884–1965).3 It measures distribution—of income or anything else—on a scale that goes from 0 to 1.

The Price of Inequality: How Today's Divided Society Endangers Our Future by Joseph E. Stiglitz

affirmative action, Affordable Care Act / Obamacare, airline deregulation, Alan Greenspan, Andrei Shleifer, banking crisis, barriers to entry, Basel III, battle of ideas, Bear Stearns, behavioural economics, Berlin Wall, business cycle, capital controls, Carmen Reinhart, Cass Sunstein, central bank independence, collapse of Lehman Brothers, collective bargaining, colonial rule, corporate governance, Credit Default Swap, Daniel Kahneman / Amos Tversky, Dava Sobel, declining real wages, deskilling, electricity market, Exxon Valdez, Fall of the Berlin Wall, financial deregulation, financial innovation, Flash crash, framing effect, full employment, George Akerlof, Gini coefficient, Glass-Steagall Act, Great Leap Forward, income inequality, income per capita, indoor plumbing, inflation targeting, information asymmetry, invisible hand, jobless men, John Bogle, John Harrison: Longitude, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, Kenneth Arrow, Kenneth Rogoff, London Interbank Offered Rate, lone genius, low interest rates, low skilled workers, Marc Andreessen, Mark Zuckerberg, market bubble, market fundamentalism, mass incarceration, medical bankruptcy, microcredit, moral hazard, mortgage tax deduction, negative equity, obamacare, offshore financial centre, paper trading, Pareto efficiency, patent troll, Paul Samuelson, Paul Volcker talking about ATMs, payday loans, Phillips curve, price stability, profit maximization, profit motive, public intellectual, purchasing power parity, race to the bottom, rent-seeking, reserve currency, Richard Thaler, Robert Shiller, Robert Solow, Ronald Coase, Ronald Reagan, Savings and loan crisis, search costs, shareholder value, short selling, Silicon Valley, Simon Kuznets, spectrum auction, Steve Jobs, stock buybacks, subprime mortgage crisis, technology bubble, The Chicago School, The Fortune at the Bottom of the Pyramid, The Myth of the Rational Market, The Spirit Level, The Wealth of Nations by Adam Smith, too big to fail, trade liberalization, Tragedy of the Commons, transaction costs, trickle-down economics, ultimatum game, uranium enrichment, very high income, We are the 99%, wealth creators, women in the workforce, zero-sum game

Of course, what he meant was not that the taxes themselves led to higher growth but that the taxes financed public expenditures—investments in education, technology, and infrastructure—and the public expenditures were what had sustained the high growth—more than offsetting any adverse effects from the higher taxation. Gini coefficient One standard measure of inequality is the Gini coefficient. If income were shared in proportion to the population—the bottom 10 percent getting roughly 10 percent of the income, the bottom 20 percent getting 20 percent, and so forth—then the Gini coefficient would be zero. There would be no inequality. On the other hand, if all the income went to the top person, the Gini coefficient would be one, in some sense “perfect” inequality. More-equal societies have Gini coefficients of .3 or below. These include Sweden, Norway, and Germany.96 The most unequal societies have Gini coefficients of .5 or above.

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See Institute of Directors press release, “The Answer to High Executive Pay Lies with Shareholders and Boards, Says IoD,” October 28, 2011, available at http://press.iod.com/2011/10/28/the-answer-to-high-executive-pay-lies-with-shareholders-says-iod/ (accessed March 6, 2012). 92. OECD, “Divided We Stand.” Among OECD countries, Turkey and Mexico both have substantially greater inequality as measured by the Gini coefficient. See the discussion of this measure below. 93. These comparisons are based on Gini coefficient data provided by the United Nations International Human Development Indicators, but are also supported by other databases. The Gini coefficient is an imperfect measure of inequality, but is useful for general international comparisons such as this one. I discuss some of the difficulties of comparing Gini data in subsequent footnotes in this chapter. 94.

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These include Sweden, Norway, and Germany.96 The most unequal societies have Gini coefficients of .5 or above. These include some countries in Africa (notably South Africa with its history of grotesque racial inequality) and Latin America—long recognized for their divided (and often dysfunctional) societies and polities.97 America hasn’t made it yet into this “elite” company, but it’s well on the way. In 1980 our Gini coefficient was just touching .4; today it’s .47.98 According to UN data, we are slightly more unequal than Iran and Turkey,99 and much less equal than any country in the European Union.100 We end this international comparison by coming back to a theme we raised earlier: measures of income inequality don’t fully capture critical aspects of inequality.

The Glass Half-Empty: Debunking the Myth of Progress in the Twenty-First Century by Rodrigo Aguilera

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, activist fund / activist shareholder / activist investor, Alan Greenspan, Anthropocene, availability heuristic, barriers to entry, basic income, benefit corporation, Berlin Wall, Bernie Madoff, Bernie Sanders, bitcoin, Boris Johnson, Branko Milanovic, Bretton Woods, Brexit referendum, Capital in the Twenty-First Century by Thomas Piketty, capitalist realism, carbon footprint, Carmen Reinhart, centre right, clean water, cognitive bias, collapse of Lehman Brothers, Colonization of Mars, computer age, Corn Laws, corporate governance, corporate raider, creative destruction, cryptocurrency, cuban missile crisis, David Graeber, David Ricardo: comparative advantage, death from overwork, decarbonisation, deindustrialization, Deng Xiaoping, Doha Development Round, don't be evil, Donald Trump, Doomsday Clock, Dunning–Kruger effect, Elon Musk, European colonialism, fake news, Fall of the Berlin Wall, first-past-the-post, Francis Fukuyama: the end of history, fundamental attribution error, gig economy, Gini coefficient, Glass-Steagall Act, Great Leap Forward, green new deal, Hans Rosling, housing crisis, income inequality, income per capita, index fund, intangible asset, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Jean Tirole, Jeff Bezos, Jeremy Corbyn, Jevons paradox, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, joint-stock company, Joseph Schumpeter, karōshi / gwarosa / guolaosi, Kenneth Rogoff, Kickstarter, lake wobegon effect, land value tax, Landlord’s Game, late capitalism, liberal capitalism, long peace, loss aversion, low interest rates, Mark Zuckerberg, market fundamentalism, means of production, meta-analysis, military-industrial complex, Mont Pelerin Society, moral hazard, moral panic, neoliberal agenda, Network effects, North Sea oil, Northern Rock, offshore financial centre, opioid epidemic / opioid crisis, Overton Window, Pareto efficiency, passive investing, Peter Thiel, plutocrats, principal–agent problem, profit motive, public intellectual, purchasing power parity, race to the bottom, rent-seeking, risk tolerance, road to serfdom, Robert Shiller, Robert Solow, savings glut, Scientific racism, secular stagnation, Silicon Valley, Silicon Valley ideology, Slavoj Žižek, Social Justice Warrior, Social Responsibility of Business Is to Increase Its Profits, sovereign wealth fund, Stanislav Petrov, Steven Pinker, structural adjustment programs, surveillance capitalism, tail risk, tech bro, TED Talk, The Spirit Level, The Wealth of Nations by Adam Smith, too big to fail, trade liberalization, transatlantic slave trade, trolley problem, unbiased observer, universal basic income, Vilfredo Pareto, Washington Consensus, Winter of Discontent, Y2K, young professional, zero-sum game

According to the latest global income estimates from Branko Milanovic, the global Gini coefficient (a widely used measure of inequality that goes from 0 to 1, the former being perfectly equal and the latter perfectly unequal societies) came in at 0.63 in 2013 (Figure 6.12). This would put it around the levels of Haiti and South Africa, the only countries in the world with Gini coefficients over 0.60. And that’s the good news: the global Gini has been gradually declining since hitting a peak of 0.69 in 1988. This decline in global inequality is also a recent phenomenon. Historic estimates (with less robust data than the post-1988 figures) show that global inequality stood at 0.43 in 1820 when capitalism and industrialization were in their infancy.

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Despite the rapid growth of many developing economies in the post-war era, not only did global inequality continue to increase but the share of inequality caused by between-country (as opposed to within-country) differences also grew. Like poverty, global inequality only began to decline when two countries that together account for around one third of the global population began converging: China and India. In fact, the component of the Gini coefficient that is accounted for by within-country inequality has risen since 1988 and now accounts for around one-third of global inequality, compared to around one-fifth in 1988.31 Tellingly, both China and India have become considerably more unequal (depending on the source, China’s Gini is now around the same or even higher than that of the US32), which illustrates how country-level and global inequality dynamics can vary dramatically.

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Under this measurement, inequality today is worse than in 1988. Figure 6.12: A very unequal world Notes: The Gini coefficient (or index) is the most commonly used indicator for inequality and ranges from 0 (perfect equality; all people have equal income) to 1 (perfect inequality; one person receives all income). Historic data for 1820–1980 is provided by Bourguignon and Morrison (2002), with more recent data from Lakner and Milanovic (1988–2008) and Milanovic (2013). Decomposition of between- and within-country inequality in the L-M / M series is based on Thiel’s L, a different inequality indicator and thus, actual shares of the Gini coefficient may vary slightly.

Exploring Everyday Things with R and Ruby by Sau Sheong Chang

Alfred Russel Wallace, bioinformatics, business process, butterfly effect, cloud computing, Craig Reynolds: boids flock, data science, Debian, duck typing, Edward Lorenz: Chaos theory, Gini coefficient, income inequality, invisible hand, p-value, price stability, Ruby on Rails, Skype, statistical model, stem cell, Stephen Hawking, text mining, The Wealth of Nations by Adam Smith, We are the 99%, web application, wikimedia commons

Given that all roids are the same, our Utopia simulation simply shows that over time, the rich get richer and the poor get poorer (in this case, the poor die), and the gap of inequality widens. Isn’t this simply guessing? Let’s do a second analysis. Inequality is frequently measured using the Gini coefficient, so we’ll analyze the distribution of energy levels with the Gini coefficient and Lorenz curves (for more information, see the sidebar ). Gini Coefficient and Lorenz Curve The Gini coefficient is a measure of statistical dispersion developed by the Italian statistician and sociologist Corrado Gini and published in his 1912 paper “Variability and Mutability.” It is a measure of the inequality of a distribution, a value of 0 expressing perfect equality and a value of 1 expressing perfect inequality.

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It is a measure of the inequality of a distribution, a value of 0 expressing perfect equality and a value of 1 expressing perfect inequality. Although commonly used as a measure of inequality of income or wealth, the Gini coefficient has also been applied in many other fields, including ecology, health science, and chemistry. Associated with the Gini coefficient is the Lorenz curve, a graphical representation of the cumulative distribution function of a probability distribution. It was developed by Max O. Lorenz in 1905 to represent inequality of the wealth distribution. If there is perfect equality, the curve will be a line y = x. If there is perfect inequality, it will be a line y = 0 (i.e., a horizontal line).

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If there is perfect inequality, it will be a line y = 0 (i.e., a horizontal line). The Gini coefficient is the area between the line of perfect equality and the Lorenz curve, as a percentage of the area between the line of perfect equality and the line of perfect inequality. For this analysis, we’ll use the ineq library, which conveniently provides all the necessary functions for us to do this analysis. Let’s apply the same data points we used for graphing to some new R code that calculates the coefficience of inequality (Example 8-13). Example 8-13. Analyzing inequality over time library(ineq) data <- read.table("money.csv", header=F, sep=",") points = c(1,5,15,30,50,75,100,125,150,200,300,500) pdf("inequality.pdf") par(mfcol=c(4,3)) for (i in 1:12) { p <- Lc(as.vector(as.matrix(data[points[i],]))) ie <- ineq(data[points[i],]) plot(p, main=paste("t =", points[i], "/ Gini = ", round(ie, 3)), font.main=1) } dev.off() Although we use the same data as before (of course) and the same sample points, instead of generating histograms, this time we generate Lorenz curves and print out the Gini coefficient in the title of the chart as well (Figure 8-4).

Capitalism, Alone: The Future of the System That Rules the World by Branko Milanovic

affirmative action, Asian financial crisis, assortative mating, barriers to entry, basic income, Berlin Wall, bilateral investment treaty, Black Swan, Branko Milanovic, capital controls, Capital in the Twenty-First Century by Thomas Piketty, carried interest, colonial rule, corporate governance, creative destruction, crony capitalism, deindustrialization, dematerialisation, Deng Xiaoping, discovery of the americas, European colonialism, Fall of the Berlin Wall, financial deregulation, Francis Fukuyama: the end of history, full employment, ghettoisation, gig economy, Gini coefficient, global supply chain, global value chain, Great Leap Forward, high net worth, household responsibility system, income inequality, income per capita, invention of the wheel, invisible hand, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, labor-force participation, laissez-faire capitalism, land reform, liberal capitalism, low skilled workers, Lyft, means of production, new economy, offshore financial centre, Paul Samuelson, plutocrats, post-materialism, purchasing power parity, remote working, rent-seeking, ride hailing / ride sharing, Robert Solow, Silicon Valley, single-payer health, special economic zone, Tax Reform Act of 1986, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, Thorstein Veblen, uber lyft, universal basic income, Vilfredo Pareto, Washington Consensus, women in the workforce, working-age population, Xiaogang Anhui farmers

That superiority was most evident in colonial conquests, but it was also reflected in income gaps between the two parts of the world and thus in global income inequality among all citizens of the world, which we can estimate with relative precision from 1820 onward, as illustrated in Figure 1.1. In this graph, and throughout the book, inequality is measured using an index called the Gini coefficient, which ranges in value from 0 (no inequality) to 1 (maximum inequality). (The index is often expressed as a percentage, ranging from 0 to 100, where each percentage point is called a Gini point.) Before the Industrial Revolution in the West, global inequality was moderate, and nearly as much of it was due to differences among individuals living in the same nations as among the mean incomes of individuals in different nations.

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In short, it is a systemic feature of liberal meritocratic capitalism that capital income is extremely concentrated and is received mostly by the rich.24 Note too that inequality in labor income (before taxes) in these countries has increased during this period, from a Gini coefficient of under 0.5 to about 0.6. Looking at a snapshot of capital and labor income inequalities in rich countries from around 2013, we see that with the exception of Taiwan, all the countries shown have extremely concentrated income from capital, with Gini coefficients above 0.86 (Figure 2.2). Labor income Ginis are much lower, generally between 0.5 and 0.6, and even lower for Taiwan. I will return to the case of Taiwan later in the chapter. The curse of wealth To see how important the combination of rising capital income and heavy concentration of capital ownership is to total income inequality, one has to look at it dynamically.

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Around the turn of the twenty-first century, China was joined in that role by India, which, because of its large population, relative poverty, and high growth rate, now also contributes significantly to a decline in both global income inequality and global poverty. FIGURE 5.1. GDP per capita for China and India as a percentage of British GDP, and for Indonesia as a percentage of Dutch GDP, from the Industrial Revolution to today Data source: Calculated from the Maddison Project (2018); all GDP per capita data in 2011 PPPs (variable cgdppc, which is the real GDP variable used for cross-country comparisons at a given point in time). The importance of reduced global inequality does not reside in a decrease in a single number (the Gini coefficient of inequality), but rather in the convergence in real incomes across vast groups of people.

Think Complexity by Allen B. Downey

Benoit Mandelbrot, cellular automata, Conway's Game of Life, Craig Reynolds: boids flock, discrete time, en.wikipedia.org, Frank Gehry, Gini coefficient, Guggenheim Bilbao, Laplace demon, mandelbrot fractal, Occupy movement, Paul Erdős, peer-to-peer, Pierre-Simon Laplace, power law, seminal paper, sorting algorithm, stochastic process, strong AI, Thomas Kuhn: the structure of scientific revolutions, Turing complete, Turing machine, Vilfredo Pareto, We are the 99%

Agents who own a large proportion of the total wealth leave behind larger amounts of sugar, making an investment into the sugarscape and increasing the total wealth. The Gini Coefficient To compare the effect of taxation on wealth distribution, we need a metric that measures how distributed or flat a certain wealth distribution is. We use the Gini coefficient, which is often used in economics to measure the wealth gap (see http://en.wikipedia.org/wiki/Gini_coefficient). The Gini coefficient is between 0 and 1, with 0 the measurement of a perfectly uniform distribution and 1 the measurement of a distribution with complete inequality. Figure 11-1 shows a histogram describing the wealth distribution when there is no tax system in place.

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The agents have a similar amount of sugar, and the economy has a low Gini coefficient, 0.02. Figure 11-3 shows that higher taxes in general result in lower Gini coefficients. This makes sense, since the point of our tax system is to redistribute wealth. In this model, perfect equality comes at a price. With no taxation, the mean wealth was 358; with a 20% tax rate, it drops to 157. Figure 11-4 shows the effect of tax rate on wealth; mean wealth gets smaller as taxes get higher. Figure 11-2. Histogram of wealth with tax system Figure 11-3. The Gini coefficient versus the tax rate Figure 11-4. Mean wealth versus tax rate Conclusion It’s up to a society to determine its ideal wealth distribution.

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Self-Organized Criticality Sand Piles Spectral Density Fast Fourier Transform Pink Noise Reductionism and Holism SOC, Causation, and Prediction 10. Agent-Based Models Thomas Schelling Agent-Based Models Traffic Jams Boids Prisoner’s Dilemma Emergence Free Will 11. Case Study: Sugarscape The Original Sugarscape The Occupy Movement A New Take on Sugarscape Pygame Taxation and the Leave Behind The Gini Coefficient Results with Taxation Conclusion 12. Case Study: Ant Trails Introduction Model Overview API Design Sparse Matrices wx Applications 13. Case Study: Directed Graphs and Knots Directed Graphs Implementation Detecting Knots Knots in Wikipedia 14. Case Study: The Volunteer’s Dilemma The Prairie Dog’s Dilemma Analysis The Norms Game Results Improving the Chances A.

Unhealthy societies: the afflictions of inequality by Richard G. Wilkinson

attribution theory, business cycle, clean water, correlation coefficient, experimental subject, full employment, fundamental attribution error, Gini coefficient, income inequality, income per capita, Indoor air pollution, invisible hand, land reform, longitudinal study, means of production, purchasing power parity, rising living standards, twin studies, upwardly mobile

It is included here only for the sake of its Japanese data.) The measure of income distribution used in figure 5.6 is the Gini coefficient, which measures inequality across the whole population rather than by just comparing the rich and poor. Its value varies between 0, which would mean everyone had the same income, and 1, which would mean all income went to one individual and no one else would have any. This means that a value of 0.4 (to the right on the Figure 5.6: Life expectancy (M&F) and Gini coefficients of post-tax income inequality (standardised for household size) Sources: Data from M. Sawyer, Income distribution in OECD countries, OECD Economic Outlook, Occasional Studies, 1976, 3–36, Table 11; and World Bank Income distribution and health 85 horizontal axis) represents greater inequality than 0.3.

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Both the Gini coefficient and the ratio of incomes of the bottom and top 20 per cent of the population shown in the figure record a slow widening of income differences until the mid-1980s and then, from about 1985 onwards, a more rapid widening. The rate at which inequality increased during this period is almost unprecedented. Among the OECD countries only New Zealand saw a faster Income distribution and health 95 Figure 5.9: Widening income differences: distribution of disposable income adjusted for household size, UK Note: The Gini coefficient measures the degree of income inequality—not just between rich and poor, but across the whole population.

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RA418.W45 1996 306.4´61–dc20 96–21560 ISBN 0-203-42168-X Master e-book ISBN ISBN 0-203-72992-7 (Adobe eReader Format) ISBN 0-415-09234-5 (hbk) ISBN 0-415-09235-3 (pbk) Contents List of illustrations Preface 1 Introduction: the social economy of health vii ix 1 Part I The health of societies 2 Health becomes a social science 13 3 Rising life expectancy and the epidemiological transition 29 Part II Health inequalities within societies 4 The problem of health inequalities 53 5 Income distribution and health 72 Part III Social cohesion and social conflict 6 A small town in the USA, wartime Britain, Eastern Europe and Japan 113 7 An anthropology of social cohesion 137 8 The symptoms of disintegration 153 Part IV How society kills 9 The psychosocial causes of illness 10 Baboons, civil servants and children’s height 175 193 vi Contents Part V Redistribution, economic growth and the quality of life 11 Social capital: putting Humpty together again 211 Bibliography Name index Subject index 233 247 251 Illustrations FIGURES 3.1 3.2 4.1 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 Life expectancy and income per capita for selected countries and periods Increases in life expectancy in relation to percentage increase in GDPpc Relative risk of death from coronary heart disease according to employment grade, and proportions of differences that can be explained statistically by various risk factors Income and mortality among white US men GDP per capita and life expectancy in OECD countries in 1990 The cross-sectional relationship between income distribution and life expectancy (M&F) at birth in developed countries, c. 1981 The annual rate of change of life expectancy in twelve European Community countries and the rate of change in the percentage of the population in relative poverty, 1975–85 The relationship between income distribution and mortality among fifty states of the USA in 1990 Life expectancy (M&F) and Gini coefficients of posttax income inequality (standardised for household size) Social class differences in infant mortality in Sweden compared with England and Wales Social class differences in mortality of men 20–64 years: Sweden compared with England and Wales 34 37 65 73 74 76 77 79 84 87 88 viii Illustrations 5.9 Widening income differences: distribution of disposable income adjusted for household size, UK 5.10 Indices showing changes in death rates among young adults, children and infants (M&F combined, England and Wales, 1975–92) 5.11 Trends in life expectancy among blacks and whites in the USA (M&F combined) 5.12 Three measures of self-reported health in relation to income (M&F combined) 65 years and over living alone or in two-person households 8.1 The relationship between income distribution and homicide among the states of the USA in 1990 8.2 The decline in reading standards.

A World Without Work: Technology, Automation, and How We Should Respond by Daniel Susskind

"World Economic Forum" Davos, 3D printing, agricultural Revolution, AI winter, Airbnb, Albert Einstein, algorithmic trading, AlphaGo, artificial general intelligence, autonomous vehicles, basic income, Bertrand Russell: In Praise of Idleness, Big Tech, blue-collar work, Boston Dynamics, British Empire, Capital in the Twenty-First Century by Thomas Piketty, cloud computing, computer age, computer vision, computerized trading, creative destruction, David Graeber, David Ricardo: comparative advantage, deep learning, DeepMind, Demis Hassabis, demographic transition, deskilling, disruptive innovation, Donald Trump, Douglas Hofstadter, driverless car, drone strike, Edward Glaeser, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, fake news, financial innovation, flying shuttle, Ford Model T, fulfillment center, future of work, gig economy, Gini coefficient, Google Glasses, Gödel, Escher, Bach, Hans Moravec, income inequality, income per capita, industrial robot, interchangeable parts, invisible hand, Isaac Newton, Jacques de Vaucanson, James Hargreaves, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joi Ito, Joseph Schumpeter, Kenneth Arrow, Kevin Roose, Khan Academy, Kickstarter, Larry Ellison, low skilled workers, lump of labour, machine translation, Marc Andreessen, Mark Zuckerberg, means of production, Metcalfe’s law, natural language processing, Neil Armstrong, Network effects, Nick Bostrom, Occupy movement, offshore financial centre, Paul Samuelson, Peter Thiel, pink-collar, precariat, purchasing power parity, Ray Kurzweil, ride hailing / ride sharing, road to serfdom, Robert Gordon, Sam Altman, Second Machine Age, self-driving car, shareholder value, sharing economy, Silicon Valley, Snapchat, social intelligence, software is eating the world, sovereign wealth fund, spinning jenny, Stephen Hawking, Steve Jobs, strong AI, tacit knowledge, technological solutionism, TED Talk, telemarketer, The Future of Employment, The Rise and Fall of American Growth, the scientific method, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, Thorstein Veblen, Travis Kalanick, Turing test, Two Sigma, Tyler Cowen, Tyler Cowen: Great Stagnation, universal basic income, upwardly mobile, warehouse robotics, Watson beat the top human players on Jeopardy!, We are the 99%, wealth creators, working poor, working-age population, Y Combinator

Exploring existing inequalities, then, is useful because it shows us how a world with insufficient work can emerge from what we already see around us. In a sense, today’s inequalities are the birth pangs of tomorrow’s technological unemployment. INCOME INEQUALITY How can we see the current trends in inequality? One way is to look at inequality of overall incomes, and in particular something known as the Gini coefficient. This is a number that captures how incomes are spread out: if everyone has the same income in a particular society, then its Gini coefficient is zero, and if only one person earns everything, then the Gini coefficient is one.9 In most developed countries, this number has risen significantly over the last few decades.10 (In less-developed countries the story is somewhat ambiguous: their Gini coefficients were usually very high to begin with, but have remained relatively stable.)

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In the United States, for example, from 1981 to 2017, the income share of the top 0.1 percent increased more than three and a half times from its already disproportionately high level, and the share of the top 0.01 percent rose more than fivefold.16 The three measures of income inequality do diverge sometimes, of course, and it is possible to point to particular instances where some measurement departs from an upward trend. The Gini coefficient in the UK, for instance, has not really risen for twenty-five years.17 But it is rare to find a country where none of the three measurements show rising inequality; in the UK, as Figure 8.3 shows, the income share of the 1 percent has soared. And when all the measures, applied to lots of different countries, are taken together, the big picture is clear: in the most prosperous parts of the world, we are seeing a move toward societies with greater income inequality.

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See both Era Dabla-Norris, Kalpana Kochhar, Frantisek Ricka, et al., “Causes and Consequences of Income Inequality: A Global Perspective,” IMF Staff Discussion Note (2015); and Jan Luiten van Zanden, Joerg Baten, Marco Mira d’Ercole, et al., “How Was Life? Global Well-Being Since 1820,” OECD (2014), p. 207: “It is hard not to notice the sharp increase in income inequality experienced by the vast majority of countries from the 1980s. There are very few exceptions to this…” 11.  See, for instance, Piketty, Capital in the Twenty-First Century, p. 266. 12.  These are post-tax and transfer Gini coefficients for 2017, or latest available year. This is an updated version of Figure 1.3 in OECD, “In It Together: Why Less Inequality Benefits All” (2015), using OECD (2019) data; http://www.oecd.org/social/income-distribution-database.htm (accessed April 2019). 13.  

The Great Divide: Unequal Societies and What We Can Do About Them by Joseph E. Stiglitz

"World Economic Forum" Davos, accelerated depreciation, accounting loophole / creative accounting, affirmative action, Affordable Care Act / Obamacare, agricultural Revolution, Alan Greenspan, Asian financial crisis, banking crisis, Bear Stearns, Berlin Wall, Bernie Madoff, Branko Milanovic, Bretton Woods, business cycle, capital controls, Capital in the Twenty-First Century by Thomas Piketty, carbon tax, Carmen Reinhart, carried interest, classic study, clean water, collapse of Lehman Brothers, collective bargaining, company town, computer age, corporate governance, credit crunch, Credit Default Swap, deindustrialization, Detroit bankruptcy, discovery of DNA, Doha Development Round, everywhere but in the productivity statistics, Fall of the Berlin Wall, financial deregulation, financial innovation, full employment, gentrification, George Akerlof, ghettoisation, Gini coefficient, glass ceiling, Glass-Steagall Act, global macro, global supply chain, Home mortgage interest deduction, housing crisis, income inequality, income per capita, information asymmetry, job automation, Kenneth Rogoff, Kickstarter, labor-force participation, light touch regulation, Long Term Capital Management, low interest rates, manufacturing employment, market fundamentalism, mass incarceration, moral hazard, mortgage debt, mortgage tax deduction, new economy, obamacare, offshore financial centre, oil shale / tar sands, Paul Samuelson, plutocrats, purchasing power parity, quantitative easing, race to the bottom, rent-seeking, rising living standards, Robert Solow, Ronald Reagan, Savings and loan crisis, school vouchers, secular stagnation, Silicon Valley, Simon Kuznets, subprime mortgage crisis, The Chicago School, the payments system, Tim Cook: Apple, too big to fail, trade liberalization, transaction costs, transfer pricing, trickle-down economics, Turing machine, unpaid internship, upwardly mobile, urban renewal, urban sprawl, very high income, War on Poverty, Washington Consensus, We are the 99%, white flight, winner-take-all economy, working poor, working-age population

And if we broaden the range of metrics we consider, we see that even after two decades of “malaise,” Japan’s performance is far superior to that of the United States. Consider, for instance, the Gini coefficient, the standard measure of inequality. Zero represents perfect equality, and 1 stands for perfect inequality. While Japan’s Gini coefficient stands today at around 0.33, the number for the United States is 0.38, according to the Organization for Economic Cooperation and Development. (Other data sources put the United States’ level of inequality at even higher levels.) In the United States, the average income of the top 10 percent is 15.9 times that of the bottom 10 percent—compared with 10.7 times for Japan.

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At the same time, while Africa has finally started to grow, creating an increasing number of middle-class African families, the number of people in poverty has remained very high, with some 415 million people living on less than $1.25 per day. Putting all of this together, one reaches a disappointing result: overall inequality, in the way it is conventionally measured (the Gini coefficient, a number ranging from zero, with perfect equality, to one, with perfect inequality), has barely budged. The Piketty Phenomenon The final two articles of this section are, in part, a response to the enormous success of the economist Thomas Piketty’s book Capitalism in the Twenty-First Century. The success of that book echoed the growing concern about inequality, a concern expressed in Davos by the world’s elite, and consistent with the way my own article “Of the 1 percent, by the 1 Percent, for the 1 Percent” had gone viral.

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In the United States, the average income of the top 10 percent is 15.9 times that of the bottom 10 percent—compared with 10.7 times for Japan. The reasons for these differences are political choices, not economic inevitability. Also according to the OECD, the Gini coefficient before taxes and transfer payments is about the same in the two countries: 0.499 for the United States, and 0.488 for Japan. But the United States does only a little to modulate its inequality, bringing it down to .38. Japan does much more, reducing the Gini coefficient to 0.33. To be sure, Japan’s situation is not perfect. The country needs to do better in caring for its “older old,” those over 75. This cohort constitutes a growing share of the world’s aging population.

Losing Control: The Emerging Threats to Western Prosperity by Stephen D. King

"World Economic Forum" Davos, Admiral Zheng, Alan Greenspan, asset-backed security, barriers to entry, Berlin Wall, Bernie Madoff, Bretton Woods, BRICs, British Empire, business cycle, capital controls, Celtic Tiger, central bank independence, collateralized debt obligation, corporate governance, credit crunch, crony capitalism, currency manipulation / currency intervention, currency peg, David Ricardo: comparative advantage, demographic dividend, demographic transition, Deng Xiaoping, Diane Coyle, Fall of the Berlin Wall, financial deregulation, financial innovation, fixed income, foreign exchange controls, Francis Fukuyama: the end of history, full employment, G4S, George Akerlof, German hyperinflation, Gini coefficient, Great Leap Forward, guns versus butter model, hiring and firing, income inequality, income per capita, inflation targeting, invisible hand, Isaac Newton, junk bonds, knowledge economy, labour market flexibility, labour mobility, liberal capitalism, low interest rates, low skilled workers, market clearing, Martin Wolf, mass immigration, Meghnad Desai, Mexican peso crisis / tequila crisis, Naomi Klein, new economy, old age dependency ratio, Paul Samuelson, Ponzi scheme, price mechanism, price stability, purchasing power parity, rent-seeking, reserve currency, rising living standards, Ronald Reagan, Savings and loan crisis, savings glut, Silicon Valley, Simon Kuznets, sovereign wealth fund, spice trade, statistical model, technology bubble, The Great Moderation, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, The Market for Lemons, The Wealth of Nations by Adam Smith, Thomas Malthus, trade route, transaction costs, Washington Consensus, We are all Keynesians now, women in the workforce, working-age population, Y2K, Yom Kippur War

Nationalism, in part, was a protest against an empire that had unfairly kept the benefits of economic progress residing with a privileged minority. EMERGING NATIONS AND THE RISE OF INCOME INEQUALITY IN THE DEVELOPED WORLD According to the World Bank’s World Development Indicators, the US and China have roughly equivalent income distributions, as measured by Gini coefficients. (The Gini coefficient is typically expressed as a ratio between 0 and 1, where 0 represents a precisely equal income distribution and a figure of 1 implies that one person has made off with all the income. It’s no great surprise that countries ruled by despots tend to have very high Gini coefficients.) By Western European or Japanese standards, both the US and China are very unequal societies.

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This is an intriguing result given that the US is regarded as the arch-capitalist economy whereas China still, publicly, hangs on to its communist credentials. Figure 6.1: Gini coefficients Source: World Development Indicators 2009, World Bank There are three key problems with this data, at least for the purposes of my argument. First, there may be no statistical consistency across countries, leading to an apples and pears problem. Second, the source years for the data vary enormously, from 1993 in Japan to 2007 in Brazil. Third, because the World Bank offers no consistent time series, it’s difficult to work out how globalization may have affected income inequality over time. Nevertheless, other sources are very much consistent with the idea that both the US and China have seen big increases in income inequality in recent decades.

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Nevertheless, other sources are very much consistent with the idea that both the US and China have seen big increases in income inequality in recent decades. The US Census Bureau calculates that, between 1967 and 2007, the Gini coefficient for American household income rose from 0.397 to 0.463. The share of household income delivered to the highest quintile rose over the same period from around 43 per cent to 50 per cent. Meanwhile, the ratio between the richest 5 per cent of households and the poorest 10 per cent jumped from 11.7 to 14.6. Chinese data are far more difficult to obtain and offer nothing like the wealth of information provided by the US statisticians.

Two Nations, Indivisible: A History of Inequality in America: A History of Inequality in America by Jamie Bronstein

Affordable Care Act / Obamacare, back-to-the-land, barriers to entry, basic income, Bernie Sanders, big-box store, Black Lives Matter, blue-collar work, Branko Milanovic, British Empire, Capital in the Twenty-First Century by Thomas Piketty, clean water, cognitive dissonance, collateralized debt obligation, collective bargaining, Community Supported Agriculture, corporate personhood, crony capitalism, deindustrialization, desegregation, Donald Trump, ending welfare as we know it, Frederick Winslow Taylor, full employment, Gini coefficient, Glass-Steagall Act, income inequality, interchangeable parts, invisible hand, job automation, John Maynard Keynes: technological unemployment, labor-force participation, land reform, land tenure, longitudinal study, low skilled workers, low-wage service sector, mandatory minimum, mass incarceration, minimum wage unemployment, moral hazard, moral panic, mortgage debt, New Urbanism, non-tariff barriers, obamacare, occupational segregation, Occupy movement, oil shock, plutocrats, price discrimination, race to the bottom, rent control, road to serfdom, Ronald Reagan, Sam Peltzman, scientific management, Scientific racism, Simon Kuznets, single-payer health, Strategic Defense Initiative, strikebreaker, the long tail, too big to fail, trade route, transcontinental railway, Triangle Shirtwaist Factory, trickle-down economics, universal basic income, Upton Sinclair, upwardly mobile, urban renewal, vertical integration, W. E. B. Du Bois, wage slave, War on Poverty, women in the workforce, working poor, Works Progress Administration

Then one measures the way the actual curve compares with both a “perfect equality” scenario (one in which all households have the same income or wealth) and a “perfect inequality” scenario (one in which one household has 100 percent of the income or wealth and the other households have 0). A Gini coefficient of zero represents perfect equality; a coefficient of 1 represents perfect inequality.16 Peter Lindert and Jeffrey Williamson, the most-cited economic historians to write about American inequality, claim that inequality followed this trajectory: a period of relative equality during the American Revolution was followed by growing inequality before the Civil War, high levels of inequality at the turn of the century, and then finally a leveling off of inequality in the middle decades of the twentieth century. While this is the dominant view, economic historian Carole Shammas showed that Williamson and Lindert omitted from their calculations married women (subject to laws that excluded them from ownership of most property, so without a claim to income in most cases) and African Americans (the vast majority of them slaves, and thus without income at all).

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The United States supplied 99 percent of all of the raw cotton used by Great Britain’s massive textile industry in 1851, and cotton represented 60 percent of American exports.9 The Gini coefficient of wealth inequality, which had been 0.694 in 1774, increased to 0.832 in 1860. Even incremental changes in the economy were producing significant inequality.10 The inequality of the antebellum period is even more acute when we consider the plight of enslaved people, who are excluded from the above Gini coefficient calculation. The inequality of the antebellum period had physical effects. Over the period between 1780 and 1850, life expectancies at age 10 declined in the United States from a high of almost 56 years to a low of 48, and mean heights dropped from 5 feet 7 inches for white men to 5 feet 6 inches.

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Whatever “equality” means, it cannot mean a nation in which over half the population has no claim to income or to wealth.17 Shammas argued that historians of inequality should focus on wealth rather than income, since in her estimation wealth is even more likely to be lopsided than income, and more likely to confer political power. She recalculated Gini coefficients for the period from 1774 to 1986 and showed that throughout that entire period, the Gini coefficient was at least 0.72, rising to 0.83 during the 1850s and 1860s. For the purposes of comparison, the Gini coefficient of wealth for the United States in 2015 was 80.56, making it the most unequal country in the developed world.18 Moreover, consistently, the wealth of the first, second, and third quintiles of the population combined—that is, the poorest 60 percent of the population—never exceeded 11 percent of the nation’s total wealth.

Rewriting the Rules of the European Economy: An Agenda for Growth and Shared Prosperity by Joseph E. Stiglitz

"World Economic Forum" Davos, accelerated depreciation, Airbnb, Alan Greenspan, balance sheet recession, bank run, banking crisis, barriers to entry, Basel III, basic income, behavioural economics, benefit corporation, Berlin Wall, bilateral investment treaty, business cycle, business process, Capital in the Twenty-First Century by Thomas Piketty, carbon tax, central bank independence, collapse of Lehman Brothers, collective bargaining, corporate governance, corporate raider, corporate social responsibility, creative destruction, credit crunch, deindustrialization, discovery of DNA, diversified portfolio, Donald Trump, eurozone crisis, Fall of the Berlin Wall, financial engineering, financial intermediation, Francis Fukuyama: the end of history, full employment, gender pay gap, George Akerlof, gig economy, Gini coefficient, Glass-Steagall Act, hiring and firing, housing crisis, Hyman Minsky, income inequality, independent contractor, inflation targeting, informal economy, information asymmetry, intangible asset, investor state dispute settlement, invisible hand, Isaac Newton, labor-force participation, liberal capitalism, low interest rates, low skilled workers, market fundamentalism, mini-job, moral hazard, non-tariff barriers, offshore financial centre, open economy, Paris climate accords, patent troll, pension reform, price mechanism, price stability, proprietary trading, purchasing power parity, quantitative easing, race to the bottom, regulatory arbitrage, rent-seeking, Robert Shiller, Ronald Reagan, selection bias, shareholder value, Silicon Valley, sovereign wealth fund, TaskRabbit, too big to fail, trade liberalization, transaction costs, transfer pricing, trickle-down economics, tulip mania, universal basic income, unorthodox policies, vertical integration, zero-sum game

International Evidence,” Journal of the European Economic Association 12, no. 4 (2014): 949–68, https://doi.org/10.1111/jeea.12083. 8. The Gini coefficient is a common measurement of inequality; the higher the number, the greater the inequality. Typically, Gini coefficients change little from year to year, so these large changes in a span of eight years are unusual. See Eurostat, “Gini Coefficient of Advertised Disposable Income,” European Commission, Feb. 15, 2019, http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=ilc_di12b&lang=en. 9. Eurostat, “Gini Coefficient of Equivalized Disposable Income,” European Commission, Aug. 17, 2018, https://ec.europa.eu/eurostat/tgm/table.do?

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When there is a high level of unemployment and excess capacity, what limits output is aggregate demand. If demand grew more rapidly, then output and incomes would also grow more quickly. Far graver developments in inequality have followed the crisis and recession in southern European countries than elsewhere. Indeed, part of the argument for austerity was that it would contribute to internal devaluation by forcing wages down and making exports more competitive. In fact, all measures of inequality now show widening gaps. For instance, from 2007 to 2015, the Gini coefficient (before any transfers of income) increased from 49.4 to 60.7 for Greece and from 45.4 to 50.8 for Spain.8 And the pressure on state finances meant that Greece, Spain, and others could not cushion the losses through the standard welfare state; even after-transfer Gini coefficients rose.9 Indeed, in many countries, there were cutbacks in the provision of public services, which hit those in the middle and bottom of the income scale particularly hard.

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For instance, from 2007 to 2015, the Gini coefficient (before any transfers of income) increased from 49.4 to 60.7 for Greece and from 45.4 to 50.8 for Spain.8 And the pressure on state finances meant that Greece, Spain, and others could not cushion the losses through the standard welfare state; even after-transfer Gini coefficients rose.9 Indeed, in many countries, there were cutbacks in the provision of public services, which hit those in the middle and bottom of the income scale particularly hard. In turn, rising inequality in the EU chipped away at aggregate demand and, by extension, employment. It was part of the vicious cycle into which Europe had fallen. Of course, there are well-known fiscal and monetary policies that governments could have used to respond to the decrease in aggregate demand caused by growing inequality. For example, if governments spend more and tax less or if interest rates fall and credit availability increases, aggregate demand can be restored to a level that ensures full employment.

The Economics Anti-Textbook: A Critical Thinker's Guide to Microeconomics by Rod Hill, Anthony Myatt

American ideology, Andrei Shleifer, Asian financial crisis, bank run, barriers to entry, behavioural economics, Bernie Madoff, biodiversity loss, business cycle, cognitive dissonance, collateralized debt obligation, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, David Ricardo: comparative advantage, different worldview, electricity market, endogenous growth, equal pay for equal work, Eugene Fama: efficient market hypothesis, experimental economics, failed state, financial innovation, full employment, gender pay gap, Gini coefficient, Glass-Steagall Act, Gunnar Myrdal, happiness index / gross national happiness, Home mortgage interest deduction, Howard Zinn, income inequality, indoor plumbing, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), invisible hand, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kenneth Arrow, liberal capitalism, low interest rates, low skilled workers, market bubble, market clearing, market fundamentalism, Martin Wolf, medical malpractice, military-industrial complex, minimum wage unemployment, moral hazard, Paradox of Choice, Pareto efficiency, Paul Samuelson, Peter Singer: altruism, positional goods, prediction markets, price discrimination, price elasticity of demand, principal–agent problem, profit maximization, profit motive, publication bias, purchasing power parity, race to the bottom, Ralph Nader, random walk, rent control, rent-seeking, Richard Thaler, Ronald Reagan, search costs, shareholder value, sugar pill, The Myth of the Rational Market, the payments system, The Spirit Level, The Wealth of Nations by Adam Smith, Thorstein Veblen, ultimatum game, union organizing, working-age population, World Values Survey, Yogi Berra

The most commonly used measure that summarizes the entire income distribution is the Gini ­coefficient. This is the ratio of the area between the Lorenz curve and the 199 9  |  Government, taxation table 9.2 Measures of income inequality 45-degree line (marked ‘A’ in Figure 9.1) and the entire area under the 45-degree line (A + B in the figure). So the Gini coefficient = A/(A + B). It’s zero if income is equally distributed; it’s 1 if one household has everything. Table 9.2 also shows estimates of the Gini coefficient for a selection of countries. With the exception of India, the developing countries shown have much higher income inequality than the developed countries.

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This is not surprising in light of our discussion in Chapter 2 of the difficulties of conclusive empirical testing. She points out that ideas about the growth-retarding effects of inequality centre around inequality at the bottom of the income distribution, while inequality at the top end of the distribution is sometimes seen as facilitating growth. Testing the effects of income inequality using a single measure of inequality such as the Gini coefficient misses these differences and looks only at some average of the effects (ibid.: 273–4). Instead, she examines a group of relatively high-income countries using data on their income distributions.

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The gap between the points showing actual household incomes (called the Lorenz curve) and this reference line indicates the nature and extent of income inequality. Income inequality is usually summarized in a single number to aid in comparing inequality over time and across countries. One simple way is to calculate the ratio of the shares of total income held by the top 10 or 20 per cent of 198 Country Top 10% to bottom 10% Top 20% to bottom 20% Gini coefficient 8.1 4.5 6.2 6.1 5.6 5.5 6.9 6.9 9.2 7.8 9.4 9.1 8.2 9.4 8.8 10.3 12.5 11.6 13.8 12.5 15 15.9 24.6 4.3 3.4 4 3.9 3.8 3.8 4.3 4.4 5.1 4.7 5.5 5.6 4.9 5.6 5.6 6 7 6.5 7.2 6.8 8 8.4 12.8 0.247 0.249 0.250 0.258 0.269 0.269 0.283 0.291 0.309 0.316 0.326 0.327 0.330 0.343 0.345 0.347 0.352 0.360 0.360 0.362 0.385 0.408 0.461 8.6 12.7 17.8 21.6 48.3 33 51.3 33.1 63.8 5.6 7.6 9.7 12.2 16 15.7 21.8 17.9 25.3 0.368 0.399 0.437 0.469 0.482 0.549 0.570 0.578 0.586 Some OECD countries Denmark Japan Sweden Norway Finland Hungary Germany Austria Netherlands Korea, South Canada France Belgium Ireland Poland Spain Australia Italy United Kingdom New Zealand Portugal United States Mexico Some non-OECD countries India Russia Nigeria China (excluding Hong Kong) Venezuela Chile Brazil South Africa Colombia Note: Values are for income or expenditure shares.

The Great Demographic Reversal: Ageing Societies, Waning Inequality, and an Inflation Revival by Charles Goodhart, Manoj Pradhan

asset-backed security, banks create money, Berlin Wall, bonus culture, Boris Johnson, Branko Milanovic, Brexit referendum, business cycle, capital controls, carbon tax, central bank independence, commodity super cycle, coronavirus, corporate governance, COVID-19, deglobalization, demographic dividend, demographic transition, Deng Xiaoping, en.wikipedia.org, Fall of the Berlin Wall, financial independence, financial repression, fixed income, full employment, gig economy, Gini coefficient, Greta Thunberg, housing crisis, income inequality, inflation targeting, interest rate swap, job automation, Kickstarter, long term incentive plan, longitudinal study, low interest rates, low skilled workers, manufacturing employment, Martin Wolf, mass immigration, middle-income trap, non-tariff barriers, offshore financial centre, oil shock, old age dependency ratio, open economy, paradox of thrift, Pearl River Delta, pension reform, Phillips curve, price stability, private sector deleveraging, quantitative easing, rent control, savings glut, secular stagnation, shareholder value, special economic zone, The Great Moderation, The Wealth of Nations by Adam Smith, total factor productivity, working poor, working-age population, yield curve, zero-sum game

There are two main databases, the World Bank’s PovcalNet database and the World Inequality Database. Out of the many potential measures of inequality we initially select four, (but they all tend in the same directions), to wit (i) the Gini coefficient,3 Diagram 7.1, for a number of OECD countries, (ii) for a few selected countries the share of income of the top 10 and 1% of the distribution, Tables 7.1 and 7.2, and (iii) the share of wealth for the top 10%, Table 7.3. We show these latter data points for the income inequality data at five-year intervals for the USA, UK, Germany, France, Sweden, Italy Japan, China, Brazil, Egypt and India, and the wealth inequality data for four countries, USA, China, France and UK.

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In their paper ‘The Great Divide’; ‘Regional Inequality and Fiscal Policy’, the authors, Gbohoui et al., state that: Redistributive fiscal policies have helped reduce, but not fully offset, rising nationwide income inequality (IMF 2017; Immervoll and Richardson 2011). For advanced OECD countries, the average redistributive effect of fiscal policy—measured by the difference in Gini coefficients on household income before and after taxes and transfers—is about one-third (from 0.49 Gini points from market income inequality to 0.31 Gini points for disposable income inequality in 2015) (Figure 6 top left panel).

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George, Henry Geriatricians German pension reform German retirees react to pension reforms Germany Germany’s dependency ratio Gig economy ‘Gilets jaunes’ Gini coefficient Gini coefficient, measure of income dispersion Global ageing Global demographic headwinds Global disinflation Global dominance Global economy, ageing of Global environment, changing Global Financial Crisis (GFC) Global forces, dominant Global growth, driven by now ageing economies Global growth, India beat China Global inequality Global inequality, falling Globalisation Globalisation, effect underestimated Globalisation, its Great Reversal Globalisation, result of, a triumph for macro-economics Globalisation, slowing Globalisation effects, not significant in short run Global resources Global savings glut Gold discoveries Gold standard Goodhart, C.A.E.

China's Future by David Shambaugh

Berlin Wall, capital controls, demographic dividend, demographic transition, Deng Xiaoping, facts on the ground, financial intermediation, financial repression, Gini coefficient, Great Leap Forward, guns versus butter model, high net worth, high-speed rail, Kickstarter, knowledge economy, low skilled workers, market bubble, megacity, middle-income trap, Mikhail Gorbachev, military-industrial complex, New Urbanism, offshore financial centre, open economy, Pearl River Delta, rent-seeking, secular stagnation, short selling, South China Sea, special drawing rights, too big to fail, urban planning, Washington Consensus, working-age population, young professional

While not as high and acute as South Africa, Brazil, or Nigeria, China’s Gini rating ranks it fourth in the world (Figure 3.2). Inequality is not simply a statistical measure of income. As scholars Jane Duckett and Guohui Wang point out, inequality involves access by individuals and households to public services such as housing, healthcare, and education; it biases people in their search for employment, and it involves discrimination and unequal opportunities for women and minorities.14 Figure 3.1 China’s Gini Coefficient Source: China National Bureau of Statistics. Figure 3.2 China’s Gini Coefficient in Comparison Sources: China National Bureau of Statistics; OECD; World Bank.

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Another study by the Asian Development Bank is even more bullish about China’s middle class potential, arguing that by 2030 it will account for 80 percent of the total population.12 This magnitude and rapidity of growth is probably unlikely, but it still points toward the dramatic social transformation that lies ahead in China. A particularly acute social problem in China, now and into the future, is inequality. China is now among the top ten countries of the world’s highest Gini Coefficient rankings, the main measure of social inequality in societies worldwide, although the official estimates are not in agreement. The World Bank’s most recent estimate was .37 in 2011, and is the lowest, while the Chinese government’s own calculation (Figure 3.1) puts it higher, at .47 for the same year, while others put it in between at .42.13 While high, China’s Gini ranking peaked around 2009 and has fallen since (paralleling a global pattern).

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China’s Growing Military Capabilities China’s Future Impact on the World Notes Index End User License Agreement List of Figures 1.1 Possible Pathways for China’s Future 1.2 Pathways and Likely Results for China’s Future 1.3 The J-Curve 2.1 China’s Development Strategy 2.2 China’s GDP Growth Rates 2.3 China’s Alternative GDP Projections 3.1 China’s Gini Coefficient 3.2 China’s Gini Coefficient in Comparison 3.3 China’s Reported Incidents of Mass Unrest 3.4 Xinjiang and Tibet 3.5 Hong Kong’s “Umbrella Revolution” 3.6 Taiwan’s Sunflower Movement 3.7 China’s Urbanization Growth 3.8 China’s Demographic Projections 4.1 China’s Political Orientation 1985–2015 4.2 Zeng Qinghong 4.3 Xi Jinping 5.1 China’s Trade in Asia 5.2 Asian Perceptions of China’s Territorial Disputes 5.3 Perceptions of China as a Global Power 5.4 American Views of China 2005–2015 5.5 Presidents Xi Jinping and Vladimir Putin 5.6 China’s Soft Power Appeal in the Developing World 5.7 China’s Military Spending 2000-2014 Dedicated to Harry Harding China’s Future David Shambaugh polity Copyright © David Shambaugh 2016 The right of David Shambaugh to be identified as Author of this Work has been asserted in accordance with the UK Copyright, Designs and Patents Act 1988.

Capital in the Twenty-First Century by Thomas Piketty

accounting loophole / creative accounting, Asian financial crisis, banking crisis, banks create money, Berlin Wall, book value, Branko Milanovic, British Empire, business cycle, capital controls, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, carbon tax, central bank independence, centre right, circulation of elites, collapse of Lehman Brothers, conceptual framework, corporate governance, correlation coefficient, David Ricardo: comparative advantage, demographic transition, distributed generation, diversification, diversified portfolio, European colonialism, eurozone crisis, Fall of the Berlin Wall, financial intermediation, full employment, Future Shock, German hyperinflation, Gini coefficient, Great Leap Forward, high net worth, Honoré de Balzac, immigration reform, income inequality, income per capita, index card, inflation targeting, informal economy, invention of the steam engine, invisible hand, joint-stock company, Joseph Schumpeter, Kenneth Arrow, low interest rates, market bubble, means of production, meritocracy, Money creation, mortgage debt, mortgage tax deduction, new economy, New Urbanism, offshore financial centre, open economy, Paul Samuelson, pension reform, power law, purchasing power parity, race to the bottom, randomized controlled trial, refrigerator car, regulatory arbitrage, rent control, rent-seeking, Robert Gordon, Robert Solow, Ronald Reagan, Simon Kuznets, sovereign wealth fund, Steve Jobs, Suez canal 1869, Suez crisis 1956, The Nature of the Firm, the payments system, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, Thomas Malthus, Thorstein Veblen, trade liberalization, twin studies, very high income, Vilfredo Pareto, We are the 99%, zero-sum game

By construction, it ranges from 0 to 1: it is equal to 0 in case of complete equality and to 1 when inequality is absolute, that is, when a very tiny group owns all available resources. In practice, the Gini coefficient varies from roughly 0.2 to 0.4 in the distributions of labor income observed in actual societies, from 0.6 to 0.9 for observed distributions of capital ownership, and from 0.3 to 0.5 for total income inequality. In Scandinavia in the 1970s and 1980s, the Gini coefficient of the labor income distribution was 0.19, not far from absolute equality. Conversely, the wealth distribution in Belle Époque Europe exhibited a Gini coefficient of 0.85, not far from absolute inequality.22 These coefficients—and there are others, such as the Theil index—are sometimes useful, but they raise many problems.

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If this happens, the future could hold in store a new world of inequality more extreme than any that preceded it.21 Problems of Synthetic Indices Before turning to a country-by-country examination of the historical evolution of inequality in order to answer the questions posed above, several methodological issues remain to be discussed. In particular, Tables 7.1–3 include indications of the Gini coefficients of the various distributions considered. The Gini coefficient—named for the Italian statistician Corrado Gini (1884–1965)—is one of the more commonly used synthetic indices of inequality, frequently found in official reports and public debate.

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Indeed, it is impossible to summarize a multidimensional reality with a unidimensional index without unduly simplifying matters and mixing up things that should not be treated together. The social reality and economic and political significance of inequality are very different at different levels of the distribution, and it is important to analyze these separately. In addition, Gini coefficients and other synthetic indices tend to confuse inequality in regard to labor with inequality in regard to capital, even though the economic mechanisms at work, as well as the normative justifications of inequality, are very different in the two cases. For all these reasons, it seemed to me far better to analyze inequalities in terms of distribution tables indicating the shares of various deciles and centiles in total income and total wealth rather than using synthetic indices such as the Gini coefficient.

Planet of Slums by Mike Davis

barriers to entry, Branko Milanovic, Bretton Woods, British Empire, Brownian motion, centre right, clean water, company town, conceptual framework, crony capitalism, declining real wages, deindustrialization, Deng Xiaoping, disinformation, Dr. Strangelove, edge city, European colonialism, failed state, gentrification, Gini coefficient, Hernando de Soto, housing crisis, illegal immigration, income inequality, informal economy, Intergovernmental Panel on Climate Change (IPCC), Internet Archive, jitney, jobless men, Kibera, labor-force participation, land reform, land tenure, Lewis Mumford, liberation theology, low-wage service sector, mandelbrot fractal, market bubble, megacity, microcredit, Nelson Mandela, New Urbanism, Pearl River Delta, Ponzi scheme, RAND corporation, rent control, structural adjustment programs, surplus humans, upwardly mobile, urban planning, urban renewal, War on Poverty, Washington Consensus, working poor

Conspicuous consumption reached hallucinatory levels in Latin America and Africa during the 1980s as the nouveaux riches went on spending sprees in Miami and Paris while their shantytown compatriots starved. Indices of inequality reached record heights in the 1980s. In Buenos Aires the richest decile's share of income increased from 10 times that of the poorest in 1984 to 23 times in 1989. In Rio de Janeiro, inequality as measured in classical GINI coefficients climbed from 0.58 in 1981 to 0.67 in 1989 26 Indeed, throughout Latin America, the 1980s deepened the canyons and elevated the peaks of the world's most extreme social topography. According to a 2003 World Bank report, GINI coefficients are 10 points higher in Latin America than Asia; 17.5 points higher than the OECD; and 20.4 points higher than Eastern Europe.

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percent in 1992 to 28 percent in 1999, despite the much-hyped "success stories" of the border maquiladoras and NAFTA.47 Likewise in Colombia, where urban wages declined, but coca acreage tripled during the regime of Cesar Gaviria (elected in 1990), the drug cartels, according to an OECD report, "were among the most consistently favorable to his neoliberal policies."48 Global inequality, as measured by World Bank economists across the entire world population, reached an incredible GINI coefficient level of 0.67 by the end of the century — this is mathematically equivalent to a situation where the poorest twothirds of the world receive zero income, and the top third receives everything.49 Global turmoil at the the end of the decade, moreover, could be mapped with uncanny accuracy to cities and regions that experienced the sharpest increases in inequality. Throughout the Middle East and Muslim South Asia, a widening gulf between urban rich and poor corroborated the arguments of Islamists and even more radical Salafists about the irreformable corruption of ruling regimes.

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," World Bank working paper (November 2003), p. 17. 52 Soliman, Possible Way Out, p. 9. chronic underinvestment in irrigation. As a result, the wages of casual and informal labor fell, poverty soared at a pace which the National Human Development Report characterized as "unprecedented in Pakistan's history," and urban income inequality, as measured by the GINI coefficient, increased from 31.7 percent in 1992 to 36 percent in 1998.53 The biggest event of the 1990s, however, was the conversion of much of the former "Second World" - European and Asian state socialism — into a new Third World. In the early 1990s those considered to be living in extreme poverty in the former "transitional countries," as the UN calls them, rocketed from 14 million to 168 million: an almost instantaneous mass pauperization without precedent in history.54 Poverty, of course, did exist in the former USSR in an unacknowledged form, but according to World Bank researchers, the rate did not exceed 6 to 10 percent.55 Now, according to Alexey Krasheninnokov; in his report to UN-HABITAT, 60 percent of Russian families live in poverty, and the rest of the population "can only be categorized as middle class by a considerable stretch."

Rethinking Capitalism: Economics and Policy for Sustainable and Inclusive Growth by Michael Jacobs, Mariana Mazzucato

Alan Greenspan, balance sheet recession, banking crisis, basic income, Bear Stearns, Bernie Sanders, Bretton Woods, business climate, business cycle, carbon tax, Carmen Reinhart, central bank independence, circular economy, collaborative economy, complexity theory, conceptual framework, corporate governance, corporate social responsibility, creative destruction, credit crunch, Credit Default Swap, crony capitalism, David Ricardo: comparative advantage, decarbonisation, degrowth, deindustrialization, dematerialisation, Detroit bankruptcy, double entry bookkeeping, Elon Musk, endogenous growth, energy security, eurozone crisis, factory automation, facts on the ground, fiat currency, Financial Instability Hypothesis, financial intermediation, Ford Model T, forward guidance, full employment, G4S, general purpose technology, Gini coefficient, Growth in a Time of Debt, Hyman Minsky, income inequality, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), Internet of things, investor state dispute settlement, invisible hand, Isaac Newton, Joseph Schumpeter, Kenneth Rogoff, Kickstarter, knowledge economy, labour market flexibility, low interest rates, low skilled workers, Martin Wolf, mass incarceration, military-industrial complex, Modern Monetary Theory, Money creation, Mont Pelerin Society, neoliberal agenda, Network effects, new economy, non-tariff barriers, ocean acidification, paradox of thrift, Paul Samuelson, planned obsolescence, Post-Keynesian economics, price stability, private sector deleveraging, quantitative easing, QWERTY keyboard, railway mania, rent-seeking, road to serfdom, savings glut, Second Machine Age, secular stagnation, shareholder value, sharing economy, Silicon Valley, Solyndra, Steve Jobs, stock buybacks, systems thinking, the built environment, The Great Moderation, The Spirit Level, Thorstein Veblen, too big to fail, total factor productivity, Tragedy of the Commons, transaction costs, trickle-down economics, universal basic income, vertical integration, very high income

For instance, in the UK the income share of the top 1 per cent went up from 5.7 per cent in 1978 to 14.7 per cent in 2010, while the share of wealth owned by the top 1 per cent surged from 22.6 per cent in 1970 to 28 per cent in 2010 and the top 10 per cent’s wealth share increased from 64.1 per cent to 70.5 per cent over the same period.17 Figure 3: Income share of the richest 1 per cent in some major industrialised countries Source: The World Wealth and Income Database (latest data available at http://www.wid.world/ (accessed 12 May 2016)) Also disturbing are the patterns that have emerged in transition economies, which at the beginning of their movement to a market economy had low levels of inequality in income and wealth (at least according to available measurements). Today, China’s inequality of income, as measured by its Gini coefficient, is roughly comparable to that of the United States and Russia.18 Across the OECD, since 1985 the Gini coefficient has increased in seventeen of twenty-two countries for which data is available, often dramatically (Figure 2). Moreover, recent research by Piketty and his co-authors has found that the importance of inherited wealth has increased in recent decades, at least in the rich countries for which we have data.

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In 2013 almost three in ten part-time workers across the OECD were ‘involuntary’, meaning that they wanted to work full-time but could only find part-time jobs.28 The result of these trends has been a rise in inequality across the developed world. Between 1985 and 2013, the Gini coefficient measuring income inequality increased in seventeen OECD countries, was little changed in four and decreased in only one (Turkey).29 Wealth inequality has grown even more than that of income, a result both of the shift in the distribution of earnings away from wages and towards profits and of the huge increase in land and property values.

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Some caution should be exercised in comparing different countries’ Gini coefficients: in addition to the well-known flaws in the measure, different databases have used slightly different methodologies or income data to arrive at their respective figures, and thus figures are different depending on the data source. Nevertheless, many different studies confirm these broad trends. One should also be particularly cautious in interpreting differences in Gini coefficients between developed and developing countries: Kuznets (‘Economic growth and income inequality’, The American Economic Review, vol. XLV, no. 1, March 1955, pp. 1–28) put forward a persuasive set of reasons why one might expect inequality to increase in the initial stages of development, as some parts of the country and some groups in the country are better able to seize new opportunities and pull away from others.

Battling Eight Giants: Basic Income Now by Guy Standing

basic income, Bernie Sanders, carbon tax, centre right, collective bargaining, decarbonisation, degrowth, diversified portfolio, Donald Trump, Elon Musk, Extinction Rebellion, full employment, future of work, Gini coefficient, income inequality, Intergovernmental Panel on Climate Change (IPCC), job automation, labour market flexibility, Lao Tzu, longitudinal study, low skilled workers, Martin Wolf, Mont Pelerin Society, moral hazard, North Sea oil, offshore financial centre, open economy, pension reform, precariat, quantitative easing, rent control, Ronald Reagan, selection bias, universal basic income, Y Combinator

But today there are eight more giants stalking the land. Slaying the eight modern giants (1) Inequality The first giant blocking the road to a Good Society is inequality. Britain is far more unequal today than in the 1970s and more unequal than any other major industrialized country barring the United States. The Gini coefficient – a summary measure of income inequality – has risen from under 0.25 in the late 1970s to 0.34 in 2017–18, a huge increase. However, according to the conventional statistics, this increase took place primarily in the 1980s under the Thatcher government. The Gini coefficient has hardly budged since the 1990s, leading many commentators to claim that wealth and income gaps have been broadly stable since then.4 Yet other evidence indicates that the growth of inequality in recent years has been far greater than the conventional statistics suggest.

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Reportedly the richest man in the country, with a self-revealed wealth of over £22 billion, Jim Ratcliffe (a Brexit advocate), just after receiving a knighthood, announced he was off to live in the tax haven of Monaco, so as to avoid paying tax. It is not just the top 1% of incomes that is at issue here. The top 5% has also bounded ahead to take a growing share of total income.15 The researchers in this study claimed that the relative stability of the Gini coefficient therefore implied that inequality had fallen ‘across the large majority of the income distribution’ over the previous decade. Even if true, which is moot, the same may have prevailed in France in the years before 1789; if attention had focused on just the middleincome groups, nobody would have predicted the revolution.16 Moreover, the analyses based on the DWP’s household survey exclude not only the top 3% but also the bottom 3%.17 While the top 3% have gained, the omission of the bottom 3% is also distorting.

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See also individual entries definition 1, 4–8 reasons for need 8–9 security 98, 113, 114 system 1, 20, 23, 26, 32, 37, 52, 70, 84, 90–1, 122 n.7 Basic Income Earth Network (BIEN) 94 behavioural conditionality 70, 73, 77, 114 behaviour-testing 4, 39, 70, 84 benefits 5, 7, 27 conditional schemes 41 social assistance 23 BET365 11 Beveridge, William 8–9, 38 Beveridge model 21 Big Bang liberalization 18 BJP 92 black economy 40, 60 B-Mincome 99–100 Booker, Cory 101 brain development 98–9 132 Branson, Richard 54 Brexit 53 Britain 6, 8–10, 12–18, 20, 23–4, 26–7, 30–1, 33–4, 37–8, 40–2, 55, 57, 59, 90, 101, 104, 112 British Columbia 95 British Constitution 1 Buck, Karen 57 bureaucracy 40, 49, 100, 102 Bureau of Economic Analysis 16 Business Property Relief 58 California 69, 96–7 Canada 35 capacity-to-work tests 6, 104 cap-and-trade approach 34 Capita 50 capital dividend 59 capital fund 89–90 capital grants 59, 75, 76, 92 carbon dividends 37 carbon emissions 33–4 carbon tax 34–5, 37 care deficit 53 care work 36, 53, 67, 74, 84 cash payments 111 cash transfers 99 ‘casino dividend’ schemes 88 charities 48 The Charter of the Forest (1217) 1 Chicago 99 Child Benefit 57, 58, 72, 123 n.4 childcare 99, 110–11 child development 88 Child Tax Credits 81 chronic psychological stress 26 Citizens Advice 46–8 Citizen’s Basic Income Trust 7, 122 n.7, 123 n.4 citizenship rights 1, 29 civil society organizations 79 Index climate change 34 Clinton, Hillary 126 n.4 Clinton, Bill 105 Coalition government 41, 50 cognitive performance 33 collateral damage 53 common dividends 7, 20, 21, 59–60, 69, 73, 75, 83, 84, 85 Commons Fund 8, 35, 57, 59, 89 community cohesion 3 resilience 23 work 84 ‘community payback’ schemes 102 Compass 59 compensation 2, 7, 16, 104 ‘concealed debt’ 24–5 conditional cash transfer schemes 90 Conservative government 9, 85 Conservatives 23 consumer credit 24 consumption 23 contractual obligations 46 Coote, Anna 113 cost of living 25, 49, 52, 83 council house sales 76 council tax 25 Crocker, Geoff 122 n.15 cross-party plans 80 crowd-funded schemes 100 deadweight effects 102 ‘deaths of despair’ 27 Deaton, Angus 10 debt 23–6, 67, 85 debt collection practices 24–5 decarbonization 34 dementia 33 democratic values 69 Democrats 37 demographic changes 15 Index 133 Department for Work and Pensions (DWP) 11–12, 42–8, 50–2, 73, 81, 92, 129 n.6 depression 28, 94 direct taxes 56, 58 disability benefits 6, 49–52, 83 Disability Living Allowance (DLA) 49–51 Disabled People Against Cuts 52 Dividend Allowance 58 ‘dividend capitalism’ 8 domestic violence 29, 87 Dragonfly 92 due process 46, 49 ecological crisis 33, 37, 39, 114 ecological developments 21 ecological disaster 35 ecological taxes and levies 37 economy benefits 20, 60 crisis 106 damage 34 growth 20, 36, 106 industrialized 20 insecurity 21, 35, 39, 89 security 75, 80, 84, 88 system 15, 27, 38 tax-paying 60 uncertainty 8, 22–3, 31 ‘eco-socialism’ 8 ecosystems 33 Edinburgh 80 education 88, 108 Elliott, Larry 122 n.15 employment 16, 22, 39, 60–1, 81, 89, 93–4, 102, 106, 107, 110, 114 Employment Support Allowance (ESA) 27, 41, 49–51 England 28, 63, 110–11 Enlightenment 85 Entrepreneurs’ Relief 18 equality 31, 85 Europe 37 European Foundation for the Improvement of Living and Working Conditions (Eurofound) 120 n.1 European Heart Journal 33 European Union 6, 17, 41 euthanasia 113 extinction 33–7 ‘Extinction Rebellion’ 33 Fabian Society 57–8 Facebook 97 family allowances 56 family benefits 56 family insecurity 23 federal welfare programs 106 Fife 24, 80 financial crash (2007–8) 23, 26, 34 financialization 116 n.22 financial markets 18 Financial Services Authority 123 n.15 Financial Times 19, 123 n.15 financial wealth 18 Finland 28, 61, 93–5 food banks 10, 29–30, 43, 109 food donations 29 food insecurity 108–9 fossil fuels 33–4 France 12, 17, 18, 32, 38, 57 free bus services 112 freedom 8, 30, 84, 85, 101, 114 ‘free food’ 108–9, 129 n.6 ‘free’ labour market 106 free trade 13 Friends Provident Foundation 75 fuel tax 35 fund and dividend model 89 funding 29, 59, 62, 69, 71–2, 112 134 G20 (Group of 20 large economies) 15 Gaffney, Declan 57 Gallup 105 GDP 14, 17–18, 23–4, 34, 36, 59, 89, 108 General Election 91–2, 94 ‘genuine progress indicator’ 36 Germany 17–18, 38, 100 Gillibrand, Kirsten 101 Gini coefficient 9, 12 GiveDirectly 91 Glasgow City 80 globalization 14 Global Wage Report 2016/17 14 global warming 33, 37 Good Society 75, 106 The Great British Benefits Handout (TV series) 92 Great Depression 9 Great Recession 23 greenhouse gas emissions 34, 36 gross cost 110 The Guardian 101, 103, 122–3 n.15 Hansard Society 37 Harris, Kamala 101 Harrop, Andrew 57 Hartz IV 100 HartzPlus 100 health 67, 87, 100 human 33 insurance premiums 35 services 60 healthcare costs 28 hegemony 14 help-to-buy loan scheme 76 Her Majesty’s Revenue and Customs (HMRC) 64, 73, 81 Hirschmann, Albert 56 household debt 24 Index household earnings 16 household survey 12 House of Commons 110–11 housing allowance 95 Housing Benefit 24, 41, 53, 71 housing policy 53 hub-and-spoke model 112 Hughes, Chris 97 humanity 33 human relations 3 ‘immoral’ hazard 109 ‘impact’ effects 78 incentive 62 income 81 assistance 88 average 83 components 11 distribution system 4, 13–14, 38, 67, 84, 107, 114 gap 9 growth 16 insecurity 27 men vs. women 15–16 national 14, 36 pensioners’ 16 rental 13–15, 20 social 14, 16–17 support payments 110 tax 1, 7, 57, 89, 111 transfer 85 volatility 22 India 68, 80, 90–2 Indian Congress Party 91 inequality 2, 4, 9–13, 21, 29, 31, 33, 35, 37, 38, 39, 54, 80, 85, 114 growth 17 income 9–10, 15–17, 19 living standard 20 wealth 18–19, 76 informal care 111 Index 135 inheritance tax 58 in-kind services 111 insecurity 21–3, 29, 38, 39, 47, 67, 85, 106 Institute for Fiscal Studies (IFS) 10 Institute for Public Policy Research 125 n.17 Institute for Public Policy Research (IPPR) 75, 111 Institute of New Economic Thinking 123 n.15 Institute of Public Policy Research 59 insurance schemes 8 intellectual property 14–15 Intergovernmental Panel on Climate Change (IPCC) 34 International Labour Organization (ILO) 14, 122 n.4 International Monetary Fund (IMF) 31, 34 international tax evasion 18 interpersonal income inequality 83 inter-regional income inequalities 83 intra-family relationships 3 involuntary debt 26 in-work benefits 22 Ireland 35 Italy 18 labour 31, 107 inefficiency 106 law 101 markets 8, 14, 32, 39, 40, 60, 62–3, 96, 100, 106 regulations 13 supply 67, 95 Labour governments 85 labourism 106 Lansley, Stewart 59 Latin America 90 Left Alliance 94 Lenin, Vladimir Ilyich 113 Liberal government 35 life-changing errors 51 life-threatening illness 33 Liverpool 80 living standards 20, 23, 33, 36, 53, 59, 92 Local Housing Allowances 24 London Homelessness Project 92–3 low-income communities 33 low-income families 21 low-income households 17 low-income individuals 86 Low Pay Commission 63 low-wage jobs 60, 107 Luddite reaction 32 lump-sum payments 35, 59, 76 Jackson, Mississippi 99 JobCentrePlus 47 job guarantee policy 101–7 job-matching programs 106 Jobseeker’s Allowance (JSA) 41, 46 Joseph Rowntree Foundation 21 McDonnell, John 129 n.13 McKinsey Global Institute 31 Macron, Emmanuel 35 Magna Carta 1 ‘Making Ends Meet’ 97 ‘mandatory reconsideration’ stage 51 Manitoba 87–8 Manitoba Basic Annual Income Experiment (Mincome) 87 market economy 105, 114 master-servant model 101 Kaletsky, Anatole 123 n.15 Kenya 90–2 Khanna, Ro 103 Kibasi, Tom 113 136 Index Maximus 50 means-testing 4, 39, 42, 48, 58, 61–2, 70, 84, 88, 90, 109–10, 114 benefits 5, 7, 27, 40, 46, 56, 71–3, 81, 129 n.6 social assistance 23, 41, 95, 122 n.7 system 6 medical services 28 Mein Grundeinkommen (‘My Basic Income’) 100 mental health 26, 28, 94 disorders 88 trusts 28 mental illness 33, 68 migrants 7, 113 ‘minimum income floor’ 45 Ministry of Justice 51 modern insecurity 22 modern life 31 monetary policy 59 Mont Pelerin Society 13 moral commitment 75 moral hazard 109 mortality 27, 76 multinational investment funds 34 Musk, Elon 31, 54 Namibia 90–2 National Audit Office (NAO) 24, 43–4, 46, 76 National Health Service (NHS) 8, 24, 27–8, 44, 68, 80, 108, 111 National Insurance 18, 22, 124 n.4 nationalism 37 National Living Wage 63 National Minimum Wage 63–4 national solidarity 3 Native American community 88 negative income tax (NIT) 23, 87, 95, 100 neo-fascism 37–8 neoliberalism 13, 84 Netherlands 96 New Economics Foundation (NEF) 57, 113, 122 n.15 non-resident citizens 113 non-wage benefits 16 non-wage work 74 North America 67 North Ayrshire 80 North Carolina 88 North Sea oil 89–90 Nyman, Rickard 23 Oakland 96–7 Office for National Statistics (ONS) 14–15, 17, 36 Ontario, Canada 95–6 open economy 84 open ‘free’ markets 13, 15 opportunity dividend 59 Organization for Economic Co-operation and Development (OECD) 18, 23, 27, 31 Ormerod, Paul 23 Osborne, George 19 Paine, Thomas 2, 75 Painian Principle 2 panopticon state 55 Paris Agreement (2015) 34 participation income 74–5 paternalism 42, 55 pauperization 63 Pawar, Alderman Ameya 99 pay contributions 21 pension contributions 18, 58 Pension Credit 41 Pericles Condition 75 permanent capital fund 71 personal care services 110–11 Index 137 personal income tax 35 Personal Independence Payment (PIP) 49–51 personal insecurity 23 Personal Savings Allowance 58 personal tax allowances 17, 58, 59 perverse incentives 50 physical health 26, 94 piloting in Britain 67–81 applying 80–1 rules in designing 70–80 policy development 3, 69 political decision 78 political discourse 92 political instability 35 political system 38 populism 37–8, 75 populist parties 37 populist politics 39 Populus survey 55 post-war system 8 poverty 2, 4, 10–12, 22, 27, 29, 36, 38, 40, 60–1, 89, 100, 108–9, 114, 125 n.17, 129 n.6 precarity 29–30, 38, 39, 60–1, 85, 103, 129 n.6 Primary Earnings Threshold 124 n.4 private debt 23–4, 39 private inheritance 2 private insurance 85 private property rights 13 private wealth 18 privatization 13, 17, 112 property prices 76 prostitution 43 Public Accounts Committee (PAC) 51 public costs 28 public debt 23 public inheritance 61 public libraries 47 public policy 97 public sector managers 103 public services 4, 17, 62, 108, 112, 114 public spending 89 public wealth 18 ‘quantitative easing’ policy 59 quasi-basic income 89, 98 quasi-universal basic services 30 quasi-universal dividends 35 quasi-universal system 61, 70, 90 Randomised Control Trial (RCT) 124–5 n.14 rape 44 Ratcliffe, Jim 12 Reagan, Ronald 13 Reed, Howard 59 refugees 7 regressive universalism 57 regular cash payment 7 rent arrears 24 controls 53 rentier capitalism 13–21, 107, 116 n.22 republican freedom 2–3, 30, 84 Republicans 37 Resolution Foundation 10, 15, 19, 25, 76 ‘revenue neutral’ constraint 7 right-wing populism 37–8 robot advance 31–3 Royal College of Physicians 33 Royal Society of Arts 55, 59, 124 n.12 RSA Scotland 125 n.17 Rudd, Amber 9 Russia 113 138 Sanders, Bernie 101 scepticism 31 schooling 67, 89 Scotland 69, 80, 111 Second World War 19, 21 security 8, 38, 55, 68, 84 economic 3, 4, 49, 56 income 73–4 social 8, 22, 49 Self-Employed Women’s Association (SEWA) 68 self-employment 45 Shadow Chancellor of the Exchequer 3, 115 n.3 Smith, Iain Duncan 42 ‘snake oil’ 113 social assistance 3, 28 social benefit 20 social care 102, 104, 110–11 social crisis 106 social dividend scheme 92 Social Fund 29 social inheritance 2 social insecurity 21 social insurance 22, 85 social integration 44 social justice 2, 8, 20, 69, 84, 101, 114 social policy 8, 23, 26, 30, 42, 53, 84–5, 96 social protection system 32 social relation 100 social security 10, 70–1, 95 social solidarity 3, 8, 39, 61, 84–5, 91 social spending 17 social status 104 social strife 35 social value 29 ‘something-for-nothing’ economy 19–20, 61 Index Speenhamland system 63 State of the Global Workplace surveys 105 statutory minimum wages 106 stigma 47, 55 stigmatization 41, 109 Stockton 97–9 Stockton Economic Empowerment Demonstration (SEED) 97 stress 26–9, 39, 51, 67, 68, 85, 93 student loans 24 substitution effects 102–3 suicides 26–7 Summers, Larry 105–6 Sweden 113 Swiss bank Credit Suisse 12 Switzerland 35 tax advantages 49 and benefit systems 17, 18, 69, 110 credits 3, 17, 24, 63, 105, 106 policies 16 rates 72 reliefs 17–18, 57–8, 61 tax-free inheritance 19 technological change 105 technological revolution 14, 31, 114 ‘teething problems’ 42 Thatcher, Margaret 13 Thatcher government 9, 18 The Times 92 Torry, Malcolm 122 n.7 Trades Union Congress 24 tribal casino schemes 76 ‘triple-lock’ policy 16 Trump, Donald 37 Trussell Trust 29, 43 Tubbs, Michael 97–8 Index 139 Turner, Adair 123 n.15 two-child limit 44 UK.

Buying Time: The Delayed Crisis of Democratic Capitalism by Wolfgang Streeck

"there is no alternative" (TINA), "World Economic Forum" Davos, activist fund / activist shareholder / activist investor, air traffic controllers' union, Alan Greenspan, banking crisis, basic income, Bretton Woods, business cycle, capital controls, Carmen Reinhart, central bank independence, collective bargaining, corporate governance, creative destruction, currency risk, David Graeber, deindustrialization, Deng Xiaoping, Eugene Fama: efficient market hypothesis, financial deregulation, financial engineering, financial repression, fixed income, full employment, Garrett Hardin, Gini coefficient, Growth in a Time of Debt, income inequality, Joseph Schumpeter, Kenneth Rogoff, Kickstarter, knowledge economy, labour market flexibility, labour mobility, late capitalism, liberal capitalism, low interest rates, means of production, moral hazard, Myron Scholes, Occupy movement, open borders, open economy, Plutonomy: Buying Luxury, Explaining Global Imbalances, profit maximization, risk tolerance, shareholder value, too big to fail, Tragedy of the Commons, union organizing, winner-take-all economy, Wolfgang Streeck

Shareholder Value, Managerherrschaft und Mitbestimmung in Deutschland, Frankfurt/Main: Campus, 2003. 55 Fig. 1.3 shows the evolution of the Gini coefficient, the most commonly used measure of income inequality, in the seven countries used as examples (see fn. 15 in this chapter). The Gini coefficient measures the deviation of the actual distribution from equal distribution. Another measure of inequality is the share of wages – as opposed to profits – in national income. Here the picture for the sixteen main OECD countries between 1960 and 2005 is as devastating as for the Gini coefficient: ‘Labour’s share increased when capital’s relative bargaining power was threatened by the ascendancy of social democratic projects in the aftermath of World War II. The last two decades have seen a new swing of the pendulum toward a restoration of bargaining power to the capitalist class … Neo-liberalism is … an attempt to restore the capitalist class’s share of income to its pre-World War II levels’ (T.

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While governments hoped that this would bring faster growth and in any case relieve them of political responsibilities, employers invoked the expansion of markets and sharper competition to justify the degrading of wages and work conditions or the widening of wage differentials.53 At the same time, capital markets were transformed into markets for corporate control, which made of ‘shareholder value’ the supreme maxim of good management.54 In many places, even in Scandinavia, citizens were referred to private education and insurance markets as a supplement or even alternative to public providers, with the option of taking up credit to pay the bills. Economic inequality grew everywhere by leaps and bounds (Fig. 1.3).55 In this way and others, responding in more or less the same way to the pressure coming from the owners and managers of their ‘economy’, the developed capitalist countries shed the responsibility they had taken on in mid-century for growth, full employment, social security and social cohesion, handing the welfare of their citizens more than ever over to the market. FIGURE 1.3. Evolution of income inequality: Gini coefficients, seven countries Sources: OECD Database on Household Income Distribution and Poverty, OECD Factbook 2008; Economic, Environmental and Social Statistics 2008; OECD Factbook 2010: Country Indicators, OECD Factbook Statistics In the rich countries of the West, the long turn to neoliberalism encountered remarkably weak resistance.

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., The Age of Dualization: The Changing Face of Inequality in Deindustrializing Countries, Oxford: Oxford University Press, 2012; J. Goldthorpe (ed.), Order and Conflict in Contemporary Capitalism, Oxford: Clarendon Press, 1984; B. Palier and K. Thelen, ‘Institutionalizing Dualism: Complementarities and Change in France and Germany’, Politics and Society, vol. 38/1, 2010, pp. 119–48. 54 See Martin Höpner, Wer beherrscht die Unternehmen? Shareholder Value, Managerherrschaft und Mitbestimmung in Deutschland, Frankfurt/Main: Campus, 2003. 55 Fig. 1.3 shows the evolution of the Gini coefficient, the most commonly used measure of income inequality, in the seven countries used as examples (see fn. 15 in this chapter).

Inequality and the 1% by Danny Dorling

Affordable Care Act / Obamacare, banking crisis, battle of ideas, Bear Stearns, Bernie Madoff, Big bang: deregulation of the City of London, Boris Johnson, Branko Milanovic, buy and hold, call centre, Capital in the Twenty-First Century by Thomas Piketty, centre right, collective bargaining, conceptual framework, corporate governance, credit crunch, David Attenborough, David Graeber, delayed gratification, Dominic Cummings, double helix, Downton Abbey, en.wikipedia.org, Etonian, family office, financial deregulation, full employment, gentrification, Gini coefficient, high net worth, housing crisis, income inequality, land value tax, Leo Hollis, Londongrad, longitudinal study, low skilled workers, lump of labour, mega-rich, Monkeys Reject Unequal Pay, Mont Pelerin Society, mortgage debt, negative equity, Neil Kinnock, Occupy movement, offshore financial centre, plutocrats, precariat, quantitative easing, race to the bottom, Robert Shiller, Russell Brand, TaskRabbit, TED Talk, The Spirit Level, The Wealth of Nations by Adam Smith, trickle-down economics, unpaid internship, very high income, We are the 99%, wealth creators, working poor

He argues this is not an accident, but a function of how the coalition views growth can be achieved.’43 Such carefully worded statements are more than a generation away from Denis Healey’s promise of February 1974 to ‘squeeze property speculators until the pips squeak’ – and Healey was to the right of Labour at the time.44 When you hear of slow progress in the UK and US, it may surprise you to learn that income inequality may not be rising everywhere. Globally, according to the World Bank, inequality has been falling since 2000. In Brazil income inequality peaked in the 1980s. In the US it is currently at a peak, but in Sweden it appears to have been falling again just as it has fallen worldwide (see Figure 6.5).45 Such claims for falling worldwide inequality are, of course, disputed; and measures of inequality that are more sensitive to the 1 per cent taking an ever greater share may not be as forgiving of extreme greed as the Gini coefficient; but inequalities within the middle of the distribution can nonetheless fall.

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Source: Branko Milanovic, 2012 Figure 6.5 Global and selected countries’ income inequality Gini coefficients 1966–2006 Shortly after the release of the 2012 World Bank report suggesting that global income inequality was falling, another organisation published its major findings, stating: ‘Poverty has not declined to the extent claimed and inequity has risen.’46 It may be that, between the mildly rich and the relatively poor, some equalisation is occurring. Whatever the precise global trend is, it remains the case that inequality has risen more in the US and the UK than elsewhere, and that, because other places have had more success in preventing this trend, it is not inevitable that it should continue.

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Fortunately there is a strong correlation between the complex Gini coefficient of income inequality (measured after tax and benefits and adjusting for household size) and the simple measure of how much of total income the best-off 1 per cent receives each year. When the 1 per cent receives a low proportion of national income, inequality for the rest of the population is forced to be lower, because no other group can receive more than the best-off 1 per cent. Simply concentrating on the share taken by the 1 per cent is enough. It may even be one of the best measures of inequality to consider in terms of how simple a target it may be for effective social policy.12 Economists have measured the fortunes of the best-off 1 per cent for decades.

The New Urban Crisis: How Our Cities Are Increasing Inequality, Deepening Segregation, and Failing the Middle Class?and What We Can Do About It by Richard Florida

affirmative action, Airbnb, back-to-the-city movement, basic income, Bernie Sanders, bike sharing, blue-collar work, business climate, Capital in the Twenty-First Century by Thomas Piketty, clean water, Columbine, congestion charging, creative destruction, David Ricardo: comparative advantage, declining real wages, deindustrialization, Donald Trump, East Village, edge city, Edward Glaeser, failed state, Ferguson, Missouri, gentrification, Gini coefficient, Google bus, high net worth, high-speed rail, income inequality, income per capita, industrial cluster, informal economy, Jane Jacobs, jitney, Kitchen Debate, knowledge economy, knowledge worker, land value tax, low skilled workers, Lyft, megacity, megaproject, Menlo Park, mortgage tax deduction, Nate Silver, New Economic Geography, new economy, New Urbanism, occupational segregation, off-the-grid, opioid epidemic / opioid crisis, Paul Graham, plutocrats, RAND corporation, rent control, rent-seeking, restrictive zoning, Richard Florida, rising living standards, Ronald Reagan, secular stagnation, self-driving car, Silicon Valley, SimCity, sovereign wealth fund, streetcar suburb, superstar cities, tech worker, the built environment, The Chicago School, The Death and Life of Great American Cities, the High Line, The Rise and Fall of American Growth, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, Thorstein Veblen, trickle-down economics, Tyler Cowen, Uber and Lyft, uber lyft, universal basic income, upwardly mobile, urban decay, urban planning, urban renewal, urban sprawl, white flight, young professional

In New York City, for example, the 1 percent hauls in more than forty times the average income of the bottom 99 percent; in Los Angeles, San Francisco, and San Jose, they make about thirty times as much.8 The overall level of income inequality in the United States as a whole is bad enough—it is 0.450 on the Gini coefficient index, the standard for measuring income inequality. (Gini coefficient values range from 0 to 1, with 0 indicating zero inequality and 1 indicating the most extreme inequality.) The US value is about the same as Iran’s, and worse than Russia’s, India’s, or Nicaragua’s. But within many US cities and metro areas, the Gini coefficient is even worse, rivaling some of the most unequal countries on earth. New York City’s inequality is similar to that of Swaziland. Los Angeles’s matches up with Sri Lanka’s.

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The data for the three major classes are from the US Department of Labor, Bureau of Labor Statistics (BLS), 2010. Inequality Income inequality: Income inequality is based on the conventional measure of the Gini coefficient and is from the US Census Bureau’s American Community Survey (ACS) for 2010. Wage inequality: This measure concerns the wage gap between creative-, working-, and service-class workers and is calculated based on the Theil index, which is a commonly used metric for measuring wage inequality.1 The data are from the BLS’s information for 2010. Composite Inequality Index: This index combines the above measures of income and wage inequality weighted equally into a single index.

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Data on metro areas, as well as the more recent data on national trends, are from Estelle Sommeiller, Mark Price, and Ellis Wazeter, Income Inequality in the U.S. by State, Metropolitan Area, and County (Washington, DC: Economic Policy Institute, 2016), www.epi.org/publication/income-inequality-in-the-us/#epi-toc-8. 9. The Gini coefficient for nations is from the Central Intelligence Agency, The World Factbook (Washington, DC: US Government Publishing Office, 2015), www.cia.gov/library/publications/the-world-factbook; for metros it is from the US Census Bureau, “American Community Survey,” www.census.gov/programs-surveys/acs. 10. On the worsening trend in inequality across metros, see Richard Florida, “Where the Great Recession Made Inequality Worse,” CityLab, August 4, 2014, www.citylab.com/politics/2014/08/where-the-great-recession-made-inequality-worse/375480/T; US Conference of Mayors, U.S.

Hit Refresh: The Quest to Rediscover Microsoft's Soul and Imagine a Better Future for Everyone by Satya Nadella, Greg Shaw, Jill Tracie Nichols

3D printing, AlphaGo, Amazon Web Services, anti-globalists, artificial general intelligence, augmented reality, autonomous vehicles, basic income, Bretton Woods, business process, cashless society, charter city, cloud computing, complexity theory, computer age, computer vision, corporate social responsibility, crowdsourcing, data science, DeepMind, Deng Xiaoping, Donald Trump, Douglas Engelbart, driverless car, Edward Snowden, Elon Musk, en.wikipedia.org, equal pay for equal work, everywhere but in the productivity statistics, fault tolerance, fulfillment center, Gini coefficient, global supply chain, Google Glasses, Grace Hopper, growth hacking, hype cycle, industrial robot, Internet of things, Jeff Bezos, job automation, John Markoff, John von Neumann, knowledge worker, late capitalism, Mars Rover, Minecraft, Mother of all demos, Neal Stephenson, NP-complete, Oculus Rift, pattern recognition, place-making, Richard Feynman, Robert Gordon, Robert Solow, Ronald Reagan, Salesforce, Second Machine Age, self-driving car, side project, Silicon Valley, Skype, Snapchat, Snow Crash, special economic zone, speech recognition, Stephen Hawking, Steve Ballmer, Steve Jobs, subscription business, TED Talk, telepresence, telerobotics, The Rise and Fall of American Growth, The Soul of a New Machine, Tim Cook: Apple, trade liberalization, two-sided market, universal basic income, Wall-E, Watson beat the top human players on Jeopardy!, young professional, zero-sum game

But when only 1 percent earn $1 million while everyone else earns nothing, we’re approaching absolute inequality. Gini’s work provides a way of measuring the degree to which the income distribution in a given society approaches or diverges from perfect equality. The Gini coefficient for a particular population is generally expressed as a fraction. Perfect equality would be represented by a value of zero, while maximum inequality would be represented by a value of one. In the real world, the Gini coefficient for any given country or region is expressed by a fraction somewhere in between those two extremes. The Gini coefficient for an advanced European country like Germany has hovered around .3 for decades, while the figure for the United States has risen for years, now matching that of China and Mexico at over .4.

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And yet I see this mindset everywhere—in the Middle East, Asia, Africa, Latin America, and even in struggling communities in G20 nations like the United States. The resulting failure of governments to encourage rapid and intensive use of new technologies means that the trend toward growing economic inequality between the haves and the have-nots of the world has continued unabated. To get a measure of how equitable or inequitable our world is, economists turn to the work of an Italian economist named Corrado Gini who in 1912 published his formula for calculating what has become known as the Gini coefficient, which measures the difference between a society’s division of income and a perfectly equal division of income. It’s really quite elegant. If 100 percent of a given population were to earn $1 per day, that would be absolute equality.

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., 177 Carroll, Pete, 4 Case, Anne, 236 Cavium Networks, 20 CD-ROM, 28 CEO as curator of culture, 100, 241 “disease,” 92 panoramic view of, 118 cerebral palsy, 8–10 Chang, Emily, 129 charter city, 229 Cheng, Lili, 197 chess, 198–99 Chik, Joy, 58 child exploitation, 190 Chile, 223, 230 China, 86, 195, 220, 222, 229, 232, 236 chip design, 25 CIA, 169 Cisco, 174 civil liberties, 172–73 civil rights, 24 civil society, 179 Civil War, 188 clarity, 119 Clayton, Steve, 155 client/server era, 45 climate change, 142, 214 Clinton, Hillary, 230 cloud, 13, 41–47, 49, 51–62, 68, 70, 73, 81, 88, 110, 125, 129, 131, 137, 140, 150, 164, 166, 172, 180–81, 186, 189–92, 216, 219, 223–25, 228 cloud-first mission and, 57–58, 70, 76, 79, 83 public, 42–43, 57 Cloud for Global Good, 240–41 Codapalooza, 104 cognition, 89, 150, 152–53 Cohen, Leonard, 10 collaboration, 88, 102–3, 106–8, 126, 135, 163–64, 166, 200 collaborative robots (co-bots), 204 collective IQ, 142, 143 Colombia, 78 Columbia University, 165 Comin, Diego, 216–17, 226 commitment, shared, 77, 119 Common (hip hop artist), 71 Common Objects in Context challenge, 151 communication, 76–77 Compaq, 29 comparative advantage, 222, 228 competition, internal, 52 competitive zeal, 38–39, 70–71, 102 competitors, 39 partnerships and, 78, 125–38 complexity, 25, 224 computers early, 21–22, 24–26 future platforms, 110–11 programs by, 153–54 computing power, massive, 150–51 Conard, Edward, 220 concepts, 122–23, 141 consistency, 77–78, 182 Constitution Today, The (Amar), 186–87 constraints, 119 construction companies, 153 consumers, 49–50, 222 context, shared, 56–57 Continental Congress, 185 Continuum, 73 Convent of Jesus and Mary (India), 19 Cook, Tim, 177 cook stoves, 43 coolness, 75–76 core business, 142 Cortana, 125, 152, 156–58, 195, 201 Couchbase company, 58 counterintuitive strategy, 56–57 Coupland, Douglas, 74 Courtois, Jean-Philippe, 82 courts, 184–85 Covington and Burling lawyers, 3 Cranium games, 7 creativity, 58, 101, 119, 201, 207, 242 credit rating, 43, 204–5 Creed (film), 44–45 cricket, 18–22, 31, 35–40, 115 Cross-country Historical Adoption of Technology (CHAT), 217 culture bias and, 205 “live site first,” 61 three Cs and, 122–23, 141 transforming, 2, 11, 16, 40, 76–78, 81–82, 84, 90–92, 98–103, 105, 108–10, 113–18, 120, 122–23, 241–42 Culture (Eagleton), 91 Curiosity (Mars rover), 144 customer needs, 42, 59, 73, 80, 83, 88, 99, 101–2, 108, 126, 138 customization, 151 cybersecurity, 171, 190 cyberworld, rules for, 184 data, 60, 151 data analytics, 50 databases, 26 Data General company, 68 data management, 54 data platform, 59 data security, 175–76, 188–89 Deaton, Angus, 236 Deep Blue, 198–99 deep neural networks, 153 Delbene, Kurt, 3, 81–82 Delhi, India, 19, 31, 37 Dell, 63, 87, 127, 129–30 Dell, Michael, 129 democracy, 180 democratization, 4, 13, 69, 127, 148, 151–52 Deng Xiaoping, 229 Depardieu, Gerard, 33 design, 50, 69, 141, 239 desktop software, 27 Detroit, 15, 225, 233 developed economies, 99–100 share of world income, 236 developing economies, 99–100, 217, 225 device management solutions, 58 digital assistants, 142, 156–58, 195–98, 201 digital cable, 28 digital evidence, 191–92 Digital Geneva Convention, 171–72 digital ink, 142 digital literacy, 226–27 digital publishing laws, 185 digital transformation, 70, 126–27, 132, 235 dignity, 205 disabilities, 103, 200 disaster relief, 44 Disney, 150 disruption, 13 distributed systems, 49 diversity, 101–2, 108, 111–17, 205–6, 238, 241 Donne, John, 57 drones, 209, 226 Drucker, Peter, 90 dual users, 79 Dubai, 214, 228 Duke University, 3 Dupzyk, Kevin, 147 D-Wave, 160 Dweck, Carol, 92 dynamic learning, 100 Dynamics, 121 Dynamics 365, 152 dyslexia, 44, 103–4 Eagleton, Terry, 91 earthquakes, 44 EA Sports, 127 economic growth, 211–34 economic inequality, 12, 207–8, 214, 219–21, 225, 227, 236–41 Edge browser, 104 education, 42–44, 78, 97, 104, 106–7, 142, 145, 206–7, 224, 226–28, 234, 236–38 Egypt, 218–19, 223, 225 E-health companies, 222–23 8080 microprocessor, 21 elasticity, 49 electrical engineering (EE), 21–22 elevator and escalator business, 60 Elop, Stephen, 64, 72 email, 27, 169–73, 176 EMC, 129 emotion, 89, 197, 201 emotional intelligence (EQ), 158, 198 empathy, 6–12, 16, 40, 42–43, 93, 101, 133–34, 149, 157, 182, 197, 201, 204, 206, 226, 239, 241 employee resource groups (ERGs), 116–17 employees, 66–68, 75, 138 diversity and, 101, 111–17 empowerment and, 79–80, 126 global summit of, 86–87 hackathon, 10–11 talent development and, 117–18 empowerment, 87–88, 98–99, 106, 108–10, 126 encryption, 161–62, 175, 192–93 energy, generating across company, 119 energy costs, 237 Engelbart, Doug, 142 Engelbart’s Law, 142–43 engineers, 108–9 Enlightiks, 222–23 Enterprise Business, 81 entertainment industry, 126 ethics, 195-210, 239 Europe, 193 Excel, 121 experimental physicists, 162–64 eye-gaze tracking, 10 Facebook, 15, 44, 51, 125, 144, 174, 200, 222 failures, overcoming, 92, 111 Fairfax Financial Holdings, 20 fairness, 236 Federal Bureau of Investigation (FBI), 170, 177–78, 189 Federal Communications Commission (FCC), 28 fear of unknown, 110–11 feedback loop, 53 fertilizer, 164 Feynman, Richard, 160 fiefdoms, 52 field-programmable gate arrays (FPGAs), 161 Fields Medal, 162 firefighters, 43, 56 First Amendment, 185, 190 Flash, 136 focus, 135–36, 138 Foley, Mary Jo, 52 Ford Motor Company, 64 foreign direct investment, 219, 225, 229 Foreign Intelligence Surveillance Act (FISA), 173 Fourth Amendment, 185–88, 190, 193 France, 223, 236 Franco, James, 169 Franklin, Benjamin, 186 Freedman, Michael, 162, 166 free speech, 170–72, 175, 179, 185, 190, 238 Fukushima nuclear plant, 44 G20 nations, 219 Galaxy Explorer, 148 game theory, 123–24 Gandhi, Mohandas Mahatma, 16 Gartner Inc., 145 Gates, Bill, 4, 12, 21, 28, 64, 46, 67–69, 73–75, 87, 91, 127, 146, 183, 203 Gavasker, Sunil, 36 GE, 3, 126–27, 237 Gelernter, David, 143, 183 Geneva Convention, Fourth (1949), 171 Georgia Pacific, 29 Germany, 220, 223, 227–36 Gervais, Michael, 4–5 Gini, Corrado, 219 Gini coefficient, 219–21 GLEAM, 117 Gleason, Steve, 10–11 global competitiveness, 78–79, 100–102, 215 global information, policy and, 191 globalization, 222, 227, 235–37 global maxima, 221–22 goals, 90, 136 Goethe, J.W. von, 155 Go (game), 199 Goldman Sachs, 3 Google, 26, 45, 70–72, 76, 127, 160, 173–74, 200 partnership with, 125, 130–32 Google DeepMind, 199 Google Glass, 145 Gordon, Robert, 234 Gosling, James, 26 government, 138, 160 cybersecurity and, 171–79 economic growth and, 12, 223–24, 226–28 policy and, 189–92, 223–28 surveillance and, 173–76, 181 Grace Hopper, 111–14 graph coloring, 25 graphical user interfaces (GUI), 26–27 graphics-processing unit (GPU), 161 Great Convergence, the (Baldwin), 236 Great Recession (2008), 46, 212 Greece, 43 Green Card (film), 33 Guardians of Peace, 169 Gutenberg Bible, 152 Guthrie, Scott, 3, 58, 60, 82, 171 H1B visa, 32–33 habeas corpus, 188 Haber, Fritz, 165 Haber process, 165 hackathon, 103–5 hackers, 169–70, 177, 189, 193 Hacknado, 104 Halo, 156 Hamaker, Jon, 157 haptics, 148 Harvard Business Review, 118 Harvard College, 3 Harvey Mudd College, 112 Hawking, Stephen, 13 Hazelwood, Charles, 180 head-mounted computers, 144–45 healthcare, 41–42, 44, 142, 155–56, 159, 164, 198, 218, 223, 225, 237 Healthcare.gov website, 3, 81, 238 Heckerman, David, 158 Hewlett Packard, 63, 87, 127, 129 hierarchy, 101 Himalayas, 19 Hindus, 19 HIV/AIDS, 159, 164 Hobijn, Bart, 217 Hoffman, Reid, 232, 233 Hogan, Kathleen, 3, 80–82, 84 Holder, Eric, 173–74 Hollywood, 159 HoloLens, 69, 89, 125, 144–49, 236 home improvement, 149 Hong Kong, 229 Hood, Amy (CFO), 3, 5, 82, 90 Horvitz, Eric, 154, 208 hospitals, 42, 78, 145, 153, 223 Hosseini, Professor, 23 Huang, Xuedong, 151 human capital, 223, 226 humanistic approach, 204 human language recognition, 150–51, 154–55 human performance, augmented by technology, 142–43, 201 human rights, 186 Hussain, Mumtaz, 36, 37 hybrid computing, 89 Hyderabad, 19, 36–37, 92 Hyderabad Public School (HPS), 19–20, 22, 37–38, 136 hyper-scale, cloud-first services, 50 hypertext, 142 IBM, 1, 160, 174, 198 IBM Watson, 199–200 ideas, 16, 42 Illustrator, 136 image processing, 24 images, moving, 109 Imagine Cup competition, 149 Immelt, Jeff, 237 Immigration and Naturalization Act (1965), 24, 32–33 import taxes, 216 inclusiveness, 101–2, 108, 111, 113–17, 202, 206, 238 independent software vendor (ISV), 26 India, 6, 12, 17–22, 35–37, 170, 186–87, 222–23, 236 immigration from, 22–26, 32–33, 114–15 independence and, 16–17, 24 Indian Administrative Service (IAS), 16–17, 31 Indian Constitution, 187 Indian Institutes of Technology (IIT), 21, 24 Indian Premier League, 36 IndiaStack, 222–23 indigenous peoples, 78 Indonesia, 223, 225 industrial policy, 222 Industrial Revolution, 215 Fourth or future, 12, 239 information platforms, 206 information technology, 191 Infosys, 222 infrastructure, 88–89, 152–53, 213 innovation, 1–2, 40, 56, 58, 68, 76, 102, 111, 120, 123, 142, 212, 214, 220, 224, 234 innovator’s dilemma, 141–42 insurance industry, 60 Intel, 21, 45, 160, 161 intellectual property, 230 intelligence, 13, 88–89, 126, 150, 154–55, 160, 169, 173, 239 intelligence communities, 173 intensity of use, 217, 219, 221, 224–26 International Congress of the International Mathematical Union, 162 Internet, 28, 30, 48, 79, 97–98, 222 access and, 225–26, 240 security and privacy and, 172–73 Internet Explorer, 127 Internet of Things (IoT), 79, 134, 142, 228 Internet Tidal Wave, 203 Intersé, 3 Interview, The (film), 169–71 intimidation, 38 investment strategy, 90, 142 iOS devices, 59, 72, 123, 132 iPad, 70, 141 iPad Pro, 123–25 iPhone, 70, 72, 85, 121–22, 125, 177–79 Irish data center, 176, 184 Islamic State (ISIS), 177 Istanbul, 214 Jaisimha, M.L., 18, 36–37 Japan, 44, 223, 230 Japanese-American internment, 188 JAVA, 26 Jeopardy (TV show), 199 Jha, Rajesh, 82 jobs, 214, 231, 239–40.

Seasteading: How Floating Nations Will Restore the Environment, Enrich the Poor, Cure the Sick, and Liberate Humanity From Politicians by Joe Quirk, Patri Friedman

3D printing, access to a mobile phone, addicted to oil, Affordable Care Act / Obamacare, agricultural Revolution, Albert Einstein, barriers to entry, biodiversity loss, Biosphere 2, Branko Milanovic, British Empire, Buckminster Fuller, Burning Man, business climate, business cycle, business process, California gold rush, Celtic Tiger, Charles Lindbergh, clean water, Colonization of Mars, Dean Kamen, Deng Xiaoping, drone strike, Elon Musk, en.wikipedia.org, export processing zone, failed state, financial intermediation, Garrett Hardin, Gini coefficient, Great Leap Forward, happiness index / gross national happiness, income inequality, intentional community, Intergovernmental Panel on Climate Change (IPCC), joint-stock company, joint-stock limited liability company, Kickstarter, low skilled workers, Machinery of Freedom by David Friedman, Mark Zuckerberg, megacity, megaproject, minimum wage unemployment, Neil Armstrong, Network effects, new economy, obamacare, ocean acidification, off-the-grid, offshore financial centre, One Laptop per Child (OLPC), open borders, Patri Friedman, paypal mafia, peak oil, Peter H. Diamandis: Planetary Resources, Peter Thiel, price stability, profit motive, radical decentralization, Ronald Coase, Ronald Reagan, Shenzhen special economic zone , Shenzhen was a fishing village, Silicon Valley, special economic zone, standardized shipping container, stem cell, TechCrunch disrupt, TED Talk, trade route, Tragedy of the Commons, UNCLOS, UNCLOS, undersea cable, young professional

Now imagine if Mauritius were mobile. Raise All Boats Let’s defy another economic stereotype. Income inequality is measured by the Gini coefficient. If your Gini coefficient is 0, every resident owns the same amount. If your Gini coefficient is 1, one resident owns everything, and everybody else owns nothing. In many cases, extremely speedy growth in developing nations corresponds to extremely inequitable income distribution. It’s such a consistent pattern, some economists consider it akin to an economic law. For instance, Hong Kong’s Gini coefficient reached 0.50 in 2011, well above the 0.40 level used by analysts to measure the potential for social unrest—and, indeed, labor strikes in Hong Kong have been increasing.

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For instance, Hong Kong’s Gini coefficient reached 0.50 in 2011, well above the 0.40 level used by analysts to measure the potential for social unrest—and, indeed, labor strikes in Hong Kong have been increasing. Mauritius utterly defies this pattern. At the same time that the nation experienced stellar growth, its income inequality, as measured by the Gini coefficient, fell from 45.7 in 1980 to 38.9 in 2006. Richer and more equal? Mauritius is a new political experiment that educates nations on the other side of the Earth. Consider this 2010 report from Dr. Satish Chand, adjunct professor of economics at the Australian National University’s College of Asia and the Pacific, who visited Mauritius to research lessons that could be applied to the island nation of Fiji: The sugarcane fields, the mountains in the backdrop, the greenery, and the people look deceptively similar to Fiji . . .

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See also World Bank, African Development Bank, and Mauritius Board of Investment 2009. “Investment Climate Assessment: Mauritius 2009.” World Bank, Washington, DC, http://siteresources.worldbank.org/MAURITIUSEXTN/Resources/ica-mauritius-0110.pdf. At the same time that the nation experienced stellar growth, its income inequality, as measured by the Gini coefficient, fell from 45.7 in 1980 to 38.9 in 2006: Vandemoortele and Bird, “Progress in Economic Conditions in Mauritius,” 10. “The sugarcane fields, the mountains in the backdrop”: Satish Chand, Pacific Could Learn From Prosperous Mauritius, Pacific Islands Report, October 19, 2010, http://archives.pireport.org/archive/2010/October/10-20-ft.htm.

The Myth of Capitalism: Monopolies and the Death of Competition by Jonathan Tepper

"Friedman doctrine" OR "shareholder theory", Affordable Care Act / Obamacare, air freight, Airbnb, airline deregulation, Alan Greenspan, bank run, barriers to entry, Berlin Wall, Bernie Sanders, Big Tech, big-box store, Bob Noyce, Boston Dynamics, business cycle, Capital in the Twenty-First Century by Thomas Piketty, citizen journalism, Clayton Christensen, collapse of Lehman Brothers, collective bargaining, compensation consultant, computer age, Cornelius Vanderbilt, corporate raider, creative destruction, Credit Default Swap, crony capitalism, diversification, don't be evil, Donald Trump, Double Irish / Dutch Sandwich, Dunbar number, Edward Snowden, Elon Musk, en.wikipedia.org, eurozone crisis, Fairchild Semiconductor, Fall of the Berlin Wall, family office, financial innovation, full employment, gentrification, German hyperinflation, gig economy, Gini coefficient, Goldman Sachs: Vampire Squid, Google bus, Google Chrome, Gordon Gekko, Herbert Marcuse, income inequality, independent contractor, index fund, Innovator's Dilemma, intangible asset, invisible hand, Jeff Bezos, Jeremy Corbyn, Jevons paradox, John Nash: game theory, John von Neumann, Joseph Schumpeter, junk bonds, Kenneth Rogoff, late capitalism, London Interbank Offered Rate, low skilled workers, Mark Zuckerberg, Martin Wolf, Maslow's hierarchy, means of production, merger arbitrage, Metcalfe's law, multi-sided market, mutually assured destruction, Nash equilibrium, Network effects, new economy, Northern Rock, offshore financial centre, opioid epidemic / opioid crisis, passive investing, patent troll, Peter Thiel, plutocrats, prediction markets, prisoner's dilemma, proprietary trading, race to the bottom, rent-seeking, road to serfdom, Robert Bork, Ronald Reagan, Sam Peltzman, secular stagnation, shareholder value, Sheryl Sandberg, Silicon Valley, Silicon Valley billionaire, Skype, Snapchat, Social Responsibility of Business Is to Increase Its Profits, SoftBank, Steve Jobs, stock buybacks, tech billionaire, The Chicago School, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, too big to fail, undersea cable, Vanguard fund, vertical integration, very high income, wikimedia commons, William Shockley: the traitorous eight, you are the product, zero-sum game

Table of Contents Cover Introduction Chapter One: Where Buffett and Silicon Valley Billionaires Agree Key Thoughts from the Chapter Chapter Two: Dividing Up the Turf Key Thoughts from the Chapter Chapter Three: What Monopolies and King Kong Have in Common Lower Wages and Greater Income Inequality Higher Prices Fewer Startups and Jobs Lower Productivity Lower Investment Localism and Diversity Key Thoughts from the Chapter Chapter Four: Squeezing the Worker Key Thoughts from the Chapter Chapter Five: Silicon Valley Throws Some Shade Key Thoughts from the Chapter Chapter Six: Toll Roads and Robber Barons Monopolies (and Local Monopolies) Duopolies Oligopolies Key Thoughts from the Chapter Chapter Seven: What Trusts and Nazis Had in Common Key Thoughts from the Chapter Chapter Eight: Regulation and Chemotherapy Key Thoughts from the Chapter Chapter Nine: Morganizing America Key Thoughts from the Chapter Chapter Ten: The Missing Piece of the Puzzle Key Thoughts from the Chapter Conclusion: Economic and Political Freedom Principles for Reform Solutions and Remedies And Finally, What You Can Do … Notes Introduction Chapter 1: Where Buffett and Silicon Valley Billionaires Agree Chapter 2: Dividing Up the Turf Chapter 3: What Monopolies and King Kong Have in Common Chapter 4: Squeezing the Worker Chapter 5: Silicon Valley Throws Some Shade Chapter 6: Toll Roads and Robber Barons Chapter 7: What Trusts and Nazis Had in Common Chapter 8: Regulation and Chemotherapy Chapter 9: Morganizing America Chapter 10: The Missing Piece of the Puzzle Conclusion: Economic and Political Freedom Acknowledgments About the Authors Index End User License Agreement List of Tables Chapter 2 Table 2.1 The Largest Highly Concentrated Industries List of Illustrations Chapter 1 Figure 1.1 Merger Manias: 1890–2015 Figure 1.2 Collapse in the Number of US Public Companies Since 1996 Figure 1.3 Collapse in Initial Public Offerings (IPOs) Figure 1.4 Frequency of the Words “Competition,” “Competitors,” and “Pressure” in Annual Reports Chapter 2 Figure 2.1 Zero and Negative Central Bank Rates Promote Cartels Chapter 3 Figure 3.1 The US Economy Has Become Less Entrepreneurial over Time Figure 3.2 New Firms Play a Decreasing Role in the Economy Figure 3.3 Growth Phases of Organisms and Companies Figure 3.4 Lower Productivity Growth as Fewer Firms Enter Figure 3.5 Investment Significantly Lagging Profitability Chapter 4 Figure 4.1 Variant Perception US Wages Leading Indicator Figure 4.2 Percentage of Workers with Noncompete Agreements, by Group Figure 4.3 States That Do Not Enforce Noncompetes Have Higher Wages Figure 4.4 Rural Areas Are Lagging (aggregate wage growth, year-over-year, third quarter 2016) Figure 4.5 Monopsonies in Labor Markets: Commuting Zones with High Labor Concentration Figure 4.6 Maslow's Hierarchy of Needs Figure 4.7 Union Membership versus Income Distribution to Top 10% Figure 4.8 Wage Growth Closely Associated with Strikes Figure 4.9 The Great Suppression: Falling Unions and Increasing Licensing, 1950s–Today Chapter 6 Figure 6.1 Rail Mergers: Making of the Big Four Figure 6.2 Airline Mergers in Today's Oligopoly Figure 6.3 Banking Mergers in the United States Figure 6.4 Life Expectancy versus Health Expenditure over Time (1970–2014) Figure 6.5 Leading Global Meat Processing Firms Timeline of Ownership Changes, 1996–2016 Chapter 7 Figure 7.1 The First and Second Merger Waves (1890–1903, 1920–1930) Figure 7.2 Antitrust Enforcement Budget Figure 7.3 Twenty Years of Industry Consolidation Figure 7.4 Three Mega Merger Waves in the Past Three Decades Figure 7.5 Proportion of Completed Mergers and Acquisitions Chapter 8 Figure 8.1 Total US Patents Issued Annually, 1900–2014 Figure 8.2 Pages in the Federal Register (1936–2015) Figure 8.3 Companies That Lobby Extensively Have Higher Returns Figure 8.4 Revolving Door between Goldman Sachs and the Federal Government Figure 8.5 Revolving Door between Monsanto and the Federal Government Chapter 9 Figure 9.1 Largest Owners of US Banks (as of 2016 Q2) Figure 9.2 Share of Passively Managed Assets in US Markets Figure 9.3 S&P 500 Ownership by “Big 3” Figure 9.4 Net Investment by Nonfinancial Businesses Figure 9.5 Buybacks Zoom to Record Highs Chapter 10 Figure 10.1 Income Inequality in the United States, 1910–2015 Figure 10.2 The Global Wealth Pyramid, 2017 Figure 10.3 Rising Inequality. Selected Gini Coefficients Figure 10.4 Rising CEO-to-Worker Compensation Ratio, 1965–2014 Figure 10.5 Worker Pay Is Not Keeping Up with Worker Productivity Figure 10.6 Corporate Profits versus Employee Compensation Figure 10.7 Income Inequality in the United States versus Antitrust Enforcement Figure 10.8 Higher Markups Lead to Lower Wages Figure 10.9 Markups in Advanced Economies Have Been Rising since the 1980s Figure 10.10 US Net Wealth Shares: Top 0.1% versus Bottom 90% “I think the book is too hard on some companies and CEOs.

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It would have been more efficient if central banks had simply wired money directly to the bank accounts of the very wealthy. While wealth inequality is interesting, the standard way economists look at income disparities is by looking at something called a Gini coefficient. This measure shows the variation between the actual distribution of income in a country and what would apply if it were distributed perfectly evenly. It ranges from zero, indicating perfect equality, to a value of one, indicating perfect inequality with one household receiving all income. Globally, we have seen a steadily rising trend in inequality in emerging market countries, in the United States, the UK, and Australia.

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Globally, we have seen a steadily rising trend in inequality in emerging market countries, in the United States, the UK, and Australia. Europe has seen a smaller rise in income inequality, primarily due to high taxes and transfer payments to poorer households.7 Higher taxes mitigate the symptoms but do not solve the problem (Figure 10.3).8 Figure 10.3 Rising Inequality. Selected Gini Coefficients SOURCE: http://www.presidency.ucsb.edu/economic_reports/2016.pdf. SOURCE: Dr. Shane Oliver and AMP Capital.9 It is not surprising that the United States has seen a big increase in inequality over the past 30 years. The extremes in income distribution are most clearly reflected in extraordinary CEO pay. In the US CEO pay has exploded.

Bourgeois Dignity: Why Economics Can't Explain the Modern World by Deirdre N. McCloskey

"Friedman doctrine" OR "shareholder theory", Airbnb, Akira Okazaki, antiwork, behavioural economics, big-box store, Black Swan, book scanning, British Empire, business cycle, buy low sell high, Capital in the Twenty-First Century by Thomas Piketty, classic study, clean water, Columbian Exchange, conceptual framework, correlation does not imply causation, Costa Concordia, creative destruction, critique of consumerism, crony capitalism, dark matter, Dava Sobel, David Graeber, David Ricardo: comparative advantage, deindustrialization, demographic transition, Deng Xiaoping, do well by doing good, Donald Trump, double entry bookkeeping, electricity market, en.wikipedia.org, epigenetics, Erik Brynjolfsson, experimental economics, Ferguson, Missouri, food desert, Ford Model T, fundamental attribution error, Garrett Hardin, Georg Cantor, George Akerlof, George Gilder, germ theory of disease, Gini coefficient, God and Mammon, Great Leap Forward, greed is good, Gunnar Myrdal, Hans Rosling, Henry Ford's grandson gave labor union leader Walter Reuther a tour of the company’s new, automated factory…, Hernando de Soto, immigration reform, income inequality, interchangeable parts, invention of agriculture, invention of writing, invisible hand, Isaac Newton, Islamic Golden Age, James Watt: steam engine, Jane Jacobs, John Harrison: Longitude, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kenneth Arrow, knowledge economy, labor-force participation, lake wobegon effect, land reform, liberation theology, lone genius, Lyft, Mahatma Gandhi, Mark Zuckerberg, market fundamentalism, means of production, middle-income trap, military-industrial complex, Naomi Klein, new economy, Nick Bostrom, North Sea oil, Occupy movement, open economy, out of africa, Pareto efficiency, Paul Samuelson, Pax Mongolica, Peace of Westphalia, peak oil, Peter Singer: altruism, Philip Mirowski, Pier Paolo Pasolini, pink-collar, plutocrats, positional goods, profit maximization, profit motive, public intellectual, purchasing power parity, race to the bottom, refrigerator car, rent control, rent-seeking, Republic of Letters, road to serfdom, Robert Gordon, Robert Shiller, Ronald Coase, Scientific racism, Scramble for Africa, Second Machine Age, secular stagnation, seminal paper, Simon Kuznets, Social Responsibility of Business Is to Increase Its Profits, spinning jenny, stakhanovite, Steve Jobs, tacit knowledge, TED Talk, the Cathedral and the Bazaar, The Chicago School, The Market for Lemons, the rule of 72, The Spirit Level, The Wealth of Nations by Adam Smith, Thomas Malthus, Thorstein Veblen, total factor productivity, Toyota Production System, Tragedy of the Commons, transaction costs, transatlantic slave trade, Tyler Cowen, Tyler Cowen: Great Stagnation, uber lyft, union organizing, very high income, wage slave, Washington Consensus, working poor, Yogi Berra

The terrible heat wave in Chicago of July 1995 killed over seven hundred people, mainly low-income.23 Yet earlier heat waves in 1936 and 1948, before air conditioning was at all common, had probably killed many more.24 The 2003 heat wave in non–air conditioned France killed 14,800 people, and 70,000 Europe-wide. Imagine what the London heat wave in June 1858 did. 6 Inequality Is Not the Problem Robert Reich argues that the problem must be measured by inequality, Gini-coefficient style, not by the absolute condition of the poor. “Widening inequality,” he declares, “challenges the nation’s core ideal of equal opportunity”: Widening inequality still hampers upward mobility. That’s simply because the ladder is far longer now. The distance between its bottom and top rungs, and between every rung along the way, is far greater.

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Their chart 2 exhibits weekly income distributions in 1886 prices at 1886, 1906, 1938, and 1960, showing the disappearance of the inflation-adjusted classic line of misery for British workers, “’round about a pound a week.”8 Yet the left works overtime, out of the best of motives, to rescue its ethically irrelevant focus on Gini coefficients and the relative poverty line. A recent example of the leftish labor is the book by a French economist I have mentioned, Thomas Piketty’s Capital in the Twenty-First Century (translated 2014), which was greeted with squeals of delight by the American and British left, and rapidly rose to number one on the New York Times best-seller list. Piketty claims that relative poverty is what matters, whether or not the poorest improve. “Just as we’ve been saying!” the left cried. “Eliminate poverty and inequality.” Much of the research on the economics of inequality stumbles on this simple ethical point, focusing on measures of relative inequality such as the Gini coefficient rather than on measures of the absolute welfare of the poor, on inequality rather than poverty, having elided the two.

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Much of the research on the economics of inequality stumbles on this simple ethical point, focusing on measures of relative inequality such as the Gini coefficient rather than on measures of the absolute welfare of the poor, on inequality rather than poverty, having elided the two. Speaking of the legal philosopher Ronald Dworkin’s egalitarianism, Frankfurt observed that Dworkin in fact, and ethically, “cares principally about the [absolute] value of people’s lives, but he mistakenly represents himself as caring principally about the relative magnitudes of their economic assets.”9 Dworkin and the left commonly miss the ethical point, which is the liberal, Joshua Monk one of lifting up the poor.

A Fine Mess by T. R. Reid

accelerated depreciation, Affordable Care Act / Obamacare, Alan Greenspan, Bernie Sanders, Capital in the Twenty-First Century by Thomas Piketty, carbon tax, carried interest, centre right, clean water, Donald Trump, Double Irish / Dutch Sandwich, game design, Gini coefficient, High speed trading, Home mortgage interest deduction, Honoré de Balzac, income inequality, industrial robot, land value tax, loss aversion, mortgage tax deduction, obamacare, Occupy movement, offshore financial centre, oil shock, plutocrats, race to the bottom, Ronald Reagan, seigniorage, Silicon Valley, Skype, Snapchat, sovereign wealth fund, Tax Reform Act of 1986, Tesla Model S, The Wealth of Nations by Adam Smith, Tim Cook: Apple, Tobin tax, We are the 99%, WikiLeaks

But the top earners have seen big increases in income since 2000; as of 2015, the top 1% of American families had income of $405,000. To make the top one-tenth of 1% took income of $1.9 million. Using the standard international measure of inequality, President Obama was basically correct when he said that among the advanced democracies the imbalance is “most pronounced” in the United States. The customary gauge of economic inequality is called the Gini coefficient, named for the Italian economist who thought it up. In the Gini rankings, a nation where everybody had the same amount of wealth and the same income would get a Gini score of 0; a country where one person took in all the income, and nobody else earned a cent, would get a score of 1.

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Generally, the world’s poor countries—where a few families control the wealth, and tens of millions live in squalor—have high Gini coefficients. Nations like Lesotho, Botswana, Honduras, and Haiti have Gini numbers near 0.6, making them the least economically equal societies on the planet. Among the rich countries, the democracies of western Europe tend to score around 0.3; the world champions at economic equality include Sweden, Denmark, and Norway, where high wages for working people and high taxes on the rich bring the Gini index down to about 0.25. The United States had a Gini coefficient in 2014 of 0.4—the worst rating among rich countries. Among the thirty-four members of the OECD, the club of industrialized democracies, only Mexico and Chile ranked higher than the United States on the inequality scale.

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The First Republic, in its zeal for new terminology, replaced the standard word for “tax” (impôt) with the French word contribution, and to this day French politicians routinely talk about taxes as “social contributions,” as a way to maintain the essential French ideal of égalité. “For most of the French left, and a chunk of the right, high taxes are a hallmark of a decent society that puts fairness before profit and public service before business,” the Economist noted. In terms of égalité, at least, this tax regime seems to have worked; France has always had a lower Gini coefficient (that is, a more even distribution of wealth) than most of its European neighbors or the United States. When the Great Recession hit France in 2008, Nicolas Sarkozy, a center-right politician, was president. (Sarkozy supports free higher education, a complete ban on handguns, and unemployment compensation that never ends, but in European terms that makes him “center-right.”)

Economic Dignity by Gene Sperling

active measures, Affordable Care Act / Obamacare, antiwork, autism spectrum disorder, autonomous vehicles, basic income, behavioural economics, benefit corporation, Bernie Sanders, Big Tech, Cass Sunstein, collective bargaining, company town, corporate governance, cotton gin, David Brooks, desegregation, Detroit bankruptcy, disinformation, Donald Trump, Double Irish / Dutch Sandwich, driverless car, Elon Musk, employer provided health coverage, Erik Brynjolfsson, Ferguson, Missouri, fulfillment center, full employment, gender pay gap, ghettoisation, gig economy, Gini coefficient, green new deal, guest worker program, Gunnar Myrdal, housing crisis, Ida Tarbell, income inequality, independent contractor, invisible hand, job automation, job satisfaction, labor-force participation, late fees, liberal world order, longitudinal study, low skilled workers, Lyft, Mark Zuckerberg, market fundamentalism, mass incarceration, mental accounting, meta-analysis, minimum wage unemployment, obamacare, offshore financial centre, open immigration, payday loans, Phillips curve, price discrimination, profit motive, race to the bottom, RAND corporation, randomized controlled trial, Richard Thaler, ride hailing / ride sharing, Ronald Reagan, Rosa Parks, Second Machine Age, secular stagnation, shareholder value, Sheryl Sandberg, Silicon Valley, single-payer health, speech recognition, stock buybacks, subprime mortgage crisis, tech worker, TED Talk, The Chicago School, The Future of Employment, The Wealth of Nations by Adam Smith, Toyota Production System, traffic fines, Triangle Shirtwaist Factory, Uber and Lyft, uber lyft, union organizing, universal basic income, W. E. B. Du Bois, War on Poverty, warehouse robotics, working poor, young professional, zero-sum game

If the number is moving toward 0, it means the nation is experiencing less economic inequality. While there are few economic goals as important as reducing economic inequality, even a measure like reducing the Gini coefficient cannot be seen as an ultimate end goal in itself. For example, imagine if the United States implemented a set of policies that reduced the income of the very richest Americans by 30 percent while reducing the income of everyone else by 20 percent. The Gini coefficient would have gotten better, but no one would likely be celebrating. A version of this actually happened: the World Bank estimates that the United States’ Gini coefficient declined from 2007 to 2010 during the severe economic hardship of the Great Recession.9 The point here is that even a metric that measures something as unobjectionably good as reducing inequality is still not an ultimate end goal in itself, if it is not in the context of serving a larger end goal of lifting up people’s lives and well-being while reducing economic inequality.

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For many years, I bought into the notion that the way to get beyond GDP as the end goal of the economic policy world was simply to push our focus toward other economic metrics that were better proxies for shared growth and shared prosperity. Measures like the Gini coefficient, median income, unemployment rates, and job growth paint a more accurate picture of whether a rising tide is in fact lifting all boats than examining GDP or the value of the stock market. Yet even those metrics are still means to larger economic ends—and have shortcomings when they are considered ends in themselves. Consider the Gini coefficient, which is named after an Italian statistics whiz named Corrado Gini (I promise it is not as complicated as it sounds). The Gini coefficient measures how much inequality there is in an economy, with a measure between 0 and 1.

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See SNAP Ford, Henry, 237 Ford, Martin, 128 Ford Motor Company, 140, 229, 237, 244, 254 for-profit schools, 111–14, 275–76 foster care, 40 Fournier, Ron, 195 Fourteenth Amendment, 17–18 Fox News, 92, 103 franchise workers, 252–55 Frankfurter, Felix, 19, 176 fraud, 43, 85, 187, 335n Frederiksen, Mette, 294 Free Application for Federal Student Aid (FAFSA), 210 “freedom to contract,” 19–20 Freeman, Morgan, 13 free markets, 106–7, 119, 173 Frey, Carl Benedikt, 128, 130 Friedman, John, 278 Friedman, Milton, 119 Frontline, “Rape on the Night Shift,” 79 full-employment policies, 265–68, 281 Funke, Manuel, 295 Furman, Jason, 115, 128, 183–84, 247 gainful employment regulations, 113–14 Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP), 289 Gascón, George, 59 Gates, Bill, 7, 150 Gaye, Marvin, 41 GDP (gross domestic product), xv, xix, 3, 4–6 gender wage gap, 245, 275 General Electric, 119, 137 Geneva Convention, 17 Genghis Khan, 116 Gephardt, Dick, 123 Gerard, Leo, 251 Germany caregiving credits, 162 works councils, 250 Germino, Laura, 256 Geronimus, Arline, 61 Getting Back to Full Employment (Baker and Bernstein), 267 gig economy, 9–10, 63–64, 191–92, 230–33, 251–52 Gillard, Julia, 131 Gillibrand, Kirsten, 34–35 Gilmer v. Interstate/Johnson Lane Corp., 260 Gini, Corrado, 6–7 Gini coefficient, 6–7 Ginsburg, Ruth Bader, 20, 248, 260 Glenn-Leistikow, Sarah, 215 globalization, 139–41, 145–46, 247 GM (General Motors), 140, 231, 237, 253–54 Godoey, Anna, 178 Goldin, Claudia, 270, 273 Gompers, Samuel, 15, 82, 308–9n Goodwin, Doris Kearns, 21 Google, 230, 259–60 Google Play, 117 Gore, Al, 145 government regulations, 106–11 government role, 89–105 automation and AI, 146–50 compact of contribution vs. punitive test, 90–94 economic dignity compact, 137 during economic downturns, 137–39 encouraging risk-taking and entrepreneurship, 97–98 era of big government responsibility, 101–5 health care economics, 99–101 innovation and, 98–99 jobs and globalization, 139–41 lack of intensive government investment, 94–96 in providing meaningful work, 229–33, 234–36 public options and guarantee of economic dignity, 104–5 role in economic change, 136–50 “second-chance” policies, 141–46 graduation rates, 275–76, 312n Graham, Carol, 60 Granholm, Jennifer, 137–38 Great Chicago Fire of 1871, 67 Great Depression, xiii, 20 Great Gatsby Curve, 42 Great Recession, xiii, 7, 191, 201, 213, 266–67, 270, 273 Great Society, 25–26, 190 Greenhouse, Steven, 256 Green New Deal, 141, 220 Groundwork of the Metaphysics of Morals (Kant), 14, 15, 136 Gruber, Jonathan, 98–99, 100, 138 Guendelsberger, Emily, 236–37 Gurrola, Alejandra, 216 H-1B visas, 262–63 H-2A visas, 261–62 Hacker, Jacob, 176, 274 Hackman, Richard, 226–27 Halpern-Meekin, Sarah, 180 Hamermesh, Daniel S., 52 Hamilton (musical), 127 Hamilton, Alexander, 16 Hamilton, Darrick, 15, 104 Hanauer, Nick, 193, 273–74 Hand, Learned, 251–52 Hansen, Bradley, 49 Harris, Alexes, 56 Harris, Kamala, 184 “Harry Potter divide,” 287–88 Head Start, 350n health care policy, xiii–xiv, xv–xvi, 99–101, 102–3 conservatives and, 99–101, 166–67 government’s role, 99–101 preexisting conditions, 97, 100, 101, 103, 166–67, 356 universal health care security, xiii–xiv, xv–xvi, 35, 40, 100–101, 102–3, 168, 200, 236 “health coaches,” 147 health insurance.

Currency Wars: The Making of the Next Gobal Crisis by James Rickards

"World Economic Forum" Davos, Alan Greenspan, Asian financial crisis, bank run, Bear Stearns, behavioural economics, Benoit Mandelbrot, Berlin Wall, Big bang: deregulation of the City of London, Black Swan, borderless world, Bretton Woods, BRICs, British Empire, business climate, buy and hold, capital controls, Carmen Reinhart, Cass Sunstein, collateralized debt obligation, complexity theory, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, cross-border payments, currency manipulation / currency intervention, currency peg, currency risk, Daniel Kahneman / Amos Tversky, deal flow, Deng Xiaoping, diversification, diversified portfolio, Dr. Strangelove, Fall of the Berlin Wall, family office, financial innovation, floating exchange rates, full employment, game design, German hyperinflation, Gini coefficient, global rebalancing, global reserve currency, Great Leap Forward, guns versus butter model, high net worth, income inequality, interest rate derivative, it's over 9,000, John Meriwether, Kenneth Rogoff, laissez-faire capitalism, liquidity trap, Long Term Capital Management, low interest rates, mandelbrot fractal, margin call, market bubble, Mexican peso crisis / tequila crisis, Money creation, money market fund, money: store of value / unit of account / medium of exchange, Myron Scholes, Network effects, New Journalism, Nixon shock, Nixon triggered the end of the Bretton Woods system, offshore financial centre, oil shock, one-China policy, open economy, paradox of thrift, Paul Samuelson, power law, price mechanism, price stability, private sector deleveraging, proprietary trading, quantitative easing, race to the bottom, RAND corporation, rent-seeking, reserve currency, Ronald Reagan, short squeeze, sovereign wealth fund, special drawing rights, special economic zone, subprime mortgage crisis, The Myth of the Rational Market, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, time value of money, too big to fail, value at risk, vertical integration, War on Poverty, Washington Consensus, zero-sum game

One of the best measures of the rent seeking relationship between elites and citizens in a stagnant economy is the Gini coefficient, a measure of income inequality; a higher coefficient means greater income inequality. In 2006, shortly before the recent recession began, the coefficient for the United States reached an all-time high of 47, which contrasts sharply with the all-time low of 38.6, recorded in 1968 after two decades of stable gold-backed money. The Gini coefficient trended lower in 2007 but was near the all-time high again by 2009 and trending higher. The Gini coefficient for the United States is now approaching that of Mexico, which is a classic oligarchic society characterized by gross income inequality and concentration of wealth in elite hands.

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The Gini coefficient for the United States is now approaching that of Mexico, which is a classic oligarchic society characterized by gross income inequality and concentration of wealth in elite hands. Another measure of elite rent seeking is the ratio of amounts earned by the top 20 percent of Americans compared to amounts earned by those living below the poverty line. This ratio went from a low of 7.7 to 1 in 1968 to a high of 14.5 to 1 in 2010. These trends in both the Gini coefficient and the wealth-to-poverty income ratio in the United States are consistent with Tainter’s findings on civilizations nearing collapse. When society offers its masses negative returns on inputs, those masses opt out of society, which is ultimately destabilizing for masses and elites.

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Gates, Robert Gazprom Geithner, Timothy General Agreement on Tariffs and Trade (GATT) General Electric (GE) General Motors (GM) Genoa Conference of 1922 Germany bilateral trade relations with China currency collapse in 1920s and European sovereign debt crisis of 2010 and G20 gold reserves and gold standard and panic of 1931 reichsmark rentenmark rise of Nazi party support for euro trade deficits during 1980s and U.S. in London Gold Pool Weimar hyperinflation and World War I reparations Gertz, Bill Gini coefficient global corporations globalization gold and Bretton Woods system China’s 2009 five hundred metric tons of gold transfer classical gold standard of 1870 to 1914 as currency anchor FDR’s gold confiscations flaws in 1920s gold exchange standard flexible gold standard France and desire to return to gold standard Genoa Conference and return to gold standard gold clauses in contracts gold SDR gold standard during war time gold standard, return to and Great Depression international gold reserves London Gold Pool 1930s deflation and U.S. gold devaluation under Nixon’s New Economic Policy and Panic of 1931 vs. paper money prices during U.S. recessions, 1970s to 1980s pure gold standard stocks and two-tier system, creation of U.S. and dollar-gold parity U.S. gold reserves gold bullion and coins gold mining Gold Reserve Act of 1934 Gold Standard Acts of 1900 and 1925 Goldman Sachs Gramm, Phil Great Depression beggar-thy-neighbor devaluations during Federal Reserve role during France and gold as contributing factor to impact on U.S. economy Greece Greenspan, Alan gross domestic product (GDP) in China four components of growth in major currencies and monetarism and changes in U.S. consumer and growth of in U.S. during Kennedy-Johnson years U.S. economy and 2011 Group of Eight (G8) Group of Seven (G7) Group of Ten (G10) Group of Twenty (G20) Brazil and and Panic of 2008 and SDRs 2008 Summit on Financial Markets and the World Economy 2009 Pittsburgh G20 summit 2011 Cannes, France G20 summit U.S. rebalancing plan and Group of Two (G2) Gutfreund, John Halliwell, Steve Hamilton, Alexander hedge funds Hemingway, Ernest Herodotus heuristics, in economics Hitler, Adolf Hoover, Herbert Hu Jintao Hua Guofeng Hughes, Charles Evans Humphrey-Hawkins Full Employment Act of 1978 hyperinflation import surtax India Indonesia inflation caused by U.S.

India's Long Road by Vijay Joshi

Affordable Care Act / Obamacare, barriers to entry, Basel III, basic income, blue-collar work, book value, Bretton Woods, business climate, capital controls, carbon tax, central bank independence, clean water, collapse of Lehman Brothers, collective bargaining, colonial rule, congestion charging, Cornelius Vanderbilt, corporate governance, creative destruction, crony capitalism, decarbonisation, deindustrialization, demographic dividend, demographic transition, Doha Development Round, eurozone crisis, facts on the ground, failed state, financial intermediation, financial repression, first-past-the-post, floating exchange rates, foreign exchange controls, full employment, germ theory of disease, Gini coefficient, global supply chain, global value chain, hiring and firing, income inequality, Indoor air pollution, Induced demand, inflation targeting, invisible hand, land reform, low interest rates, Mahatma Gandhi, manufacturing employment, Martin Wolf, means of production, microcredit, moral hazard, obamacare, Pareto efficiency, price elasticity of demand, price mechanism, price stability, principal–agent problem, profit maximization, profit motive, purchasing power parity, quantitative easing, race to the bottom, randomized controlled trial, rent-seeking, reserve currency, rising living standards, school choice, school vouchers, secular stagnation, Silicon Valley, smart cities, South China Sea, special drawing rights, The Future of Employment, The Market for Lemons, too big to fail, total factor productivity, trade liberalization, Tragedy of the Commons, transaction costs, universal basic income, urban sprawl, vertical integration, working-age population

For various reasons, including severe under-​reporting of and by the rich, measured consumption inequality systematically underestimates true income inequality. Some attempts have been made to measure inequality of incomes in India directly. These turn up with calculated Gini coefficients above 50 per cent, which puts India in the same ball-​park as high-​inequality Latin American countries like Brazil.22 Measures of interpersonal inequality of consumption are good enough to indicate what is happening to the trend of inequality. On this measure, from the early 1960s to the early 1990s, inequality in India was roughly flat, with a broadly stable Gini coefficient in the low thirties.23 But in the last two decades there has been a rise: the all-​India Gini coefficient has gone up by about six percentage points from 1993 to 2011, from around 30 to 36 per cent (see Table 2.4).24 This is mostly due to a rise in intra-​urban inequality, and the urban-​rural income differential; intra-​rural inequality has not increased by much.25 Other pieces of evidence are also suggestive of rising inequality, particularly in urban areas.

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n.a. 31.3 (RG: 30.1; UG: 34.1) 36.0 45.3 (320 million) (404 million) 27.5 37.2 (302 million) (407 million) n.a. 32.1 (RG: 30.9; UG: 34.7) (323 million) 1993/​94 29.2 (RG: 28.5; UG: 30.8) (329 million) 1983 31.5 (RG: 30.3; UG: 35.3) (321 million) 1977/​78 35.0 (RG: 33.7; UG: 38.2) (262 million) 1973/​74 Inequality: Gini Coefficient (%) n.a. 30.7 (RG: 28.5; UG: 34.4) n.a. 34.7 (RG: 28.1; UG: 36.4) 21.9 29.5 35.9 (269 million) (363 million) (RG:28.7; UG:37.7) Notes: In the “Headcount Poverty Ratio” part of the table, the figures in brackets show the absolute number of poor people in millions. In the “Inequality: Gini Coefficient” part of the Table, RG means Rural Gini and UG means Urban Gini. Sources: Poverty, 1950s and 1960s: Datt (1997); poverty, 1973/​74 to 2011/​12 (except Rangarajan poverty in 2011/​12): Planning Commission (2014a) and Planning Commission (2014c); poverty, 2011/​ 12 (Rangarajan definition): Planning Commission (2014a); inequality, 1950s to 1993/​94: Datt (1997); inequality, 2004/​5 and 2011/​12: Himanshu (2015). 1 9 4 7 –​2 0 1 6 : A T O U R D ’ H O R I Z O N [ 21 ] 22 PARTIAL REFORM SINCE 1980: THE POLITICAL BACKDROP Congress (I) and Mrs.

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On this measure, from the early 1960s to the early 1990s, inequality in India was roughly flat, with a broadly stable Gini coefficient in the low thirties.23 But in the last two decades there has been a rise: the all-​India Gini coefficient has gone up by about six percentage points from 1993 to 2011, from around 30 to 36 per cent (see Table 2.4).24 This is mostly due to a rise in intra-​urban inequality, and the urban-​rural income differential; intra-​rural inequality has not increased by much.25 Other pieces of evidence are also suggestive of rising inequality, particularly in urban areas. Firstly, in the last decade, National Sample Survey data show that a) per capita urban consumption increased twice as fast as per capita rural consumption and b) within the urban sector, per capita consumption in the top decile has risen much faster than in other deciles.

The Growth Delusion: Wealth, Poverty, and the Well-Being of Nations by David Pilling

Airbnb, Alan Greenspan, banking crisis, Bernie Sanders, Big bang: deregulation of the City of London, Branko Milanovic, call centre, carbon tax, centre right, clean tech, clean water, collapse of Lehman Brothers, collateralized debt obligation, commoditize, Credit Default Swap, credit default swaps / collateralized debt obligations, dark matter, Deng Xiaoping, Diane Coyle, Donald Trump, double entry bookkeeping, Easter island, Erik Brynjolfsson, falling living standards, financial deregulation, financial engineering, financial intermediation, financial repression, Gini coefficient, Glass-Steagall Act, Goldman Sachs: Vampire Squid, Google Hangouts, Great Leap Forward, Hans Rosling, happiness index / gross national happiness, Higgs boson, high-speed rail, income inequality, income per capita, informal economy, invisible hand, Jeremy Corbyn, job satisfaction, Mahatma Gandhi, Mahbub ul Haq, market fundamentalism, Martin Wolf, means of production, military-industrial complex, Monkeys Reject Unequal Pay, mortgage debt, off grid, old-boy network, Panopticon Jeremy Bentham, peak oil, performance metric, pez dispenser, profit motive, purchasing power parity, race to the bottom, rent-seeking, Robert Gordon, Ronald Reagan, Rory Sutherland, science of happiness, shareholder value, sharing economy, Simon Kuznets, sovereign wealth fund, TED Talk, The Great Moderation, The Wealth of Nations by Adam Smith, Thomas Malthus, total factor productivity, Tragedy of the Commons, transaction costs, transfer pricing, trickle-down economics, urban sprawl, women in the workforce, World Values Survey

One basic measure of inequality is the Gini coefficient, which is often expressed on a scale of 0 to 100.7 Invented by Italian statistician Corrado Gini in 1912, at one end of the scale 0 represents a society of perfect equality in which everyone earns the same; at the other 100 is an economy in which one person earns everything. Relatively equal societies, such as those in Scandinavia, have a Gini coefficient of below 30, with the most unequal society in the world, South Africa, at 63.8 The US has a Gini coefficient of 41, the UK 33, and Germany 30.9 One could perform the same exercise for wealth or assets—which generally reveals greater inequality still. Figure 10 A Real Household Income at Selected Percentiles, 1967–2012 (reported in 2012 dollars).10 Another way is to disaggregate income according to percentiles of the population.

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If averages are skewed in America and Europe because a few people have much more, in Africa it is generally the other way around. Of course there is gross inequality, but, typically, people with jobs support an extended family, from parents, uncles, sisters, brothers, and hangers-on to anyone who can claim even the most tenuous of connections. Ryan recalls an incident when someone walked into his office at the planning ministry complaining that Kenya’s GINI coefficient—which measures inequality—was “disastrous.” “I said, ‘Yes, it’s disastrous, but it doesn’t mean what you think it means,’ ” Ryan recalls. “It so happened that the assistant minister in the planning ministry was an ex-student of mine.

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“But I think there is a rising consensus in the US and other countries that it’s something we need to do.” INEQUALITY Even the notion of median income has its limits. In addition to finding out how the typical person or household is doing, it is right to shine a light on those left behind. There are several ways of doing this. After all, it took clever academic sleuthing to uncover the shocking fact that less-well-educated, middle-aged white Americans have shortening lifespans. One basic measure of inequality is the Gini coefficient, which is often expressed on a scale of 0 to 100.7 Invented by Italian statistician Corrado Gini in 1912, at one end of the scale 0 represents a society of perfect equality in which everyone earns the same; at the other 100 is an economy in which one person earns everything.

Stakeholder Capitalism: A Global Economy That Works for Progress, People and Planet by Klaus Schwab, Peter Vanham

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, 3D printing, additive manufacturing, agricultural Revolution, air traffic controllers' union, Anthropocene, Apple II, Asian financial crisis, Asperger Syndrome, basic income, Berlin Wall, Big Tech, biodiversity loss, bitcoin, Black Lives Matter, blockchain, blue-collar work, Branko Milanovic, Bretton Woods, British Empire, business process, capital controls, Capital in the Twenty-First Century by Thomas Piketty, car-free, carbon footprint, carbon tax, centre right, clean tech, clean water, cloud computing, collateralized debt obligation, collective bargaining, colonial rule, company town, contact tracing, contact tracing app, Cornelius Vanderbilt, coronavirus, corporate governance, corporate social responsibility, COVID-19, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, cuban missile crisis, currency peg, cyber-physical system, decarbonisation, demographic dividend, Deng Xiaoping, Diane Coyle, digital divide, don't be evil, European colonialism, Fall of the Berlin Wall, family office, financial innovation, Francis Fukuyama: the end of history, future of work, gender pay gap, general purpose technology, George Floyd, gig economy, Gini coefficient, global supply chain, global value chain, global village, Google bus, green new deal, Greta Thunberg, high net worth, hiring and firing, housing crisis, income inequality, income per capita, independent contractor, industrial robot, intangible asset, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invisible hand, James Watt: steam engine, Jeff Bezos, job automation, joint-stock company, Joseph Schumpeter, Kenneth Rogoff, Khan Academy, Kickstarter, labor-force participation, lockdown, low interest rates, low skilled workers, Lyft, manufacturing employment, Marc Benioff, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Martin Wolf, means of production, megacity, microplastics / micro fibres, Mikhail Gorbachev, mini-job, mittelstand, move fast and break things, neoliberal agenda, Network effects, new economy, open economy, Peace of Westphalia, Peter Thiel, precariat, Productivity paradox, profit maximization, purchasing power parity, race to the bottom, reserve currency, reshoring, ride hailing / ride sharing, Ronald Reagan, Salesforce, San Francisco homelessness, School Strike for Climate, self-driving car, seminal paper, shareholder value, Shenzhen special economic zone , Shenzhen was a fishing village, Silicon Valley, Simon Kuznets, social distancing, Social Responsibility of Business Is to Increase Its Profits, special economic zone, Steve Jobs, Steve Wozniak, synthetic biology, TaskRabbit, The Chicago School, The Future of Employment, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, the scientific method, TikTok, Tim Cook: Apple, trade route, transfer pricing, Uber and Lyft, uber lyft, union organizing, universal basic income, War on Poverty, We are the 99%, women in the workforce, working poor, working-age population, Yom Kippur War, young professional, zero-sum game

In many people's experience, it matters much more how they fare compared to their fellow citizens than to the rest of the world population. In all but a few countries, national inequality has been rising and often rather fast. The traditional measure of inequality, the Gini coefficient, doesn't do justice to the severity of the problem. The Gini coefficient translates the degree of inequality into a number from 0 (everyone has the same income) to 1 (one person has the entire economy's income). While a higher score over time tells us that inequality has risen, it's difficult to understand what that means in practice. In the US, for example, the Gini coefficient rose from its low point of 0.43 in 1971 to a post-war high of 0.58 today.40 It is an increase, of course, but precisely how good or bad is either number?

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Even among urbanites, some citizens had preferential access to real estate, whereas others did not. Over time, as cities developed and so-called Tier I and Tier II cities skyrocketed, those initial inequalities widened, leading to systemic inequality and a lack of opportunities for many. (Until, Bai noted, around 2010, when the Gini coefficient of China peaked, the labor share of income GDP bottomed out, and the skill premium for educated workers started declining. These were all indicators that income inequality was at its highest level ever, despite improvements in the skills of workers.) The story of unequal access to education, health care, and housing must sound familiar to an American ear as well.

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See Asian Tigers Fourth Industrial Revolution, 18, 45, 68, 71, 116, 122, 125, 142–145, 161–162, 177, 186, 201, 208, 212, 213, 237, 239 The Fourth Industrial Revolution (Schwab), 116 Foxconn (Taiwan), 59 France Compagnie de Suez join stock company of, 103 First Industrial Revolution spreading to, 131 La France Insoumise populist party of, 81 vote for right-wing populist parties (2000, 2017–2019), 84fig Yellow Vests (Gilets Jaunes) protests of, 86–87, 195 Youth for Climate movement (2017), 86 La France Insoumise (France), 81 The Freelance Isn't Free Law (New York), 243 Freelancers Union (New York), 242–243 Freelancing work, 237–238, 240–243 Freund, Caroline, 138 Frey, Carl, 116, 135 Frick Coke Company, 132 Frick, Henry, 132 Fridays for Climate strikes (2018), 149, 250 Friedman, Milton, 14, 136, 175, 205, 209 Friedrichshafen (Germany), 4–5, 6–7, 8–9, 251 Fukuyama, Francis, 15, 112 “The Future of Employment” study (2013), 116 G G7 countries, social compact breaking down in, 110–111 Gama, Vasco da, 97 Garikipati, Supriya, 224 Gates, Bill, 132 Gazivoda, Tin, 195 GDP (gross domestic product) China's increased total debt–to–GDP ratio, 62 COVID crisis impact on public debt and, 19 description and function of, 9, 24 emerging markets (2002–2019), 64–65fig formula for calculating, 24 New Zealand's COVID-19 response and impact on, 222–223 New Zealand's focus on social issues instead of, 234–236 post-World War II low level of, 105 private sector percentage of China's, 172 Simon Kuznets' warning on progress measured by, 21–25, 34, 46, 53 Singapore (1965–2019), 123–125 stakeholder model going beyond profits and, 189–193 trade globalization measured by percentage of, 16 See also GNI (gross national income); GNP (gross national product) GDP growth declining rates since the 1960s, 25–28 differentiating between global, national, and regional, 27–28 singular focus of policymaking on, 25 as “war-time metric,” 25 Gender pay equity, 243 Gender representation advocacy of, 243–244 Ireland's experiment in, 194 as stakeholder model issue, 188–189 General Data Protection Regulation (European Union), 212 General-purpose technologies (GPTs), 143 Generation Z workers, 240 German reunification, 17, 78 Germany Berlin Wall (1961–1989) dividing, 75–77, 88, 89 Christian–Democrats (CDU) political party of, 78, 79 erosion of the political center in, 80–90 extreme views replacing Volksparteien, 80, 83 female-led government leadership during COVID-19 pandemic in, 224 First Industrial Revolution spreading to, 131 following the First World War, 4 growing populism and polarizing politics (2020) in, 79, 87–88 Hartmann machine works (Chemnitz, Kingdom of Saxony), 103fig integration of East and West, 17, 78 lowering debt burden through economic growth, 31 neo-Nazi elements protesting COVID-19 responses, 87 reconstruction of post-war economy and society, 3, 7–11, 251 social reforms (1880s) in, 133 Social–Democrats (SPD) political party of, 78, 80–81 stakeholder concept adopted in, 174 “Stunde Null” (or “Zero Hour”) [May 8, 1945] ending the war, 5 vote for right-wing populist parties (2000, 2017–2019), 84fig well-managed COVID crisis response in, 79 See also East Germany; West Germany Ghana, 27, 70 Gig workers, 187–188, 237–238, 240–243 Gig Workers Rising (California), 241 Gig worker strike (2019), 187 Gig Workers United (California), 241 The Gilded Age: A Tale of Today (Twain and Warner), 133 Gini coefficient of China/India, 37fig–38, 226 Global Competitiveness Index (World Economic Forum), 189, 190 Global debt population pyramid and repayment of, 30 problem of rising, 28–31 what is included in, 28 Global economic growth ASEAN nations, 63–66, 67fig “the Asian Century,” 70–71fig Chinese economy impacting, 63–66, 70–72 declining productivity growth impact on, 33–34 Elephant Curve of Global Inequality and Growth graph, 137–138fig foundations of the post-war, 4–7 India, 66, 67–69 low GDP growth impact on, 25–28 low-interest rates and low inflation impact on, 31–33 post-World War II expansion of the, 3, 7–11, 251 rising debt impact on, 28–31 the tumultuous 1970s and 1980s, 11–15 Global economic order Davos Manifesto (1973) on new direction for, 13–14, 88, 213 impact of income inequality on the, 36–41 impact of the COVID-19 pandemic on the, 108 requirements of a post-COVID world and, 251 SARS–CoV–2 vaccines development and possible “Great Reset” of, 248 understanding the foundations of post-war, 4–7 Global financial crisis (2007–2009), 18, 34, 112–113, 122 Global Footprint Network (GFN), 19, 48fig–49 Global Infrastructure Hub, 32 Globalists, The End of Empire and the Birth of Neoliberalism (Slobodian), 181 Globalization adverse effects of, 107, 110–114 current state of, 108–114 description and implications of, 16 early beginnings and spice routes history of, 99–108 economic decline beginning in 2007, 18–19 GDP measure of trade, 16 New York Times op–ed (Schwab) on, 85 as political ideology, 108 reasons for embracing, 114 success stories from Indonesia, 93–99 three conditions required for positive, 109–110 YouGov–Bertelsmann poll (2018) on, 97 Globalization 4.0, 106–108 Globalization conditions balanced political leadership, 109–110 when functioning as social compact, 109, 110–111 when technology is congruent with economic and societal advantages, 110 Globalization history Age of Discovery (15th to 18th century), 100–102 first wave (19th century–1914), 102–105 globalization 4.0, 106–108 lessons learned from, 108–114 second and third wave (20th century), 105–106 Silk Road and spice routes, 99–102 Global population.

Stakeholder Capitalism: A Global Economy That Works for Progress, People and Planet by Klaus Schwab

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, 3D printing, additive manufacturing, agricultural Revolution, air traffic controllers' union, Anthropocene, Apple II, Asian financial crisis, Asperger Syndrome, basic income, Berlin Wall, Big Tech, biodiversity loss, bitcoin, Black Lives Matter, blockchain, blue-collar work, Branko Milanovic, Bretton Woods, British Empire, business process, capital controls, Capital in the Twenty-First Century by Thomas Piketty, car-free, carbon footprint, carbon tax, centre right, clean tech, clean water, cloud computing, collateralized debt obligation, collective bargaining, colonial rule, company town, contact tracing, contact tracing app, Cornelius Vanderbilt, coronavirus, corporate governance, corporate social responsibility, COVID-19, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, cuban missile crisis, currency peg, cyber-physical system, decarbonisation, demographic dividend, Deng Xiaoping, Diane Coyle, digital divide, don't be evil, European colonialism, Fall of the Berlin Wall, family office, financial innovation, Francis Fukuyama: the end of history, future of work, gender pay gap, general purpose technology, George Floyd, gig economy, Gini coefficient, global supply chain, global value chain, global village, Google bus, green new deal, Greta Thunberg, high net worth, hiring and firing, housing crisis, income inequality, income per capita, independent contractor, industrial robot, intangible asset, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invisible hand, James Watt: steam engine, Jeff Bezos, job automation, joint-stock company, Joseph Schumpeter, Kenneth Rogoff, Khan Academy, Kickstarter, labor-force participation, lockdown, low interest rates, low skilled workers, Lyft, manufacturing employment, Marc Benioff, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Martin Wolf, means of production, megacity, microplastics / micro fibres, Mikhail Gorbachev, mini-job, mittelstand, move fast and break things, neoliberal agenda, Network effects, new economy, open economy, Peace of Westphalia, Peter Thiel, precariat, Productivity paradox, profit maximization, purchasing power parity, race to the bottom, reserve currency, reshoring, ride hailing / ride sharing, Ronald Reagan, Salesforce, San Francisco homelessness, School Strike for Climate, self-driving car, seminal paper, shareholder value, Shenzhen special economic zone , Shenzhen was a fishing village, Silicon Valley, Simon Kuznets, social distancing, Social Responsibility of Business Is to Increase Its Profits, special economic zone, Steve Jobs, Steve Wozniak, synthetic biology, TaskRabbit, The Chicago School, The Future of Employment, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, the scientific method, TikTok, Tim Cook: Apple, trade route, transfer pricing, Uber and Lyft, uber lyft, union organizing, universal basic income, War on Poverty, We are the 99%, women in the workforce, working poor, working-age population, Yom Kippur War, young professional, zero-sum game

In many people's experience, it matters much more how they fare compared to their fellow citizens than to the rest of the world population. In all but a few countries, national inequality has been rising and often rather fast. The traditional measure of inequality, the Gini coefficient, doesn't do justice to the severity of the problem. The Gini coefficient translates the degree of inequality into a number from 0 (everyone has the same income) to 1 (one person has the entire economy's income). While a higher score over time tells us that inequality has risen, it's difficult to understand what that means in practice. In the US, for example, the Gini coefficient rose from its low point of 0.43 in 1971 to a post-war high of 0.58 today.40 It is an increase, of course, but precisely how good or bad is either number?

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Even among urbanites, some citizens had preferential access to real estate, whereas others did not. Over time, as cities developed and so-called Tier I and Tier II cities skyrocketed, those initial inequalities widened, leading to systemic inequality and a lack of opportunities for many. (Until, Bai noted, around 2010, when the Gini coefficient of China peaked, the labor share of income GDP bottomed out, and the skill premium for educated workers started declining. These were all indicators that income inequality was at its highest level ever, despite improvements in the skills of workers.) The story of unequal access to education, health care, and housing must sound familiar to an American ear as well.

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See Asian Tigers Fourth Industrial Revolution, 18, 45, 68, 71, 116, 122, 125, 142–145, 161–162, 177, 186, 201, 208, 212, 213, 237, 239 The Fourth Industrial Revolution (Schwab), 116 Foxconn (Taiwan), 59 France Compagnie de Suez join stock company of, 103 First Industrial Revolution spreading to, 131 La France Insoumise populist party of, 81 vote for right-wing populist parties (2000, 2017–2019), 84fig Yellow Vests (Gilets Jaunes) protests of, 86–87, 195 Youth for Climate movement (2017), 86 La France Insoumise (France), 81 The Freelance Isn't Free Law (New York), 243 Freelancers Union (New York), 242–243 Freelancing work, 237–238, 240–243 Freund, Caroline, 138 Frey, Carl, 116, 135 Frick Coke Company, 132 Frick, Henry, 132 Fridays for Climate strikes (2018), 149, 250 Friedman, Milton, 14, 136, 175, 205, 209 Friedrichshafen (Germany), 4–5, 6–7, 8–9, 251 Fukuyama, Francis, 15, 112 “The Future of Employment” study (2013), 116 G G7 countries, social compact breaking down in, 110–111 Gama, Vasco da, 97 Garikipati, Supriya, 224 Gates, Bill, 132 Gazivoda, Tin, 195 GDP (gross domestic product) China's increased total debt–to–GDP ratio, 62 COVID crisis impact on public debt and, 19 description and function of, 9, 24 emerging markets (2002–2019), 64–65fig formula for calculating, 24 New Zealand's COVID-19 response and impact on, 222–223 New Zealand's focus on social issues instead of, 234–236 post-World War II low level of, 105 private sector percentage of China's, 172 Simon Kuznets' warning on progress measured by, 21–25, 34, 46, 53 Singapore (1965–2019), 123–125 stakeholder model going beyond profits and, 189–193 trade globalization measured by percentage of, 16 See also GNI (gross national income); GNP (gross national product) GDP growth declining rates since the 1960s, 25–28 differentiating between global, national, and regional, 27–28 singular focus of policymaking on, 25 as “war-time metric,” 25 Gender pay equity, 243 Gender representation advocacy of, 243–244 Ireland's experiment in, 194 as stakeholder model issue, 188–189 General Data Protection Regulation (European Union), 212 General-purpose technologies (GPTs), 143 Generation Z workers, 240 German reunification, 17, 78 Germany Berlin Wall (1961–1989) dividing, 75–77, 88, 89 Christian–Democrats (CDU) political party of, 78, 79 erosion of the political center in, 80–90 extreme views replacing Volksparteien, 80, 83 female-led government leadership during COVID-19 pandemic in, 224 First Industrial Revolution spreading to, 131 following the First World War, 4 growing populism and polarizing politics (2020) in, 79, 87–88 Hartmann machine works (Chemnitz, Kingdom of Saxony), 103fig integration of East and West, 17, 78 lowering debt burden through economic growth, 31 neo-Nazi elements protesting COVID-19 responses, 87 reconstruction of post-war economy and society, 3, 7–11, 251 social reforms (1880s) in, 133 Social–Democrats (SPD) political party of, 78, 80–81 stakeholder concept adopted in, 174 “Stunde Null” (or “Zero Hour”) [May 8, 1945] ending the war, 5 vote for right-wing populist parties (2000, 2017–2019), 84fig well-managed COVID crisis response in, 79 See also East Germany; West Germany Ghana, 27, 70 Gig workers, 187–188, 237–238, 240–243 Gig Workers Rising (California), 241 Gig worker strike (2019), 187 Gig Workers United (California), 241 The Gilded Age: A Tale of Today (Twain and Warner), 133 Gini coefficient of China/India, 37fig–38, 226 Global Competitiveness Index (World Economic Forum), 189, 190 Global debt population pyramid and repayment of, 30 problem of rising, 28–31 what is included in, 28 Global economic growth ASEAN nations, 63–66, 67fig “the Asian Century,” 70–71fig Chinese economy impacting, 63–66, 70–72 declining productivity growth impact on, 33–34 Elephant Curve of Global Inequality and Growth graph, 137–138fig foundations of the post-war, 4–7 India, 66, 67–69 low GDP growth impact on, 25–28 low-interest rates and low inflation impact on, 31–33 post-World War II expansion of the, 3, 7–11, 251 rising debt impact on, 28–31 the tumultuous 1970s and 1980s, 11–15 Global economic order Davos Manifesto (1973) on new direction for, 13–14, 88, 213 impact of income inequality on the, 36–41 impact of the COVID-19 pandemic on the, 108 requirements of a post-COVID world and, 251 SARS–CoV–2 vaccines development and possible “Great Reset” of, 248 understanding the foundations of post-war, 4–7 Global financial crisis (2007–2009), 18, 34, 112–113, 122 Global Footprint Network (GFN), 19, 48fig–49 Global Infrastructure Hub, 32 Globalists, The End of Empire and the Birth of Neoliberalism (Slobodian), 181 Globalization adverse effects of, 107, 110–114 current state of, 108–114 description and implications of, 16 early beginnings and spice routes history of, 99–108 economic decline beginning in 2007, 18–19 GDP measure of trade, 16 New York Times op–ed (Schwab) on, 85 as political ideology, 108 reasons for embracing, 114 success stories from Indonesia, 93–99 three conditions required for positive, 109–110 YouGov–Bertelsmann poll (2018) on, 97 Globalization 4.0, 106–108 Globalization conditions balanced political leadership, 109–110 when functioning as social compact, 109, 110–111 when technology is congruent with economic and societal advantages, 110 Globalization history Age of Discovery (15th to 18th century), 100–102 first wave (19th century–1914), 102–105 globalization 4.0, 106–108 lessons learned from, 108–114 second and third wave (20th century), 105–106 Silk Road and spice routes, 99–102 Global population.

The Technology Trap: Capital, Labor, and Power in the Age of Automation by Carl Benedikt Frey

3D printing, AlphaGo, Alvin Toffler, autonomous vehicles, basic income, Bernie Sanders, Branko Milanovic, British Empire, business cycle, business process, call centre, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, Charles Babbage, Clayton Christensen, collective bargaining, computer age, computer vision, Corn Laws, Cornelius Vanderbilt, creative destruction, data science, David Graeber, David Ricardo: comparative advantage, deep learning, DeepMind, deindustrialization, demographic transition, desegregation, deskilling, Donald Trump, driverless car, easy for humans, difficult for computers, Edward Glaeser, Elon Musk, Erik Brynjolfsson, everywhere but in the productivity statistics, factory automation, Fairchild Semiconductor, falling living standards, first square of the chessboard / second half of the chessboard, Ford Model T, Ford paid five dollars a day, Frank Levy and Richard Murnane: The New Division of Labor, full employment, future of work, game design, general purpose technology, Gini coefficient, Great Leap Forward, Hans Moravec, high-speed rail, Hyperloop, income inequality, income per capita, independent contractor, industrial cluster, industrial robot, intangible asset, interchangeable parts, Internet of things, invention of agriculture, invention of movable type, invention of the steam engine, invention of the wheel, Isaac Newton, James Hargreaves, James Watt: steam engine, Jeremy Corbyn, job automation, job satisfaction, job-hopping, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kickstarter, Kiva Systems, knowledge economy, knowledge worker, labor-force participation, labour mobility, Lewis Mumford, Loebner Prize, low skilled workers, machine translation, Malcom McLean invented shipping containers, manufacturing employment, mass immigration, means of production, Menlo Park, minimum wage unemployment, natural language processing, new economy, New Urbanism, Nick Bostrom, Norbert Wiener, nowcasting, oil shock, On the Economy of Machinery and Manufactures, OpenAI, opioid epidemic / opioid crisis, Pareto efficiency, pattern recognition, pink-collar, Productivity paradox, profit maximization, Renaissance Technologies, rent-seeking, rising living standards, Robert Gordon, Robert Solow, robot derives from the Czech word robota Czech, meaning slave, safety bicycle, Second Machine Age, secular stagnation, self-driving car, seminal paper, Silicon Valley, Simon Kuznets, social intelligence, sparse data, speech recognition, spinning jenny, Stephen Hawking, tacit knowledge, The Future of Employment, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thomas Malthus, total factor productivity, trade route, Triangle Shirtwaist Factory, Turing test, union organizing, universal basic income, warehouse automation, washing machines reduced drudgery, wealth creators, women in the workforce, working poor, zero-sum game

Yet to suggest that growing income inequality was entirely due to capital would be misleading. Economists tend to rely on the Gini coefficient to measure levels of inequality across time and space. One of its virtues is that it is straightforward to interpret. If every citizen of a country had the same income, the Gini coefficient would be 0. If one person captured all the income, the income Gini coefficient would be 1. As Lindert and Williamson show, the Gini coefficient for property income was naturally higher, as property ownership is typically more concentrated, but labor income inequality rose even more rapidly: between 1774 and 1870 the property Gini grew from 0.703 to 0.808, while the earnings Gini increased from 0.370 in 1774 to 0.454 in 1860.62 A large part of this can be explained by the displacement of the blue-collar artisan, which led to the hollowing out of middle-income jobs and, thus, greater earnings inequality.63 Moreover, as Kuznets conjectured, inequality rose as a result of American workers shifting from low-income agricultural jobs to high-income manufacturing jobs in the city.

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Because American urbanization accelerated between 1870 and World War I, while the Second Industrial Revolution spun out new industries and raised skill demand, it stands to reason that total inequality should have accelerated as well, all else being equal. It is therefore somewhat surprising that inequality (as measured by the overall Gini coefficient) plateaued around 0.5 and even fell slightly between 1870 and 1929, even though the top 1 percent share rose dramatically from 9.8 percent to 17.8 percent.64 Was the fall in inequality the result of industrialization’s reaching its intermediate stage? While the trajectory of American inequality between the Civil War and World War I does not disprove Kuznets’s hypothesis, it does suggest that there were also other factors at work. The upsurge in private wealth relative to total private incomes between 1870 and 1913 is consistent with the idea that capital played a larger role in shaping American income distribution, leading top incomes to continue to grow.

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The changing face of technology is also reflected in long-run trends in the Gini coefficient (figure 14). As Branko Milanovic has noted, “This revolution [the computer revolution], like the Industrial Revolution of the early nineteenth century, widened income disparities.”41 These periods were not only times when the profit share of income reached historical heights and the wages of ordinary citizens were stagnant. As noted above, both were episodes when technology replaced middle-income workers. In the computer era, the increase in inequality happened in large part because new technologies strongly rewarded more highly skilled symbolic analysts while driving up the capital share of national income.

The Meritocracy Trap: How America's Foundational Myth Feeds Inequality, Dismantles the Middle Class, and Devours the Elite by Daniel Markovits

8-hour work day, activist fund / activist shareholder / activist investor, affirmative action, algorithmic management, Amazon Robotics, Anton Chekhov, asset-backed security, assortative mating, basic income, Bernie Sanders, big-box store, business cycle, capital asset pricing model, Capital in the Twenty-First Century by Thomas Piketty, Carl Icahn, carried interest, collateralized debt obligation, collective bargaining, compensation consultant, computer age, corporate governance, corporate raider, crony capitalism, David Brooks, deskilling, Detroit bankruptcy, disruptive innovation, Donald Trump, Edward Glaeser, Emanuel Derman, equity premium, European colonialism, everywhere but in the productivity statistics, fear of failure, financial engineering, financial innovation, financial intermediation, fixed income, Ford paid five dollars a day, Frederick Winslow Taylor, fulfillment center, full employment, future of work, gender pay gap, gentrification, George Akerlof, Gini coefficient, glass ceiling, Glass-Steagall Act, Greenspan put, helicopter parent, Herbert Marcuse, high net worth, hiring and firing, income inequality, industrial robot, interchangeable parts, invention of agriculture, Jaron Lanier, Jeff Bezos, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, junk bonds, Kevin Roose, Kiva Systems, knowledge economy, knowledge worker, Kodak vs Instagram, labor-force participation, Larry Ellison, longitudinal study, low interest rates, low skilled workers, machine readable, manufacturing employment, Mark Zuckerberg, Martin Wolf, mass incarceration, medical residency, meritocracy, minimum wage unemployment, Myron Scholes, Nate Silver, New Economic Geography, new economy, offshore financial centre, opioid epidemic / opioid crisis, Paul Samuelson, payday loans, plutocrats, Plutonomy: Buying Luxury, Explaining Global Imbalances, precariat, purchasing power parity, rent-seeking, Richard Florida, Robert Gordon, Robert Shiller, Robert Solow, Ronald Reagan, Rutger Bregman, savings glut, school choice, shareholder value, Silicon Valley, Simon Kuznets, six sigma, Skype, stakhanovite, stem cell, Stephen Fry, Steve Jobs, stock buybacks, supply-chain management, telemarketer, The Bell Curve by Richard Herrnstein and Charles Murray, The Theory of the Leisure Class by Thorstein Veblen, Thomas Davenport, Thorstein Veblen, too big to fail, total factor productivity, transaction costs, traveling salesman, universal basic income, unpaid internship, Vanguard fund, War on Poverty, warehouse robotics, Winter of Discontent, women in the workforce, work culture , working poor, Yochai Benkler, young professional, zero-sum game

The line’s slight downward slope overall reveals that the median earner captures a little less income relative to the poor today than at midcentury—that the poor and the middle class are converging. FIGURE 4 U.S. Top-End, Bottom-End, and Full Gini Coefficients over Time (Five-Year Moving Averages) FIGURE 4 shows the Gini coefficients of the United States, calculated in three ways. The upward-sloping dark gray line displays the Gini for the entire U.S. economy. Its steep rise reflects the commonplace sense that inequality has shown a stark increase, from levels that resembled Norway in 1964 to levels that resemble India today. The light gray line is less familiar. It displays the Gini index for the bottom 70 percent of the U.S. income distribution, constructed not by redistributing any income but simply by discarding all income from the top 30 percent of households.

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The top one-tenth of 1 percent earned, on average, 3.5 percent, less than a third of the current share. See Piketty and Saez, “Income Inequality in the United States,” Table A3, https://eml.berkeley.edu//~saez/index.html. between two-thirds and three-quarters: See Chapter 4. toward superordinate labor: See Chapter 4. Canada, Japan, and Norway: See Table 5 of Carola Grün and Stephan Klasen, “Growth, Inequality, and Well-Being: Intertemporal and Global Comparisons,” Discussion Paper no. 95, Ibero-America Institute for Economic Research, Ibero-Amerika Inst. Für Wirtschaftsforschung, Göttingen (2003), 21–23 (listing Gini coefficients for over 150 countries from 1960 to 1998). India, Morocco, Indonesia, Iran, Ukraine, and Vietnam: Recent Gini Index figures for these countries are: the United States, 41.5 (2016); India, 35.1 (2011); Morocco, 39.2 (2006); Indonesia, 39.5 (2013); Iran, 38.8 (2014); Ukraine, 25.0 (2016); Vietnam, 34.8 (2014).

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See World Bank, Development Research Group, “GINI index (World Bank estimate),” World Bank Group, 2018, accessed June 13, 2018, http://databank.worldbank.org/data/reports.aspx?source=2&series=SI.POV.GINI&country=, and http://data.worldbank.org/indicator/SI.POV.GINI. Bangkok, Thailand: The U.S. Census Bureau’s American Community Survey estimates that Fairfield County had a Gini coefficient of 53.52 in 2011. Bangkok’s Gini coefficient that year, as reported by the UN, was 40.0. See U.S. Census Bureau, “2007–2011 American Community Survey,” accessed June 13, 2018, https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml, and United Nations Human Settlements Programme, Urbanization and Development: Emerging Futures, World Cities Report 2016 (2016), accessed June 13, 2018, 206–7, Table C.1, http://wcr.unhabitat.org/wp-content/uploads/2017/02/WCR-2016-Full-Report.pdf.

The Trouble With Billionaires by Linda McQuaig

"World Economic Forum" Davos, battle of ideas, Bear Stearns, Bernie Madoff, Big bang: deregulation of the City of London, British Empire, Build a better mousetrap, carried interest, Charles Babbage, collateralized debt obligation, computer age, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, Douglas Engelbart, Douglas Engelbart, employer provided health coverage, financial deregulation, fixed income, full employment, Gary Kildall, George Akerlof, Gini coefficient, Glass-Steagall Act, income inequality, Intergovernmental Panel on Climate Change (IPCC), invention of the telephone, invention of the wheel, invisible hand, Isaac Newton, Jacquard loom, John Bogle, Joseph-Marie Jacquard, laissez-faire capitalism, land tenure, lateral thinking, low interest rates, Mark Zuckerberg, market bubble, Martin Wolf, mega-rich, minimum wage unemployment, Mont Pelerin Society, Naomi Klein, neoliberal agenda, Northern Rock, offshore financial centre, Paul Samuelson, plutocrats, Ponzi scheme, pre–internet, price mechanism, proprietary trading, purchasing power parity, RAND corporation, rent-seeking, rising living standards, road to serfdom, Robert Solow, Ronald Reagan, The Chicago School, The Spirit Level, The Wealth of Nations by Adam Smith, Tobin tax, too big to fail, trickle-down economics, Vanguard fund, very high income, wealth creators, women in the workforce

Fig. 10 The higher the tax level, the lower the share of income going to the top 1 per cent16 In addition to making market incomes more equal, countries with high tax levels are able to provide more extensive government transfer payments (such as child allowances, pensions and employment benefits) that particularly benefit low- and middle-income families, thereby further reducing inequality in final, disposable incomes. The redistributive effect of the ‘tax-and-transfer’ system can be illustrated with a chart showing inequality, before and after taxes and transfers. To show this, we have used the Gini coefficient as a measure of inequality. The Gini coefficient is a number between 0 and 1, where 0 corresponds with perfect equality (everyone has the same amount of income) and 1 corresponds with perfect inequality (where one person has all the income). Hence, the higher the number (the closer to 1), the greater the degree of inequality. Before taxes, Italy has the greatest degree of inequality, with a Gini of 0.47.

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– distinguish themselves once again with impressive tax-and-transfer systems that substantially reduce inequality. For instance, in Denmark, the tax-and-transfer system reduces the Gini coefficient by more than one-third from 0.37 to only 0.24, leaving Denmark with the most equal distribution of disposable income. Figure 11 ranks countries according to the inequality in the distribution of disposable income, but it also shows the important role of the tax-and-transfer system in achieving the final result of a more equal society. The grey bars represent a country’s Gini after taxes and transfers, with the white bars representing the reduction of inequality in a country’s Gini before taxes and transfers. ‌

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Highest top 1 per cent income data since 2005 are used, except late 1990s data for Germany, the Netherlands and Switzerland due to data availability. Average tax ratio of 1975-2008 based on OECD data. ‌17 Gini coefficients for people aged 18-65 based on OECD data from the late 2000s. ‌18 As an illustration of the importance of taxes and transfers in society, representative average tax ratios and changes in inequality are correlated. The average tax ratio of 1975-2008 explains about 69 percent of the variation of differences between Gini before taxes and transfers and Gini after taxes and transfers calculated based on OECD data from the late 2000s.

Ten Lessons for a Post-Pandemic World by Fareed Zakaria

"there is no alternative" (TINA), 15-minute city, AlphaGo, An Inconvenient Truth, anti-fragile, Asian financial crisis, basic income, Bernie Sanders, Boris Johnson, butterfly effect, Capital in the Twenty-First Century by Thomas Piketty, car-free, carbon tax, central bank independence, clean water, cloud computing, colonial rule, contact tracing, coronavirus, COVID-19, Credit Default Swap, David Graeber, Day of the Dead, deep learning, DeepMind, deglobalization, Demis Hassabis, Deng Xiaoping, digital divide, Dominic Cummings, Donald Trump, Edward Glaeser, Edward Jenner, Elon Musk, Erik Brynjolfsson, failed state, financial engineering, Francis Fukuyama: the end of history, future of work, gentrification, George Floyd, gig economy, Gini coefficient, global pandemic, global reserve currency, global supply chain, green new deal, hiring and firing, housing crisis, imperial preference, income inequality, Indoor air pollution, invention of the wheel, Jane Jacobs, Jeff Bezos, Jeremy Corbyn, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Snow's cholera map, junk bonds, lockdown, Long Term Capital Management, low interest rates, manufacturing employment, Marc Andreessen, Mark Zuckerberg, Martin Wolf, means of production, megacity, Mexican peso crisis / tequila crisis, middle-income trap, Monroe Doctrine, Nate Silver, Nick Bostrom, oil shock, open borders, out of africa, Parag Khanna, Paris climate accords, Peter Thiel, plutocrats, popular capitalism, Productivity paradox, purchasing power parity, remote working, reserve currency, reshoring, restrictive zoning, ride hailing / ride sharing, Ronald Reagan, secular stagnation, Silicon Valley, social distancing, software is eating the world, South China Sea, Steve Bannon, Steve Jobs, Steven Pinker, Suez crisis 1956, TED Talk, the built environment, The Death and Life of Great American Cities, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, The Spirit Level, The Wealth of Nations by Adam Smith, Thomas L Friedman, Tim Cook: Apple, trade route, UNCLOS, universal basic income, urban planning, Washington Consensus, white flight, Works Progress Administration, zoonotic diseases

In Latin America, legendary for its hierarchical societies, over this period, twelve of the sixteen countries studied showed more widely shared prosperity. How to measure inequality is a matter of spirited debate. I have opted for the standard measure, the so-called Gini coefficient, which has been used by the World Bank, the IMF, and most scholars for decades. It is a measure of relative inequality. So if I was earning $100 and you were earning $1,000, and then our incomes both went up by 10%, our relative inequality would be unchanged. But since 10% of $1,000 is a lot more than 10% of $100, in absolute terms, you would have gained more. That is of course also true for countries.

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Viewed that way, the gap has widened dramatically, because these groups have done much better than the rest of society. In other words, there are legitimate ways of looking at inequality that show that it has increased, but using the traditional, historical measure, we can see that after a long unbroken climb upward, global inequality has recently declined. The richest and most successful countries in the world are an exception to this trend; inequality has risen sharply in many of them. That is especially true of the United States, where the Gini coefficient has climbed to its highest level since 1928, when it had soared from years of unchecked capitalism that led to the Great Depression and then the reforms of the New Deal.

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TWO AMERICAS Many scholars have shown that high levels of inequality make for bad economics and politics. It means lower economic growth—fewer people who can spend—and lower levels of trust in each other and in political institutions. As we have seen, historical estimates put American inequality at the highest since the Great Depression—and government studies back this up for more recent decades. The US Census Bureau has collected data on inequality since 1967. America’s Gini coefficient has risen by 22% since then. If we focus on the top 10%, or even worse, the top 1%, the gap has grown even more sharply. These groups have seen their share of national income rise almost everywhere in the world—but among developed nations, nowhere has it spiked more than in America.

The Great Escape: Health, Wealth, and the Origins of Inequality by Angus Deaton

Admiral Zheng, agricultural Revolution, Branko Milanovic, BRICs, British Empire, call centre, carbon tax, clean water, colonial exploitation, Columbian Exchange, compensation consultant, creative destruction, declining real wages, Downton Abbey, Easter island, Edward Jenner, end world poverty, financial engineering, financial innovation, Ford Model T, germ theory of disease, Gini coefficient, Glass-Steagall Act, Great Leap Forward, illegal immigration, income inequality, invention of agriculture, invisible hand, John Snow's cholera map, knowledge economy, Louis Pasteur, low skilled workers, new economy, off-the-grid, Paul Volcker talking about ATMs, purchasing power parity, randomized controlled trial, rent-seeking, rising living standards, Robert Solow, Ronald Reagan, Simon Kuznets, Steve Jobs, Steven Pinker, structural adjustment programs, The Spirit Level, too big to fail, trade route, Tragedy of the Commons, very high income, War on Poverty, zoonotic diseases

The Distribution of Incomes in the United States The evolution of income can be looked at from three different perspectives: growth, poverty, and inequality. Growth is about the average and how it changes, poverty about the bottom, and inequality about how widely incomes are spread across families or people. The spread is often measured by the Gini coefficient, named after Corrado Gini, an Italian economist who worked in the first half of the twentieth century. Gini’s coefficient, or simply the Gini, is a number that lies between 0 (perfect equality—everyone has the same) and 1 (perfect inequality, with one person having everything). It measures how far people are apart on average.

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Even so, taxes have not played a very large part in shaping the changes in inequality since the 1970s, most of which have been driven by pretax income. In the 1980s tax policy widened disparities somewhat, by means of tax reductions that favored the better-off, while in the 1990s the opposite was true, with tax increases at the top and expansions in the Earned Income Tax Credit, which provides benefits at the bottom. Since 2001, tax cuts have once again favored high-income taxpayers. The Congressional Budget Office estimates that, between 1979 and 2007, income inequality (measured by the Gini coefficient, though on a slightly different basis) increased by about a quarter for pretax income and by about a third for after-tax income (including the value of Medicare).

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See also men; women gender roles, 133 Germany: cholera in, 96; foreign aid of, 275; POW camps of, 2–3 germ theory of disease: development of, 10, 96–97; effects of application of, 126, 239, 319; inequalities resulting from, 98, 140; practices based on, 93, 94, 99–100, 133, 239; spread of, 101, 127, 133, 150–51 Ghana: commodity exports of, 286; foreign aid received by, 300–301, 315; incomes in, 284 Gilens, Martin, 212 Gini coefficient, 187–88. See also income inequalities givewell.org, 271 givingwhatwecan.org, 269, 271 Glass-Steagall Act, 211, 213 Global Alliance for Vaccines and Immunisation (GAVI Alliance), 104, 321 Global Fund to Fight AIDS, Tuberculosis and Malaria, 276, 307–8, 309 globalization: economic growth and, 231–32; health effects of, 149–52; impact on wages, 195, 257; impacts on labor, 194–96; inequality as consequence of, 5, 41–42, 195, 257–59, 260; inequality reductions from, 257; in past, 150; politics and, 10–11; of production, 10, 195, 246 global poverty: amounts needed to eliminate, 268–70, 271–73; economic growth and, 233–35, 312; inequalities, 4–5, 41–46, 257–59, 261–63; poverty lines, 220, 223–24, 249, 256; reduction of, 44–46, 45f, 167, 247, 249–51.

The Economics of Enough: How to Run the Economy as if the Future Matters by Diane Coyle

accounting loophole / creative accounting, affirmative action, Alan Greenspan, An Inconvenient Truth, bank run, banking crisis, behavioural economics, Berlin Wall, bonus culture, Branko Milanovic, BRICs, business cycle, call centre, carbon tax, Cass Sunstein, central bank independence, classic study, collapse of Lehman Brothers, conceptual framework, corporate governance, correlation does not imply causation, Credit Default Swap, deindustrialization, demographic transition, Diane Coyle, different worldview, disintermediation, Edward Glaeser, endogenous growth, Eugene Fama: efficient market hypothesis, experimental economics, Fall of the Berlin Wall, Financial Instability Hypothesis, Francis Fukuyama: the end of history, general purpose technology, George Akerlof, Gini coefficient, global supply chain, Gordon Gekko, greed is good, happiness index / gross national happiness, hedonic treadmill, Hyman Minsky, If something cannot go on forever, it will stop - Herbert Stein's Law, illegal immigration, income inequality, income per capita, industrial cluster, information asymmetry, intangible asset, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Jane Jacobs, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, knowledge economy, light touch regulation, low skilled workers, market bubble, market design, market fundamentalism, megacity, Network effects, new economy, night-watchman state, Northern Rock, oil shock, Paradox of Choice, Pareto efficiency, principal–agent problem, profit motive, purchasing power parity, railway mania, rising living standards, Robert Solow, Ronald Reagan, selective serotonin reuptake inhibitor (SSRI), Silicon Valley, social contagion, South Sea Bubble, Steven Pinker, tacit knowledge, The Design of Experiments, The Fortune at the Bottom of the Pyramid, The Market for Lemons, The Myth of the Rational Market, The Spirit Level, the strength of weak ties, Tragedy of the Commons, transaction costs, transfer pricing, tulip mania, ultimatum game, University of East Anglia, vertical integration, web application, web of trust, winner-take-all economy, World Values Survey, zero-sum game

Other European countries are in between these two in the extent of the inequality in incomes and in the recent trend. There are several ways to measure inequality numerically. The most thorough is using a measure such as the Gini coefficient, an index running from zero (fully equal) to one (all the income goes to the top people), which is calculated in a way that takes account of the middle sections of the income distribution. It is therefore a good measure of the kinds of change in income taking place in India and China where, as discussed above, there has been a big increase in incomes in the middle. The Gini coefficient has two drawbacks: the calculations have not been done for all countries and all time periods of interest; and it is not intuitively easy to understand.

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See distribution Inconvenient Truth, An (Gore), 60 Index of Sustainable Economic Welfare (ISEW), 36 India, 212; emerging middle class of, 125; fairness and, 122–26, 133; inequality and, 125–26; nature and, 63, 65, 81; posterity and, 108; purchasing power parity (PPP) and, 306n19; Satyam and, 146; trust and, 146, 149, 163, 172; wage penalties and, 133; World Bank influence and, 163 Industrial Revolution, 27, 149, 290, 297 inequality, 4–5, 11, 17, 84, 306n19, 308n34; Bush and, 127–28; consequences for growth, 135–36; decline in trust and, 139–44; dramatic increase in, 126–27, 131; extraction ratio for, 124; fairness and, 114–16, 122–43; fractal character of, 134; Gini coefficient and, 126; globalization and, 122–24, 127, 131, 155; happiness and, 25, 36, 42, 44, 53; high salaries and, 130, 143–44, 193, 223, 277–78, 286, 296; historical perspective on, 126–27; institutions and, 116, 127–31, 141; measurement of, 126; policy recommendations for, 267, 276, 295–97; poverty and, 43, 55–56, 100, 125, 128, 138, 142, 168–69, 261, 267; reduction of, 276–77; Republican administrations and, 127–28; social corrosiveness of, 139–44; structural causes of, 131–35; superstar effect and, 134; taxes and, 115–16, 123, 127–28, 131, 135–36; trends in, 125–30; unequal countries and, 124–30; United Kingdom and, 125–30; United States and, 122, 125–31, 135, 276; values and, 223–24, 234–36; well-being and, 137–43; within/between countries, 123–24 inflation, 37, 43, 61, 89, 102–5, 110–11, 189, 281, 305n17 information and communication technology (ICT), 6–7, 15, 17; data explosion and, 205, 291; decreased cost of, 254; fairness and, 133; happiness and, 24–25; institutional impacts of, 252–53; structural effects of, 194–98; trust and, 156–60, 165–67, 174 innovation, 6–7, 12; consumer electronics and, 36–37; fairness and, 121, 134; growth and, 271–73, 281, 290–92; happiness and, 37; institutions and, 244, 258, 263, 290–91; measurement and, 183, 196, 201–8, 273–74; musicians and, 195; nature and, 69–70, 81; policy recommendations for, 290–91; posterity and, 102; statistics and, 201–7; trust and, 157; values and, 210, 216, 220, 236 In Praise of Slowness, 27 institutions, 18; anomie and, 48, 51; balance and, 12–17; blindness of to financial crises, 87–88; broad framework for, 249–52; capitalism and, 240; consumption and, 254, 263; decentralization and, 246; democracy and, 242–43, 251–52, 262; downsizing and, 175, 246, 255; economies of scale and, 253–58; efficiency and, 245–46, 254–55, 261; extinction crisis and, 288; face-to-face contact and, 7, 147, 165–68; failures of, 240–44, 257, 262–63, 267, 289–90; fall of communism and, 226, 239–40, 252; freedom and, 244, 262; globalization and, 244; governance and, 242, 247, 255–58, 261–62; government and, 240–63; growth and, 258, 261, 263; health care and, 247, 252–53; high salaries and, 130, 143–44, 193, 223, 277–78, 286, 296; impact of new technologies and, 252–54; importance of, 261–63; inequality and, 116, 127–31, 141; innovation and, 244, 258, 263, 290–91; legitimacy and, 8, 16, 50, 66, 68–69, 162–63, 213, 226, 269, 274, 292, 296–97; managerialism and, 259; morals and, 254; nature and, 66–69, 82–84; New Public Management and, 245–47; outsourcing and, 159, 161, 175, 219, 287; policy recommendations for, 269, 284–91; politics and, 239–48, 251, 256–63; pollution and, 15, 35, 228; productivity and, 244–47, 257, 263; public choice theory and, 242–43; public deliberation and, 258–60; reform and, 245–48, 256, 285, 288–91, 296–97; responsibility to posterity and, 296; shareholders and, 145, 248, 257–58, 277; statistics and, 245; technology and, 244–46, 251–54, 257–63 (see also technology); values and, 240–42, 246–47, 258–60 intangible assets: measurement and, 199–201, 204–6; satellite accounts and, 38, 81, 204–6, 271; social capital and, 149–52, 157, 161, 199–201 InterAcademy Council, 66–67 interbank market, 1–2 Intergovernmental Panel on Climate Change (IPCC), 59, 66–69, 82, 297 International Monetary Fund (IMF), 90, 101–3, 111, 162–64, 176, 211, 287, 297 International Price Comparison, 124 International Telecommunications Union, 219 Internet, 155, 195, 245, 260, 273, 287–89, 291, 296 invisible hand, 209 iPods, 195 Ipsos Mori poll, 66, 247 Ireland, 172 Iron Curtain, 183, 239, 252 Italy, 95, 97–98, 146, 152 Jackson, Michael, 198 Japan, 42; debt of, 102; equal income distribution in, 125; fairness and, 125–26, 140–41; inequality and, 126; lost decade of, 102; posterity and, 91–92, 95, 97–98, 102; savings rates in, 280; trust and, 169, 175; voter turnout and, 175 Jazz Age, 127 Jefferson, Thomas, 184, 253–54 Johns, Helen, 41 Johnson, Simon, 256–57 Johnson, Steven, 187 Justice (Sandel), 237 Kahneman, Daniel, 215 Kamarck, Elaine, 247–48 Kay, John, 139, 245–46, 257 Kennedy School of Government, 247 Keynes, John Maynard, 101, 183–84, 190 Kleinwort, Dresdner, 87 knowledge economy, 191 Kobayashi, Keiichiro, 102 Korea, 126 Krugman, Paul, 100–103, 127–29, 232, 282 Kyoto Protocol, 62–64 labor: absorbing work and, 10, 48–49; call centers and, 131, 133, 161; creativity and, 166–68, 205–7; downsizing and, 175, 246, 255; global cities and, 165–70; globalization and, 131, 149 (see also globalization); human capital and, 81, 203–4, 282; measurement and, 189–99; migration and, 108–10, 172; outsourcing and, 159, 161, 175, 219, 287; pensions and, 4, 25, 85–86, 90, 92–100, 103–7, 111–13, 174–76, 191, 203, 243, 269–71, 275, 280, 286, 289–90, 293; Protestant work ethic and, 13–14, 236; retirement age and, 94, 97–99, 106–7, 112; skilled, 132–33, 159, 166–67, 276; specialization and, 160–61; technology and, 131–33; unemployment and, 3, 10, 43, 51, 56, 89, 107, 169, 207, 212–13, 243; unions and, 15, 51, 224, 249; unskilled, 132–33, 158, 172, 193; well-being and, 137–39; Whitehall Studies and, 139 lack of control, 47, 138–39 Lawson, Neal, 26 Layard, Richard, 31, 39–40, 43 Lehman Brothers, 1, 85, 87–88, 145, 211, 275–76 Leipzig marches, 239 Leviathan (Hobbes), 114 light bulbs, 59–61 Linux, 205 Lipsky, John, 102, 111 List, John, 117 literacy, 36 Live Nation, 197 living standards, 78–79, 106, 113, 136, 151, 162, 190, 194, 267 lobbyists, 15, 71, 247, 257, 276, 285, 289, 296 Lolapaloozza, 197 Louis Vuitton, 150 Luxury Fever (Frank), 40 Mackenzie, Donald, 221 Madonna, 194 Malthusianism, 95 Mama Group, 197 managerial competence, 2, 16, 150, 209, 259 Manzi, Jim, 231–32 Mao Zedong, 10 markets: asymmetric information and, 17, 186, 214, 219–20, 229, 248, 254, 262–63; black, 225; boom–bust cycles and, 4, 22, 28, 93, 102, 106–9, 136–37, 145, 147, 213, 222–23, 233, 277, 280, 283; capitalism and, 182, 230–38 (see also capitalism); culture and, 230–38; declining population and, 86, 89–90, 95–99, 103, 113; democracy and, 230–38; deregulation and, 7, 212; evidence–based policy and, 233–34; exchange advantage and, 214; externalities and, 15, 70, 80, 211, 228–29, 249, 254; failures of, 226–30, 240–44, 257, 262–63, 267, 289–90; Fama hypothesis and, 221–22; flaws of, 215–16; fractal character of, 134; free market model and, 14, 121, 129, 182–83, 210–11, 218–24, 232, 240, 243, 251; fundamentalism for, 213; gift economy and, 205–7; interbank, 1–2; international trade and, 110, 148, 159, 163; invisible hand and, 209; mathematical models of, 214; merits of, 211–17; missing, 229; moral, 210, 213, 220–25, 230–33; music, 194–98; network effects and, 253, 258; options, 222; as organizing economy, 218; performativity and, 224–25; Protestant work ethic and, 13–14, 236; public choice theory and, 220, 242–45; public domain and, 196; rational calculation and, 214–15; satellite accounts and, 81; shorting of, 86; social, 217–20; stability issues and, 2–4, 25, 70, 101, 124, 135, 140–41, 174, 176, 218, 296; trilemma of, 230–38; values and, 209–10 (see also values); winner take all, 134 Marx, Karl, 14, 28, 131, 221 McDonalds, 27 McKitrick, Ross, 68 Mean Fiddler Group, 197 Measuring Australia’s Progress, 274 measurement: asymmetric information and, 17, 186, 214, 219–20, 229, 248, 254, 262–63; Australian model and, 271, 274; balance and, 12–17; bankers and, 193, 200; capitalism and, 182; challenges of, 188–93; consumption and, 181–82, 198; distribution and, 191–99; evidence–based policy and, 233–34; GDP, 10 (see also gross domestic product [GDP]); Gini coefficient and, 126; governance and, 183, 186; government and, 182–88, 191, 193, 196, 202–3, 206; growth and, 181–85, 188–90, 194, 201–5, 208; happiness and, 35–39; health issues and, 181, 188–93, 200, 207; hedonic techniques and, 274; importance of, 184–85, 187–89; of inequality, 126; innovation and, 183, 196, 201–8, 273–74; intangible assets and, 199–201, 204–6; labor and, 189–99; less publication of, 271–72; living standards and, 13, 65, 78–79, 106, 113, 136, 139, 151, 162, 190, 194, 267; Measuring Progress exercise and, 294; policy recommendations for, 270–74; politics and, 182–84, 191, 193, 203, 208; productivity and, 189–90, 194, 199–201, 206–7; resources for, 294; social capital and, 154; statistics and, 187–89, 198–208; technology and, 181–85, 188–91, 194–201, 204–6; time constraints and, 204–7; trust and, 152–57; uncertainty of accuracy and, 273; unmeasurable entities and, 187; values and, 209, 212–13, 224 Medicare, 93–94 Meek, James, 26 metrification, 184 Metropolitan Museum of Art symposium, 100–101 Mexico, 226 Microsoft, 253, 258 migration, 108–10, 172 Milanovic, Branko, 123–24 Mill, John Stuart, 31–32 Minsky, Hyman, 226 monopolies, 196, 245, 252, 254 Montreal Protocol, 59 Moore’s Law, 156 morals: bankers and, 90, 277–78; criticism of poor and, 142; fairness and, 116–20, 127, 131, 142, 144; greed and, 221 (see also greed); growth and, 275–76, 279, 293, 295, 297; happiness and, 22, 26, 30, 34, 43, 48–49; institutions and, 254; nature and, 55, 70–72, 76, 78; performativity and, 224–25; posterity and, 90; trust and, 149, 174; values and, 185, 210, 213, 220–25, 230–33 MP3 players, 195 music, 11, 194–98, 204, 208, 229, 254 nature: Brundtlandt Report and, 77; carbon prices and, 70–71; climate change and, 57–84 (see also climate change); consumption and, 58–61, 71–76, 79, 82; Copenhagen summit and, 62, 64–65, 68, 162, 292; democracy and, 61, 66, 68; efficiency and, 61–62, 69, 82; environmentalists and, 29, 55–59, 69–70, 99; freedom and, 79; future and, 75–83; global warming and, 57, 64, 66, 68; government and, 58–62, 65–71, 82–84; greenhouse gases and, 23, 29, 35, 59, 61–63, 68, 70–71, 83; green lifestyle and, 55, 61, 76, 289, 293; gross domestic product (GDP) and, 56–60, 75–76, 80–82; growth and, 56–59, 62–66, 69–72, 76, 79–82; happiness and, 56–59, 75–76, 80–84; health issues and, 81; hybrid cars and, 61; innovation and, 69–70, 81; institutions and, 66–69, 82–84; InterAcademy Council and, 66–67; Intergovernmental Panel on Climate Change (IPCC) and, 59, 66–69, 82, 297; Kyoto Protocol and, 62–64; light bulbs and, 59–61; Montreal Protocol and, 59; morals and, 55, 70–72, 76, 78; natural capital and, 79–81, 151, 271, 273; philosophy and, 69–70; plastic and, 61; politics and, 57–71, 75, 77, 82–84; population issues and, 99; productivity and, 78, 82; satellite accounts and, 81; self-interest and, 65; squandered natural wealth and, 181–82; statistics and, 66, 81–82; stewardship and, 78, 80; technology and, 69–72, 76–77, 80, 84; TEEB project and, 78–79 network effects, 253, 258 New Deal, 129 New Economics Foundation, 36 New Public Management theory, 245–47 Newton, Isaac, 214–15 Niger, 122 Nobel Prize, 18, 60, 102, 215, 220, 236, 250, 261 noise, 47 No Logo (Wolf), 34 Nordhaus, William, 37, 70, 73, 156 North, Douglass, 261 Northern Rock, 1, 146 Obama, Barack, 62–63, 87, 173, 260, 285, 288 Oberholzer-Gee, Felix, 197 obesity, 137–38, 279 Office for National Statistics, 274 Olson, Mancur, 242 opinion formers, 61 option pricing theory, 222 Orchestra of the Age of Enlightenment, 194 Organization for Economic Cooperation and Development (OECD), 4, 11, 201, 305n11; happiness and, 38, 52; inequality in, 125–26; nature and, 60, 68; policy recommendations for, 273–74, 281, 283, 287, 291, 293; posterity and, 87, 93–94, 97–99, 112; trust and, 160, 171; values and, 212, 243–44, 246 organized crime, 277 Ormerod, Paul, 41 Orwell, George, 56 Ostrom, Elinor, 17, 220, 250–51, 261–63 Pakistan, 81, 226 Paradox of Choice, The (Schwartz), 10–11, 40 Parmalat, 146 partisanship, 2, 16, 101, 128, 269, 285 Peake, Mervyn, 9 pensions, 4, 25, 243; burden of, 92–95; Chinese savings and, 94; measurement and, 191, 203; policy recommendations for, 269–71, 275, 280, 286, 289–90, 293; posterity and, 85–86, 90–100, 103–7, 111–13; retirement age and, 92, 97–99, 106–7, 112; trust and, 174–76 performativity, 224–25 Persson, Torsten, 136 Pew surveys, 140 philanthropy, 33 philosophy, 16; fairness and, 114–15, 123; freedom and, 237; happiness and, 21, 27, 31–32, 49–50; nature and, 69–70; utilitarian, 31–32, 78, 237; values and, 237–39 Pickett, Kate, 137–40 Piereson, James, 183 Piketty, Thomas, 127, 129 Pimco, 287 Pinch (Willetts), 98–99 Pinker, Steven, 118, 305n4 Poland, 239 police service, 5, 35, 163, 193, 200, 247 policy: Commission on the Measurement of Economic Performance and Social Progress and, 37–38; deregulation and, 7, 212; errors in standard, 8; evidence–based, 233–34; first ten steps for, 294–98; future and, 75–83, 291–98; Intergovernmental Panel on Climate Change (IPCC) and, 59, 66–69, 82, 297; legitimacy and, 8, 16, 50, 66, 68–69, 162–63, 213, 226, 269, 274, 292, 296–97; measurement and, 187–89; OECD countries and, 4, 11, 38, 52, 60, 68, 87, 93–94, 97–99, 112, 125–26, 160, 171, 201, 212, 243–44, 246, 273–74, 281, 283, 287, 291, 293; population growth and, 95–100; practical recommendations for, 269–91; reform and, 8, 82–83, 85 (see also reform); stability issues and, 2–4, 25, 70, 101, 124, 135, 140–41, 174, 176, 218, 296; stimulus packages and, 91, 100–103, 111; sustainability and, 57 (see also sustainability); tradition and, 9; transparency and, 83, 164, 288, 296; trilemma of, 13–14, 230–36, 275; World Forum on Statistics, Knowledge, and Policy and, 38 political correctness, 173, 231 political economy, 27–28 pollution, 15, 35, 228 Population Bomb, The (Ehrlich), 70 population issues: aging, 4, 95–100, 106, 109, 206, 267, 280, 287, 296; baby boomers and, 4, 106, 109; declining population and, 86, 89–90, 95–99, 103, 113; demographic implosion and, 95–100; environmentalists and, 99; global cities and, 165–70; Malthusianism and, 95; migration and, 108–10; one-child policy and, 95–96; posterity and, 89–90, 94–95, 105–6, 109, 112–13; retirement age and, 94, 97–99, 106–7, 112 Porter, Roy, 184 Portugal, 126, 287 posterity, 298; aging population and, 89–90, 94–95, 105–6, 109, 112–13; bankers and, 85–91, 94, 99–102; consumption and, 86, 104–6, 112–13; current generation’s debt to, 90–92, 112–13; declining population and, 86, 89–90, 95–99, 103, 113; default and, 110–12; democracy and, 106; demographic implosion and, 95–100; freedom of investors and, 108; globalization and, 108; government and, 84–95, 98–113; gross domestic product (GDP) and, 91–94, 98–99, 103, 108, 111; growth and, 90, 95, 97, 99, 102, 105–8, 111; health issues and, 89, 93–94, 97–99, 103, 106, 111–13; higher retirement age and, 94–98, 106–7, 112; innovation and, 102; institutional responsibility and, 296; less leisure and, 106–7; Medicare and, 93–94; migration and, 108–9; morals and, 90; pensions and, 85–86, 90, 92–100, 103–7, 111–13; politics and, 86–94, 98, 101–8, 111–13; poverty and, 100; productivity and, 88, 97–99, 102, 105–8, 112; public debt and, 85–86; reform and, 85–86, 98, 111–12; savings and, 86–87, 94, 98, 100–101, 105–8, 112; Social Security and, 93–94; social welfare and, 85, 100, 112; sustainability and, 79 (see also sustainability); taxpayer burden and, 85–91, 94, 99, 103–5; technology and, 107; welfare burden and, 92–95 poverty, 261, 267; desire to spend and, 55–56; fairness and, 125, 128, 138, 142; happiness and, 43; posterity and, 100; trust and, 168–69 printing press, 7 productivity, 16; balance and, 268, 271, 273–76, 281, 287; bureaucratic obstacles to, 285–86; Commission on the Measurement of Economic Performance and Social Progress and, 37–38; fairness and, 131, 135; globalization and, 131 (see also globalization); governance and, 173–77; happiness and, 27, 38, 42, 51; improvements in, 107–8; institutions and, 244–47, 257, 263; measurement and, 189–90, 194, 199–201, 206–7; nature and, 78, 82; posterity and, 88, 97–99, 102, 105–8, 112; public services and, 257; Soviet method and, 246; technology and, 107–8, 157–59, 268; trilemma of, 13–14, 230–36, 275; trust and, 156–59, 162, 166–67, 170, 174 property rights, 80, 174, 195–96, 261 Protestant work ethic, 13–14, 236 psychology: altruism and, 118–22; anomie and, 48, 51; anxiety and, 1, 25, 47–48, 136–38, 149, 174; behavioral economics and, 116–17, 121, 282; choice and, 10–11; coherence and, 49; commuting and, 47; conflict in relationships and, 47; Easterlin Paradox and, 39–44; face-to-face contact and, 7, 147, 165–68; freedom and, 237 (see also freedom); game theory and, 116–18, 121–22; gift economy and, 205–7; greed and, 26, 34, 54, 88, 129, 150, 221–23, 248, 277–79; happiness and, 9–12, 44–50 (see also happiness); lack of control and, 47; noise and, 47; paradox of prosperity and, 174; positive, 9–10, 49–50, 303n51; public choice theory and, 220, 242–45; rational choice theory and, 214–15; shame and, 47; Slow Movement and, 27–28, 205; thrift education and, 283–84, 294–95; well-being and, 137–43 Ptolemy, 274 public choice theory, 220, 242–45 Public Domain, The (Boyle), 196 public goods, 185–86, 190, 199, 211, 229, 249, 261 purchasing power parity (PPP), 306n19 Putnam, Robert, 140–41, 152–54 Quiet Coup, The (Johnson), 256–57 Radio Corporation of America (RCA), 195 Rajan, Raghuram, 136 Rank, Robert, 40 rational choice theory, 214–15 Rawls, John, 31 Reagan, Ronald, 93, 121, 127, 211, 240, 243, 247–48 recession, 9, 11–12, 275; happiness and, 22, 24, 41, 54; nature and, 55–56, 66; plethora of books following, 55; posterity and, 85, 88, 91–93, 100–101, 108, 110; recovery from, 3, 103; trust and, 182; values and, 209–10, 213, 222 reciprocal altruism, 118–22 reform, 8; benchmark for, 218; bankers and, 277–79; bonus taxes and, 278; collective assent to, 269; courage needed for, 203; first ten steps for, 294–98; health care, 285; improving statistics and, 271; institutions and, 245–48, 256, 285, 288–91, 296–97; nature and, 82–85; New Public Management and, 245–46; politics and, 287–88; posterity and, 98, 111–12; public sector, 288–90; trust and, 162–64, 176–77; values and, 218, 233, 275–78, 295 Reinhardt, Carmen, 111 religion, 10; happiness and, 32–33, 43, 50; nature and, 76, 78; Protestant work ethic and, 13–14, 236; trust and, 147 Renaissance, 7 retirement age, 94, 97–99, 106–7, 112 revalorization, 275 Road to Wigan Pier, The (Orwell), 56 Rodrik, Dani, 136 Rogoff, Kenneth, 111 Romantic Economist, The (Bronk), 28 Romanticism, 27 Rothschilds, 147 Rousseau, Jean–Jacques, 114 Royal Bank of Scotland, 146 runs, 1 Ruskin, John, 27–28 Russia, 97–98, 123; Cold War and, 93, 112, 147, 209, 213, 239; Iron Curtain and, 183, 239, 252; production targets and, 246; as Soviet Union, 228, 246 Saez, Emmanuel, 127, 129 salaries: high, 130, 143–44, 193, 223, 277–78, 286, 296; measurement and, 191–99; paradox of, 193; superstar effect and, 134; technology and, 2, 89 Sandel, Michael, 224–25, 237 Sarkozy, Nicolas, 37, 202, 274 satellite accounts, 38, 81, 204–6, 271 Satyam, 146 savings, 1, 280–82, 293; China and, 87, 94, 100, 108; necessary increasing of, 105–6; negative, 105; policy recommendations for, 280–84; posterity and, 86–87, 94, 98, 100–101, 105, 108, 112; thrift education and, 283–84, 294–95 savings clubs, 283 Schumpeter, Joseph, 14 Schwartz, Barry, 10–11, 40 Seabright, Paul, 148–49, 170, 213–14, 228 self-interest: fairness and, 114–22; greed and, 26, 34, 54, 88, 129, 150, 221–23, 248, 277–79; moral sentiments and, 119–20, 142, 221; nature and, 65; reciprocal altruism and, 118–22; values and, 214, 221 Selfish Gene, The (Dawkins), 118 Sen, Amartya, 18, 37, 43, 82, 202, 237, 274, 310n25 shame, 47 shareholders, 88, 145, 248, 257–58, 277 Silicon Valley, 166 Simon, Herbert, 249–50, 254, 261, 270 Simon, Julian, 70 Singapore, 126 Sloan School, 256 Slow Food, 27 Slow Movement, 27–28, 205 smart cards, 252–53 Smith, Adam, 119–20, 209, 221, 255 Smith, Vernon, 215 social capital, 8, 12, 17; definition of, 152–53; fairness and, 116, 121, 139–43; intangible assets and, 149–52, 157, 161, 199–201; measurement of, 154, 185; policy recommendations for, 267, 271, 273, 276; Putnam on, 152–54; trust and, 5, 151–57, 168–74, 177; values and, 223–25, 231, 257 social justice, 31, 43, 53, 65, 123, 164, 224, 237, 286 Social Limits to Growth, The (Hirsch), 190, 231 social markets, 217–20 social networks, 260, 270, 288–89 Social Security, 93–94 social welfare.

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Scott, 33, 127 food shortages, 111 Forbes Rich List, 123 “For Richer,” (Krugman), 232 France, 27, 37, 123, 125, 202, 226, 274 Frank, Robert, 43 fraud, 146–47, 150, 248 freedom: of choice, 11; happiness and, 10, 13, 26, 42–44, 50–53; institutions and, 244, 262; of investors, 108; nature and, 79; philosophies of, 237; trilemma of, 13–14, 230–36, 275; values and, 237–38 free market, 14; fairness and, 121, 129; institutions and, 240, 243, 251; measurement and, 182–83; values and, 210–11, 218–24, 232 Fuggers, 147 Fukuyama, Francis, 239 Galbraith, John Kenneth, 190, 193, 230–31, 243 Gallup Poll, 66 game theory, 116–18, 121–22 Gardner, Howard, 48 Gaskell, Mrs., 131 Gates, Bill, 33 “G” countries, 162–65, 177 Gdansk, 239 General Social Survey, 140 Germany, 87, 89, 95, 97–98, 99, 112, 125, 280 gift economy, 205–7 Gini coefficient, 126 Glaeser, Edward, 128, 171 Glastonbury Festival, 197 globalization: call centers and, 131, 133, 161; cities and, 165–70; face-to-face contact and, 7, 147, 165–68; happiness and, 24; inequality and, 122, 127, 131, 155; institutions and, 244; international trade and, 110, 148, 159, 163; manufacturing and, 148–49, 160–61; outsourcing and, 159, 161, 175, 219, 287; posterity and, 108; specialization and, 160–61; technology and, 7; trust and, 149–51, 157, 160–65, 170; values and, 210–11, 235; voter turnout and, 175 global warming, 57, 64, 66, 68 Golden Rule, 93 Goldman Sachs, 145 goods and services, 7, 10, 282; experience, 229; government budget and, 191, 193; happiness and, 24, 35–36, 40; intangible assets and, 199–201; luxury, 190–91; measurement and, 188, 191, 198; missing markets and, 229; music and, 194–98; nature and, 82; positional, 190; posterity and, 99; status and, 190; teachers and, 191–93; trust and, 161; unnecessary, 216; values and, 214, 218, 228–29.

Socialism Sucks: Two Economists Drink Their Way Through the Unfree World by Robert Lawson, Benjamin Powell

Airbnb, anti-communist, Berlin Wall, Bernie Sanders, Black Lives Matter, business cycle, cognitive dissonance, crony capitalism, Deng Xiaoping, Donald Trump, en.wikipedia.org, equal pay for equal work, Fall of the Berlin Wall, Gini coefficient, Great Leap Forward, hiring and firing, illegal immigration, income inequality, indoor plumbing, invisible hand, Kickstarter, means of production, Mont Pelerin Society, profit motive, road to serfdom, Ronald Reagan, single-payer health, special economic zone, The Wealth of Nations by Adam Smith

Most of what we heard seemed factually accurate, but they failed to discuss the difference between North and South Korea’s economic systems. Diana mistakenly claimed that “South Korea today is among the most unequal countries in the world” as a result of capitalism. But it’s not. Economists use something called a Gini coefficient to measure income inequality across countries. In 2015, South Korea’s Gini coefficient of 33.5 ranked it the fifth most equal country out of the eighty-two countries in the world with reported data.2 More generally, research with Bob’s index has shown that there is really no relationship between how capitalist a country is and how unequal its incomes are.

…

Michael, 48 Coyne, Chris, 135 Crisis and Leviathan (Higgs), 136 Cristal (beer), 35 Cuba effects of central planning in, 34–41, 45 health care in, 16, 52–53 import restrictions, 49–50 private businesses in, 42–43, 45–47 travel restrictions, 33 Cuban Revolution, 131 Cúcuta, 17, 25, 30 Cultural Revolution, 75–76, 79 Current Affairs, 137 D Dandong, 61–62, 66 Dean, Andrea, 56 deBoer, Fredrik, 138 demilitarized zone (DMZ), 65, 69 Democratic Party, 9–10, 144 Democratic People’s Republic of Korea, 59 democratic socialism, 2, 9, 16, 32, 126–27, 138–39, 146 Deng Xiaoping, 76, 79 Denmark, 10 Dikötter, Frank, 73–75, 150 Duranty, Walter, 92–95 Duvel Café, 5, 10–11 E Eastern Bloc, 85, 126 economic freedom index, 6, 10–11, 20, 63, 79, 99–100, 110, 136 Economic Freedom Network (EFN), 99, 102 Economic Freedom of the World report, 99, 151 economic freedom, 4, 11, 13, 20, 30, 56, 78–80, 105, 108, 110, 112–14, 117, 150 Ecuador, 17 Egypt, 15 El Guajirito, 45–47 Empresas Polar, 26 Erekle (king), 104 Expert Failure (Koppl), 136 F Federal Reserve, 2–3 Fisher, Michelle, 9 Florida State University, 6 Forbidden City, 72 Foreign Policy, 27 foreign-market prices, 37 Fortune Global 500, 64 Fox News, 134 Fraser Institute, 6 Free Market Institute, 7 free markets, 7, 21, 78, 116, 133, 136 Free the People, 141 free-market prices, 21, 37, 48, 88 FreedomWorks, 142 Friedman, Milton, 6–7, 30, 82, 148 G George Mason University, 7 Georgetown University, 137 Georgia (country) Law on Economic Freedom, 114 liberal reforms in, 99, 106–110, 113 ranking on economic freedom index, 110 Ukrainian government in, 101–102 winemaking in, 111–12 Georgian Soviet Socialist Republic, 105 Ghodsee, Kristen, 96 Gini coefficient, 124 Glover, Danny, 1 Gohmann, Steve, 64 grassroots movements, 141–43 Gray, Francine du Plessix, 96–98 Great Britain, 73 Great Leap Forward, 13, 73–76 Grier, Kevin, 28 gross domestic product (GDP), 2, 12–13, 49, 63, 114, 134 Guardian, The, 94 Guevara, Che, 9, 54 Guiadó, Juan, 31 Gwartney, James, 6 H Hall, Joshua, 11 Han River, 65 Harvard, 8 Harvest of Sorrow, The (Conquest), 95 Haverhill, 6 Hayek, Friedrich, 7, 30, 150 Hierta, Lars Johan, 11–12 Higgs, Robert, 136 Hobbs, Brad, 12 Hotel Caribbean, 44, 47 Hotel Ibis, 77 Hotel Metropol, 92 Hotel Nacional, 34, 71 Hotel Neptuno Tritón, 34 Huangpu River, 77 HuffPost, 53 Human Action (von Mises), 100 Hyundai-Kia, 64 I immigration, 122, 134–35, 146 In Order to Live (Yeonmi Park), 60 Incheon International Airport, 63 Independence Square, 101 International Black Sea University, 112 International Monetary Fund, 109 International Socialist Organization (ISO), 123, 125–26 Intourist Hotel, 107 invisible hand, 21 J Jandieri, Gia, 105, 116 Jones, Gareth, 94 K KGB, 89 khachapuri, 116 Khevsureti, 110 khinkali, 116 Khomassuridze, Archil, 97–98 Khrushchev, Nikita, 73 Kibbe, Matt, 141–48 Kiev, 98–102, 117 Kim Il-Sung, 125 Koppl, Roger, 136 Korean War, 63, 65 Kremlin, 89 L La Cabaña prison, 54 La Habana Vieja (Old Havana), 38, 40 Lada, 38, 50 Le Cabernet, 72 Leeson, Peter, 56 Lenin, Vladimir, 9, 16, 89–91, 114–15, 125, 128, 131 Leningrad, 98 LG, 64 libertarianism, 59, 106, 123, 144–47 Lipovskaya, Olga, 97 Little Havana, 56 Little Red Book, 73 Lujiazui Finance and Trade Zone, 80 Luxemburg, Rosa, 125 M Ma Junjie, 81 Macasa, Diana, 123 Maduro, Nicolás, 30–32, 127 Major, John, 120 Maldonado, Víctor, 25 Malecón, 43, 53 Mao Yushi, 82 Mao Zedong, 9, 73–76, 81, 95, 115, 125 Mao’s Great Famine (Dikötter), 73, 150 Marginal Revolution, 86 market prices, 18, 21, 37, 88 Martin, Sabrina, 24–25 Marx, Karl, 86–88, 122, 125, 131, 139 Marxism alienation, 87 labor theory of value, 86–87 theory of history, 88 means of production, 13, 37, 87–88, 90, 121, 124, 126, 128–29, 137–39, 147 Mediterranean, 103 Mendoza, Lorenzo, 26 Mi Amigo Hugo, 27 Miami, 33, 52, 56–57, 134, 155 millennials, 8–10, 120, 138 Milton Friedman Prize for Advancing Liberty, 82 Mises, Ludwig von, 37, 100, 150 Mont Pelerin Society, 7, 64 Mont Pelerin, 7 Moore, Michael, 1, 13, 27 Moscow, 85, 92, 100, 111, 154 Moskvitch, 50 Muggeridge, Malcolm, 94 N Nation, The, 121 National Assembly (Venezeula), 31 National Bank of Cuba, 55 Nazi Germany, 37 New Economic Policy (NEP), 91, 93 New Economic School, 104–105, 116 New Hampshire, 15 New York Times, 9–10, 30, 92, 94–96 Nobel Prize, 6–7 Norberg, Johan, 11 North American Free Trade Agreement (NAFTA), 133 North Korea border with South Korea, 65 contrast between China and, 59, 69 contrast between South Korea and, 62–63, 69, 124 poverty in, 68 refugees from, 60–61 socialism in, 13, 16, 31, 63, 67, 125 Norway, 10–11 Novotel Beijing Peace Hotel, 72 O O’Neil Center for Global Markets and Freedom, 6 Obama, Barack, 33, 55 Ocasio-Cortez, Alexandria (AOC), 143–44, 147 OECD, 13 Oriental Pearl Tower, 77 Orwell, George, 102 P PanAm Post, 18 Parajanov, Sergei, 111 Park, Yeonmi, 60, 68 Patriots, 7 Paul, Rand, 145 Paul, Ron, 142–47 Peng, Dean, 59, 72 Penn, Sean, 1, 27, 128 People’s Republic of China, 59, 73 Pessin, Haley, 121 Petroleos de Venezuela SA, 31 Peugeot, 51–52 Plaza de la Revolución, 54 Plaza Mayor, 43 private property, 10, 13, 21, 37, 45, 78–79, 87, 108–110, 121, 128, 130, 138–39 proletariat, 88, 92 Pudong, 77–78, 80 Puerto Esperanza, 50, 52 Putin, Vladimir, 102 Pyongyang, 65, 69, 85 R Rand, Ayn, 81 Reagan, Ronald, 120 Red Army, 104 Red Century column, 9, 92, 95 Red Guard, 76 Red Spots, 31 Red Square, 89 Red Terror, 89 Republican Party, 142–44 Reuters, 23, 31 Revolution Brewing, 130 Revolutionary Committee of the Don, 90 Río Táchira, 17 Road to Serfdom, The (Hayek), 30, 150 Robinson, Nathan, 137–38 Romanchuk, Jaroslav, 99 Romero, Denise, 121, 132, 135 Rose Revolution, 105, 113 Russia agricultural collectivization in, 93–95 life for women in Soviet, 96–98 Russian Civil War, 89 Russian famine, 90, 93–95 S Saakashvili, Mikheil (Misha), 101–102, 105–106, 114–15, 117 Salon, 1, 17 Salt Lake City, 7 Samsung, 64 San Jose State University, 7 Sanders, Bernie, 9–10, 17, 28, 137, 143–44, 147 Santander Bridge, 18, 22 Schoolland, Li, 60, 75 Scientific Research Mises Center, 99 Seoul, 62–65, 69 Serralde, Daniel, 120, 131 Shanghai Tower, 77 Shanghai World Financial Center, 77 Shawnee State University, 6 Shcheglov, Lev, 98 Sheng Hong, 83 Sheshelidze, Paata, Simón Bolívar Bridge, 23, Sino-Korean Friendship Bridge, 104–105 Sinuiju, 59, 61, 66 Sirota, David, 1 Smith, Adam, 21, 86, 133 Sobel, Russell, 56 Socialism Conference, 120–22, 125, 128–31, 136–39, 146 Socialist International, 32 South America, 17, 135 South China Morning Post, 82 South Korea, 62–64, 68–69, 123–24 South Ossetia, 113 Southern Methodist University (SMU), 6, 48, 77–79 Soviet Ministry of Health, 97 Soviet Women (Gray), 96 special economic zone (SEZ), 80 St.

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In a recent review of nearly two hundred academic studies, Bob and his co-author Joshua Hall concluded, “Over two-thirds of these studies found economic freedom to correspond to a ‘good’ outcome such as faster growth, better living standards, more happiness, etc. Less than four percent of the sample found economic freedom to be associated with a ‘bad’ outcome such as increased income inequality.”8 Although Sweden is still mostly free today, it used to be even freer. Our Swedish friend, Johan Norberg, has told the story of how laissez-faire economic reforms made Sweden rich.9 In his telling, back in the early 1860s his ancestors were so poor that they had to mix tree bark into their bread recipe when they were short on flour.

The Age of Stagnation: Why Perpetual Growth Is Unattainable and the Global Economy Is in Peril by Satyajit Das

"there is no alternative" (TINA), "World Economic Forum" Davos, 9 dash line, accounting loophole / creative accounting, additive manufacturing, Airbnb, Alan Greenspan, Albert Einstein, Alfred Russel Wallace, Anthropocene, Anton Chekhov, Asian financial crisis, banking crisis, Bear Stearns, Berlin Wall, bitcoin, bond market vigilante , Bretton Woods, BRICs, British Empire, business cycle, business process, business process outsourcing, call centre, capital controls, Capital in the Twenty-First Century by Thomas Piketty, carbon tax, Carmen Reinhart, Clayton Christensen, cloud computing, collaborative economy, colonial exploitation, computer age, creative destruction, cryptocurrency, currency manipulation / currency intervention, David Ricardo: comparative advantage, declining real wages, Deng Xiaoping, deskilling, digital divide, disintermediation, disruptive innovation, Downton Abbey, Emanuel Derman, energy security, energy transition, eurozone crisis, financial engineering, financial innovation, financial repression, forward guidance, Francis Fukuyama: the end of history, full employment, geopolitical risk, gig economy, Gini coefficient, global reserve currency, global supply chain, Goldman Sachs: Vampire Squid, Great Leap Forward, Greenspan put, happiness index / gross national happiness, high-speed rail, Honoré de Balzac, hydraulic fracturing, Hyman Minsky, illegal immigration, income inequality, income per capita, indoor plumbing, informal economy, Innovator's Dilemma, intangible asset, Intergovernmental Panel on Climate Change (IPCC), it is difficult to get a man to understand something, when his salary depends on his not understanding it, It's morning again in America, Jane Jacobs, John Maynard Keynes: technological unemployment, junk bonds, Kenneth Rogoff, Kevin Roose, knowledge economy, knowledge worker, Les Trente Glorieuses, light touch regulation, liquidity trap, Long Term Capital Management, low interest rates, low skilled workers, Lyft, Mahatma Gandhi, margin call, market design, Marshall McLuhan, Martin Wolf, middle-income trap, Mikhail Gorbachev, military-industrial complex, Minsky moment, mortgage debt, mortgage tax deduction, new economy, New Urbanism, offshore financial centre, oil shale / tar sands, oil shock, old age dependency ratio, open economy, PalmPilot, passive income, peak oil, peer-to-peer lending, pension reform, planned obsolescence, plutocrats, Ponzi scheme, Potemkin village, precariat, price stability, profit maximization, pushing on a string, quantitative easing, race to the bottom, Ralph Nader, Rana Plaza, rent control, rent-seeking, reserve currency, ride hailing / ride sharing, rising living standards, risk/return, Robert Gordon, Robert Solow, Ronald Reagan, Russell Brand, Satyajit Das, savings glut, secular stagnation, seigniorage, sharing economy, Silicon Valley, Simon Kuznets, Slavoj Žižek, South China Sea, sovereign wealth fund, Stephen Fry, systems thinking, TaskRabbit, The Chicago School, The Great Moderation, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, the market place, the payments system, The Spirit Level, Thorstein Veblen, Tim Cook: Apple, too big to fail, total factor productivity, trade route, transaction costs, uber lyft, unpaid internship, Unsafe at Any Speed, Upton Sinclair, Washington Consensus, We are the 99%, WikiLeaks, Y2K, Yom Kippur War, zero-coupon bond, zero-sum game

The book challenges the mythology central to liberal societies of an egalitarian meritocracy based on skill, hard work, entrepreneurship, and competition. As with GDP, measuring inequality is difficult. One measure is the Gini coefficient, developed by Italian statistician and sociologist Corrado Gini. A measure of zero represents perfect equality, with everyone having the same income, while a hundred represents perfect inequality, with one person receiving all the income. Another measure is concentration, which uses the percentage of income or wealth controlled by the top 1 percent of the population. Both measures indicate rising inequality. The Gini coefficient for the world rose to 68 in 2005, from 49 in 1820. Based on the latest statistics, the US scored 41.

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George Orwell was prescient when he wrote that “we all live by robbing Asiatic coolies, and those of us who are ‘enlightened’ all maintain that those coolies ought to be set free; but our standard of living, and hence our ‘enlightenment,’ demands that the robbery shall continue.”12 Economic apartheid, in the shape of inequality, now threatens growth.13 The newfound focus on inclusive capitalism highlights the exclusion of significant portions of the population from the benefits of economic expansion. Greater income inequality increasingly constrains an already weak recovery. Empirical research suggests that an increase in income inequality by one Gini coefficient point decreases the annual growth in GDP per capita by around 0.2 percent. Higher income households have a lower marginal propensity to consume, spending a lower portion of each incremental dollar of income than those with lower incomes.

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Brazil, Russia, India, China, and South Africa recorded 53, 40, 34, 37, and 65 respectively.2 The concentration of income indicates similar patterns of inequality to the Gini coefficient. In 2012, the top 1 percent of American households received around 19 percent of US income. The percentages for Canada, Australia, and New Zealand were measured at 12, 9, and 8 respectively. The UK, Germany, France, and Italy scored 13, 13, 8, and 9. Japan came in at 10. Inequality increased significantly between 1980 and 2002. In the US since 1977, the top 1 percent of earners received 47 percent of all income growth. In Canada, it was 37 percent.

Economics Rules: The Rights and Wrongs of the Dismal Science by Dani Rodrik

airline deregulation, Alan Greenspan, Albert Einstein, bank run, barriers to entry, behavioural economics, Bretton Woods, business cycle, butterfly effect, capital controls, carbon tax, Carmen Reinhart, central bank independence, collective bargaining, congestion pricing, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, distributed generation, Donald Davies, Edward Glaeser, endogenous growth, Eugene Fama: efficient market hypothesis, Everything should be made as simple as possible, Fellow of the Royal Society, financial deregulation, financial innovation, floating exchange rates, fudge factor, full employment, George Akerlof, Gini coefficient, Growth in a Time of Debt, income inequality, inflation targeting, informal economy, information asymmetry, invisible hand, Jean Tirole, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, labor-force participation, liquidity trap, loss aversion, low skilled workers, market design, market fundamentalism, minimum wage unemployment, oil shock, open economy, Pareto efficiency, Paul Samuelson, price elasticity of demand, price stability, prisoner's dilemma, profit maximization, public intellectual, quantitative easing, randomized controlled trial, rent control, rent-seeking, Richard Thaler, risk/return, Robert Shiller, school vouchers, South Sea Bubble, spectrum auction, The Market for Lemons, the scientific method, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, trade liberalization, trade route, ultimatum game, University of East Anglia, unorthodox policies, Vilfredo Pareto, Washington Consensus, white flight

The specific example I will consider here is the theories behind the rise in inequality in the United States and some other advanced economies since the late 1970s. Even if widely accepted, these theories are not meant to apply to other settings. The explanations I will consider do not attempt to account also for, say, the rise of inequality in this country during the gilded age before World War I or the decline in inequality in many Latin American countries since the 1990s. They are sui generis. The steep rise in US inequality that began in the mid-1970s is well documented. The Gini coefficient, a widely used measure of inequality that varies from 0 (no inequality) to 1 (maximum inequality, with all income going to a single household), rose from 0.40 in 1973 to 0.48 in 2012—a 20 percent increase.15 The country’s richest 10 percent raised their share of national income from 32 to 48 percent over the same period.16 What caused this dramatic change?

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., 13n Hunting Causes and Using Them: Approaches in Philosophy and Economics (Cartwright), 22n import quotas, 149 incentives, 7, 170, 172, 188–92 income: functional distribution of, 121 military service and, 108 personal distribution of, 121 income inequality, 117, 124–25, 138–44, 147–49 deregulation in, 143 factor endowments theory in, 139–40 Gini coefficient and, 138 globalization in, 139–41, 143 in manufacturing, 141 offshoring in, 141 skill premium in, 138–40, 142 skill upgrading in, 140, 141, 142 technological change in, 141–43 trade in, 139–40 India, 107, 154 Indonesia, 166 industrial organization, 201 industrial revolution, 115 industry: developing economies and policies on, 75–76, 87, 88 government intervention and, 34–35 inflation, 185 in business cycles, 126–27, 130–31, 133, 135, 137 public spending and, 114 infrastructure, 87, 91, 111, 163 Institute for Advanced Study (IAS), xii–xiii, xiv School of Social Science at, xii Institute for International Economics, 159 institutions: development economics and, 98, 161, 202, 205–7 labor productivity and, 123 insurance, banking and, 155 interest rates, 39, 64, 110, 129–30, 156, 161 internal validity, 23–24 International Bank for Reconstruction and Development, 2 see also World Bank international economics, 201–2 International Monetary Fund (IMF), 1n, 2 Washington Consensus and, 160, 165 Internet, big data and, 38 “Interview with Eugene Fama” (Cassidy), 157n investment: business cycles and, 129–30, 136 foreign markets and, 87, 89, 90, 92, 165–67 income inequality and, 141 savings and, 129–30, 165–67 Invisible Hand Theorem, 48–50, 51n, 182, 186 Israel, 103, 188 day care study in, 71, 190–91 Japan: city growth models and, 108 income inequality and, 139 Jenkins, Holman W., Jr., 135n Jevons, William Stanley, 119 Kahneman, Daniel, 203 Kenya, 106–7 Keynes, John Maynard, 1–2, 31, 46, 165 on business cycles, 127–37 on liquidity traps, 130 see also models, Keynesian types of Klemperer, Paul, 36n Klinger, Bailey, 111n Korea, South, 163, 164, 166 Kremer, Michael, 106–7 Krugman, Paul, 136, 148 Kuhn, Thomas, 64n Kupers, Roland, 85 Kydland, Finn E., 101n labor markets, 41, 52, 56, 57, 92, 102, 108, 111, 119, 163 labor productivity, 123–24, 141 labor theory of value, 117–19 Lancaster, Kelvin, 59 Latin America, Washington Consensus and, 159–63, 166 Leamer, Edward, 139 learning, rule-based vs. case-based forms of, 72 Leijonhufvud, Axel, 9–10 Lepenies, Philipp H., 211n leverage, 154 Levitt, Steven, 7 Levy, Santiago, 3–4, 105–6 Lewis, W.

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., 134–35, 151n, 158 Feenstra, Rob, 141 field experiments, 23–24, 105–8, 173, 202–5 financial costs, 70 financial industry: globalization of, 164–67 in Great Recession, 152–59, 184 financial markets, deregulation and, 143, 155, 158–59, 162 “Fine Is a Price, A” (Gneezy and Rustichini), 71n fines, 71 First Fundamental Theorem of Welfare Economics, 47–51, 54 fiscal policies, 75–76, 87, 88, 147–48, 149, 160–61, 171 Fischer, Stanley, 165–66 forward causation, 115 Foundations of Economic Analysis (Samuelson), 125 Fourcade, Marion, 79n, 200n France, comparative advantage principle and, 59–60 Freakonomics (Levitt and Dubner), 7 Free to Choose, 49 free trade, 11, 54, 141, 169, 170, 182–83, 194 Friedman, Milton: on assumptions in modeling, 25–26 on cigarette taxes, 27–28 on invisible hand theorem, 49 on liquidity and Great Depression, 134 on model complexity, 37 fuel subsidies, 193 functional distribution of income, 121 Galbraith, John Kenneth, 184 Galileo Galilei, 29 Gambetta, Diego, 34 game theory, 5, 14–15, 33, 36, 61–62, 103–4, 133 simultaneous vs. sequential moves in, 68 garment industry, general-equilibrium effects in, 57–58 Gelman, Andrew, 115 general-equilibrium interactions, 41, 56–58, 69n, 91, 120 General Theory of Second Best, 58–61 Germany, comparative advantage principle and, 59–60 Gibbard, Allan, 20 Gilboa, Itzhak, 72, 73 Gini coefficient, 138 globalization, 139–41, 143, 164–67, 184 Gneezy, Uri, 71n Gold Standard, 2, 127 goods and services, economic models and, 12 Gordon, Roger, 151n Grand Theory of Employment, Interest, and Money, The (Keynes), 128 greenback era, 127n Greenspan, Alan, 158, 159 gross domestic product (GDP), 151n labor productivity and, 123 growth diagnostics, 86–93, 90, 97, 110–11 Haldane, Andrew, 197 Hamilton, Alexander, 187 Hanna, Rema, 107 Hanson, Gordon, 141 Harvard University, xi, 111, 136, 149, 197, 198 Hausmann, Ricardo, 111 health care: in antipoverty programs, 4, 105–7 models and, 5, 36–37, 105–7 Heckscher, Eli, 139 Herndon, Thomas, 77 Hicks, John, 128, 133 Hiebert, Stephanie, xv Hirschman, Albert O., 144–45, 195, 210n–11n housing bubble, 153–54, 156 human capital, 87, 88, 92 Humphrey, Thomas M., 13n Hunting Causes and Using Them: Approaches in Philosophy and Economics (Cartwright), 22n import quotas, 149 incentives, 7, 170, 172, 188–92 income: functional distribution of, 121 military service and, 108 personal distribution of, 121 income inequality, 117, 124–25, 138–44, 147–49 deregulation in, 143 factor endowments theory in, 139–40 Gini coefficient and, 138 globalization in, 139–41, 143 in manufacturing, 141 offshoring in, 141 skill premium in, 138–40, 142 skill upgrading in, 140, 141, 142 technological change in, 141–43 trade in, 139–40 India, 107, 154 Indonesia, 166 industrial organization, 201 industrial revolution, 115 industry: developing economies and policies on, 75–76, 87, 88 government intervention and, 34–35 inflation, 185 in business cycles, 126–27, 130–31, 133, 135, 137 public spending and, 114 infrastructure, 87, 91, 111, 163 Institute for Advanced Study (IAS), xii–xiii, xiv School of Social Science at, xii Institute for International Economics, 159 institutions: development economics and, 98, 161, 202, 205–7 labor productivity and, 123 insurance, banking and, 155 interest rates, 39, 64, 110, 129–30, 156, 161 internal validity, 23–24 International Bank for Reconstruction and Development, 2 see also World Bank international economics, 201–2 International Monetary Fund (IMF), 1n, 2 Washington Consensus and, 160, 165 Internet, big data and, 38 “Interview with Eugene Fama” (Cassidy), 157n investment: business cycles and, 129–30, 136 foreign markets and, 87, 89, 90, 92, 165–67 income inequality and, 141 savings and, 129–30, 165–67 Invisible Hand Theorem, 48–50, 51n, 182, 186 Israel, 103, 188 day care study in, 71, 190–91 Japan: city growth models and, 108 income inequality and, 139 Jenkins, Holman W., Jr., 135n Jevons, William Stanley, 119 Kahneman, Daniel, 203 Kenya, 106–7 Keynes, John Maynard, 1–2, 31, 46, 165 on business cycles, 127–37 on liquidity traps, 130 see also models, Keynesian types of Klemperer, Paul, 36n Klinger, Bailey, 111n Korea, South, 163, 164, 166 Kremer, Michael, 106–7 Krugman, Paul, 136, 148 Kuhn, Thomas, 64n Kupers, Roland, 85 Kydland, Finn E., 101n labor markets, 41, 52, 56, 57, 92, 102, 108, 111, 119, 163 labor productivity, 123–24, 141 labor theory of value, 117–19 Lancaster, Kelvin, 59 Latin America, Washington Consensus and, 159–63, 166 Leamer, Edward, 139 learning, rule-based vs. case-based forms of, 72 Leijonhufvud, Axel, 9–10 Lepenies, Philipp H., 211n leverage, 154 Levitt, Steven, 7 Levy, Santiago, 3–4, 105–6 Lewis, W.

The People vs. Democracy: Why Our Freedom Is in Danger and How to Save It by Yascha Mounk

Abraham Maslow, affirmative action, Affordable Care Act / Obamacare, An Inconvenient Truth, Andrew Keen, basic income, battle of ideas, Black Lives Matter, Boris Johnson, Branko Milanovic, Bretton Woods, business cycle, Capital in the Twenty-First Century by Thomas Piketty, carried interest, Cass Sunstein, central bank independence, centre right, classic study, clean water, cognitive bias, conceptual framework, critical race theory, David Brooks, deindustrialization, demographic transition, desegregation, disinformation, Donald Trump, en.wikipedia.org, Evgeny Morozov, fake news, Francis Fukuyama: the end of history, gentrification, German hyperinflation, gig economy, Gini coefficient, Herbert Marcuse, Home mortgage interest deduction, housing crisis, income inequality, invention of the printing press, invention of the steam engine, investor state dispute settlement, Jeremy Corbyn, job automation, Joseph Schumpeter, land value tax, low skilled workers, Lyft, manufacturing employment, Mark Zuckerberg, mass immigration, microaggression, mortgage tax deduction, Naomi Klein, new economy, offshore financial centre, open borders, Parag Khanna, plutocrats, post-materialism, price stability, ride hailing / ride sharing, rising living standards, Ronald Reagan, Rosa Parks, Rutger Bregman, secular stagnation, sharing economy, Steve Bannon, Thomas L Friedman, Tyler Cowen, Tyler Cowen: Great Stagnation, Uber and Lyft, uber lyft, universal basic income, upwardly mobile, World Values Survey, zero-sum game

Different measures of equality paint a slightly divergent picture of just how strong the increase in inequality has been. In this case, I have been referring to the Gini coefficient for earned income. See, for example, Anthony B. Atkinson, J. Hasell, Salvatore Morelli, and M. Roser, Chartbook of Economic Inequality, 2017, http://www.chartbookofeconomicinequality.com/inequality-by-country/usa/. But similar findings also hold true about other ways of measuring income inequality, or indeed about wealth inequality. See for example Piketty, Capital. 8. See note 28 in the Introduction. 9. Raj Chetty, David Grusky, Maximilian Hell, Nathaniel Hendren, Robert Manduca, and Jimmy Narang, “The Fading American Dream: Trends in Absolute Income Mobility since 1940,” Science 356, no. 6336 (2017): 398–406.

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There was only one problem: the bulk of these gains went to the richest members of society—and the times of the most rapid growth often coincided with the times of the greatest inequality. Between 1827 and 1851, for example, the English economy grew by about 80 percent. But during that same time period, the Gini coefficient, the standard measure of income inequality, increased just as rapidly. In effect, England had, in the span of a quarter century, gone from the level of income inequality recorded in today’s Iceland to the level of income inequality recorded in today’s India.3 Then another big aberration in human history set in: a period of unprecedented economic equality.

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Broadberry and Bas van Leeuwen, “British Economic Growth and the Business Cycle, 1700–1870: Annual Estimates,” Working Paper, Department of Economics, University of Warwick, Coventry, UK, February 2011, CAGE Online Working Paper Series, vol. 2010 (20), http://www2.warwick.ac.uk/fac/soc/economics/events/seminars-schedule/conferences/venice3/programme/british_economic_growth_and_the_business_cycle_1700-1850.pdf. 3. According to Jeffrey Williamson, the Gini coefficient for male earners rose from .293 to .358 between 1827 and 1851. By comparison, the Gini coefficient of today’s Iceland is .280 while that of today’s India is .352. See Jeffrey G. Williamson, “Earnings Inequality in Nineteenth-Century Britain,” Journal of Economic History 40, no. 3 (1980): 457–475, 467; as well as the World Factbook, 2017: Distribution of Family Income—Gini Index, Central Intelligence Agency, https://www.cia.gov/library/publications/the-world-factbook/rankorder/2172rank.html. 4.

How Asia Works by Joe Studwell

affirmative action, anti-communist, Asian financial crisis, bank run, banking crisis, barriers to entry, borderless world, Bretton Woods, British Empire, call centre, capital controls, central bank independence, collective bargaining, crony capitalism, cross-subsidies, currency manipulation / currency intervention, David Ricardo: comparative advantage, deindustrialization, demographic dividend, Deng Xiaoping, failed state, financial deregulation, financial repression, foreign exchange controls, Gini coefficient, glass ceiling, Great Leap Forward, high-speed rail, income inequality, income per capita, industrial robot, Joseph Schumpeter, Kenneth Arrow, land reform, land tenure, large denomination, liberal capitalism, low interest rates, market fragmentation, megaproject, non-tariff barriers, offshore financial centre, oil shock, open economy, passive investing, purchasing power parity, rent control, rent-seeking, Right to Buy, Ronald Coase, South China Sea, The Wealth of Nations by Adam Smith, TSMC, urban sprawl, Washington Consensus, working-age population

When the share of property income in a society falls (here because fewer people were renting out land), income from current work is relatively more important and overall incomes diverge less. Household income surveys in Taiwan showed that the country moved from a Gini coefficient – the standard measure of equality, where 0 is perfect equality and 1 is perfect inequality – on a par with Brazil in the early 1950s (scoring 0.56) to a level in the mid 1960s that was unprecedented for a developing country (0.33).50 Greater equality was welcomed by the average Taiwanese, but it was the impact of land reform and a more incentivising market structure on output which was truly revolutionary.

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In Deininger’s data set, long-term growth refers to the period from 1960 to 1992. The only other developing countries he found that grew an average of more than 2.5 per cent with very unequal land distribution (defined as having a land distribution Gini coefficient of more than 70) are Puerto Rico (a small and anomalous part of the United States) and Israel. See Klaus Deininger and Lyn Squire, ‘New Ways of Looking at Old Issues: Inequality and Growth’, Journal of Development Economics, vol. 57, no. 2 (1998), pp. 259–87. 13. Tang land management was in fact more complex than stated here because small parcels of land were also granted to farmers in perpetuity.

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No country bears this out more painfully than the Philippines. Journey 2: Negros Occidental Out on the runway of Manila’s Ninoy Aquino airport, a large private jet comes in to land in the afternoon sun. It is a useful reminder, if you have travelled down from north-east Asia, that you have left the world of 0.3 Gini coefficients and entered the world of 0.5 Gini coefficients – that is, a different kind of ‘developing’ economy. The plane I am on is travelling to Bacolod, the dominant city in Negros Occidental, the western half of the island of Negros. It is an area of the Philippines sometimes referred to as ‘Sugarlandia’, because of its historical role as the epicentre of the plantation sugar industry.

The American Dream Is Not Dead: (But Populism Could Kill It) by Michael R. Strain

Bernie Sanders, business cycle, centre right, creative destruction, deindustrialization, Donald Trump, feminist movement, full employment, gig economy, Gini coefficient, income inequality, job automation, labor-force participation, market clearing, market fundamentalism, new economy, opioid epidemic / opioid crisis, public intellectual, Robert Gordon, Ronald Reagan, social intelligence, Steven Pinker, The Rise and Fall of American Growth, Tyler Cowen, upwardly mobile, working poor

The CBO uses the three household income measures described above and computes a “Gini coefficient” for each. This is a standard inequality statistic that summarizes income dispersion between households for the entire distribution of income. The CBO found that income inequality between 1979 and 2006 increased by between 24 and 27 percent, depending on the definition of income. But things look very different between 2007 and 2016. Using market income, inequality has only grown by 2 percent. Using income after taxes and transfers, inequality has actually decreased by 7 percent (figure 12). FIGURE 12. GINI COEFFICIENTS. Looking at the usual weekly earnings of workers tells a similar story.

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Between 2007 and 2019, the ratio of the 90th percentile of weekly earnings to the 10th percentile—a more conceptually straightforward measure of the rich-poor gap—increased by only 1 percent. So even if you believe that income inequality is one of the most serious challenges facing the United States, at least over the past decade or so, there seems to be a lot more heat than light. Very recently, the public debate has become interested in wealth inequality, in addition to income inequality. I focus on inequality of income here for a few reasons. It has received the most attention during the post-Great Recession period—much more than wealth inequality. It is the more relevant measure for assessing disparities in the ability of different groups to consume and to save.

…

It is the more relevant measure for assessing disparities in the ability of different groups to consume and to save. It is hard to know what to make of changes in wealth inequality over time. To see why, consider this example: Expanded social insurance and safety net programs for lower- and middle-income households reduce the need for those households to accumulate assets. This exacerbates wealth inequality because it increases the gap in asset holdings between high-wealth and low-wealth households. Or consider that innovation can increase wealth inequality while reducing income inequality. In addition, wealth inequality is a difficult metric because it is much harder to measure wealth than to measure income.

Seriously Curious: The Facts and Figures That Turn Our World Upside Down by Tom Standage

"World Economic Forum" Davos, agricultural Revolution, augmented reality, autonomous vehicles, Big Tech, blood diamond, business logic, corporate governance, CRISPR, deep learning, Deng Xiaoping, Donald Trump, Dr. Strangelove, driverless car, Elon Musk, failed state, financial independence, gender pay gap, gig economy, Gini coefficient, high net worth, high-speed rail, income inequality, index fund, industrial robot, Internet of things, invisible hand, it's over 9,000, job-hopping, Julian Assange, life extension, Lyft, M-Pesa, Mahatma Gandhi, manufacturing employment, mega-rich, megacity, Minecraft, mobile money, natural language processing, Nelson Mandela, plutocrats, post-truth, price mechanism, private spaceflight, prosperity theology / prosperity gospel / gospel of success, purchasing power parity, ransomware, reshoring, ride hailing / ride sharing, Ronald Coase, self-driving car, Silicon Valley, Snapchat, South China Sea, speech recognition, stem cell, supply-chain management, transaction costs, Uber and Lyft, uber lyft, undersea cable, US Airways Flight 1549, WikiLeaks, zoonotic diseases

This trend, though disconcerting, is not unique to the modern era. A study by Timothy Kohler of Washington State University and 17 others found that inequality may well have been rising for several thousand years, at least in some parts of the world. The scholars examined 63 archaeological sites and estimated the levels of wealth inequality in the societies whose remains were dug up, by studying the distributions of house sizes. As a measure they used the Gini coefficient (a perfectly equal society would have a Gini coefficient of zero; a society where one person owns all the wealth would have a coefficient of one). It rose from about 0.2 around 8000BC in Jerf el-Ahmar, on the Euphrates in modern-day Syria, to 0.5 in around 79AD in Pompeii.

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Horses and oxen greatly improved farm productivity – but livestock were mainly owned by the rich (who could also rent them out). In traditional African societies, livestock remain an important store of value. The agricultural revolution was good for humanity, because it supported a larger population and paved the way for modern civilisation. But it was awful for egalitarians. Nice digs Gini coefficient of house sizes at archaeological sites 1=perfect inequality, 0=perfect equality Source: “Greater post-Neolithic wealth disparities in Eurasia than in North America and Mesoamerica” by Timothy A. Kohler et al What makes something a commodity? A commodity, said Karl Marx, “appears at first sight an extremely obvious, trivial thing.

…

The extra housework such men do comes in the form of DIY or managing the family finances. The economists debunk the idea that women spend fewer hours on paid work – even when they account for differences, the chore inequality persists. It’s not that women have more time; they just do more housework. If people in couples choose to do more housework than singletons, that is their business. Perhaps it is harder to be messy when there is someone watching over your shoulder. Well-cooked meals may be more enjoyable consumed as a pair. The gender inequality this research suggests is more concerning, however, not only in itself, but also because it could be holding back women in the workplace.

Throwing Rocks at the Google Bus: How Growth Became the Enemy of Prosperity by Douglas Rushkoff

activist fund / activist shareholder / activist investor, Airbnb, Alan Greenspan, algorithmic trading, Amazon Mechanical Turk, Andrew Keen, bank run, banking crisis, barriers to entry, benefit corporation, bitcoin, blockchain, Burning Man, business process, buy and hold, buy low sell high, California gold rush, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, centralized clearinghouse, citizen journalism, clean water, cloud computing, collaborative economy, collective bargaining, colonial exploitation, Community Supported Agriculture, corporate personhood, corporate raider, creative destruction, crowdsourcing, cryptocurrency, data science, deep learning, disintermediation, diversified portfolio, Dutch auction, Elon Musk, Erik Brynjolfsson, Ethereum, ethereum blockchain, fiat currency, Firefox, Flash crash, full employment, future of work, gamification, Garrett Hardin, gentrification, gig economy, Gini coefficient, global supply chain, global village, Google bus, Howard Rheingold, IBM and the Holocaust, impulse control, income inequality, independent contractor, index fund, iterative process, Jaron Lanier, Jeff Bezos, jimmy wales, job automation, Joseph Schumpeter, Kickstarter, Large Hadron Collider, loss aversion, low interest rates, Lyft, Marc Andreessen, Mark Zuckerberg, market bubble, market fundamentalism, Marshall McLuhan, means of production, medical bankruptcy, minimum viable product, Mitch Kapor, Naomi Klein, Network effects, new economy, Norbert Wiener, Oculus Rift, passive investing, payday loans, peer-to-peer lending, Peter Thiel, post-industrial society, power law, profit motive, quantitative easing, race to the bottom, recommendation engine, reserve currency, RFID, Richard Stallman, ride hailing / ride sharing, Ronald Reagan, Russell Brand, Satoshi Nakamoto, Second Machine Age, shareholder value, sharing economy, Silicon Valley, Snapchat, social graph, software patent, Steve Jobs, stock buybacks, TaskRabbit, the Cathedral and the Bazaar, The Future of Employment, the long tail, trade route, Tragedy of the Commons, transportation-network company, Turing test, Uber and Lyft, Uber for X, uber lyft, unpaid internship, Vitalik Buterin, warehouse robotics, Wayback Machine, Y Combinator, young professional, zero-sum game, Zipcar

If corporations convert too many assets from the working and business economies into pure capital, then the whole system seizes up for lack of fuel. The main figure they cite, the Gini coefficient of income inequality, measures how much income has been monopolized by the shareholders at the top. A Gini coefficient of 0 would mean that everyone has the same amount of money; a coefficient of 1 means that all the income is being taken by just one person or corporation. According to Beth Ann Bovino, chief economist at S&P, once that coefficient goes above 0.4 or 0.45—where we are as of this writing—it hurts growth for everyone. “It’s good for a market economy to have income inequality but to extremes, it can actually damage growth long term and make it less sustainable.”19 Bovino showed that it’s not just the extreme of inequality that’s to blame but the decline of labor and business income in the face of rising capital gains.

…

., 229 Circuit City, 90 Citizens United case, 72 Claritas, 32 click workers, 50 climate change, 135, 227–28, 237 coin of the realm, 128–29 collaboration as corporate strategy, 106–7 colonialism, 71–72 commons, 215–23 co-owned networks and, 220–23 history of, 215–16 projects inspired by, 217–18 successful, elements of, 216–17 tragedy of, 215–16 worker-owned collectives and, 219–20 competencies, of corporations, 79–80 Connect+Develop, 107 Consumer Electronics Show, 19 Consumer Reports,33 contracting with small and medium-sized enterprises, 112 cooperative currencies, 160–65 favor banks, 161 LETS (Local Exchange Trading System), 163–65 time dollar systems, 161–63 co-owned networks, 220–23 corporations, 68–82 acquisition of startups, growth through, 78 amplifying effect of, 70, 73 Big Shift and, 76 cash holdings of, 76, 77–78 competency of, 79–80 cost reduction, growth through, 79–80 decentralized autonomous corporations (DACs), 149–50 Deloitte’s study of return on assets (ROA) of, 76–77 distributive alternative to platform monopolies, 93–97 evaluation of, 69–74 extractive nature of, 71–72, 73, 74, 75, 80–82 growth targets, meeting, 68–69 income inequality and, 81–82 limits to corporate model, 75–76, 80–82 managerial and financial methods to deliver growth by, 77–79 monopolies (See monopolies) obsolescence created by, 70–71, 73 offshoring and, 78–79 personhood of, 72, 73–74, 90, 91 recoding of, 93–97, 125–26 repatriation and, 80 retrieval of values of empire and, 71–72, 73 as steady-state enterprises, 97–123 Costco, 74 cost reduction, and corporate growth, 79–80 Couchsurfing.com, 46 crashes of 1929, 99 of 2007, 133–34 biotech crash, of 1987, 6 flash crash, 180 Creative Commons, 215 creative destruction, 83–87 credit, 132–33 credit-card companies, 143–44 crowdfunding, 38–39, 198–201 crowdsharing apps, 45–49 crowdsourcing platforms, 49–50 Crusades, 16 Cumbrian Pounds, 156 Curitiba, Brazil modified LETS program, 164–65 Daly, Herman, 184 data big, 39–44 getting paid for our own, 44–45 “likes” economy and, 32, 34–36 in pre-digital era, 40 Datalogix, 32 da Vinci, Leonardo, 236 debt, 152–54 decentralized autonomous corporations (DACs), 149–50 deflation, 169 Dell, 115–16 Dell, Michael, 115–16 Deloitte Center for the Edge, 76–77 destructive destruction, 100 Detroit Dollars, 156 digital distributism, 224–39 artisanal era mechanisms and values retrieved by, 233–34 developing distributive businesses, 237–38 digital industrialism compared, 226 digital technology and, 230–31 historical ideals of distributism, 228–30 leftism, distinguished, 231 Pope Francis’s encyclical espousing distributed approach to land, labor and capital, 227–28 Renaissance era values, rebirth of, 235–37 subsidiarity and, 231–32 sustainable prosperity as goal of, 226–27 digital economy, 7–11 big data and, 39–44 destabilizing form of digitally accelerated capitalism, creation of, 9–10 digital marketplace, development of, 24–30 digital transaction networks and, 140–51 disproportionate relationship between capital and value in, 9 distributism and, 224–39 externalizing cost of replacing employees in, 14–15 industrialism and, 13–16, 23–24, 44, 53–54, 93, 101–2, 201, 214, 226 industrial society, distinguished, 11 “likes” and similar metrics, economy of, 30–39 platform monopolies and, 82–93, 101 digital industrialism, 13–16, 23–24, 101–2, 201 digital distributism compared, 226 diminishing returns of, 93 externalizing costs and, 14–15 growth agenda and, 14–15, 23–24 human data as commodity under, 44 income disparity and, 53–54 labor and land pushed to unbound extremes by, 214 “likes” economy and, 33 reducing bottom line as means of creating illusion of growth and, 14 digital marketplace, 24–30 early stages of e-commerce, 25–26 highly centralized sales platforms of, 29 initial treatment of Internet as commons, 25 “long tail” of widespread digital access and, 26 positive reinforcement feedback loop and, 28 power-law dynamics and, 26–29 removal of humans from selection process in, 28 digital transaction networks, 140–51 Bitcoin, 143–49, 150–51, 152 blockchains and, 144–51 central authorities, dependence on, 142 decentralized autonomous corporations (DACs) and, 149–50 PayPal, 140–41 theft and, 142 direct public offerings (DPOs), 205–6 discount brokerages, 176–78 diversification, 208, 211 dividends, 113–14, 208–10 dividend traps, 113 Dorsey, Jack, 191–92 Draw Something, 192, 193 Drexler, Mickey, 116 dual transformation, 108–9 dumbwaiter effect, 19 Dutch East India Company, 71, 89, 131 eBay, 16, 26, 29, 45, 140 education industry, 95–97 Eisenhower administration, 52–53, 63, 75 Elberse, Anita, 28 employee-owned companies, 116–18 Enron, 133, 171n Eroski, 220 eSignal, 178 EthicalBay, 221 E*Trade, 176, 177 Etsy, 16, 26, 30 expense reduction, and corporate growth, 78–79 Facebook, 4, 31, 83, 93, 96, 201 data gathering and sales by, 41, 44 innovation by acquisition of startups, 78 IPO of, 192–93, 195 psychological experiments conducted on users by, 32–33 factors of production, 212–14 Fairmondo, 221 Family Assistance Plan, 63 family businesses, 103–4, 231–32 FarmVille, 192 favor banks, 161 Febreze Set & Refresh, 108 Federal Reserve, 137–38 feedback loop, and positive reinforcement, 28 Ferriss, Tim, 201 feudalism, 17 financial services industry, 131–33, 171–73, 175 Fisher, Irving, 158 flash crash, 180 flexible purpose corporations, 119–20 flow, investing in, 208–10 Forbes,88, 173, 174 40-hour workweek, reduction of, 58–60 401(k) plans, 171–74 Francis, Pope, 227, 228, 234 Free, Libre, Open Knowledge (FLOK) program, 217–18 Free (Anderson), 33 free money theory, local currencies based on, 156–59 barter exchanges, 159 during Great Depression, 158–59 self-help cooperatives, 159 stamp scrip, 158–59 tax anticipation scrip, 159 Wörgls, 157–58 frenzy, 98–99 Fried, Jason, 59 Friedman, Milton, 64 Friendster, 31 Frito-Lay, 80 front running, 180–81 Fulfillment by Amazon, 89 Fureai Kippu (Caring Relationship Tickets), 162 Future of Work initiative, 56n Gallo, Riso, 103–4 Gap, 116 Gates, Bill, 186 General Electric, 132 General Public License (GPL) for software, 216 Gesell, Silvio, 157 GI Bill, 99 Gimein, Mark, 147 Gini coefficient of income inequality, 81–82, 92 global warming, 135, 227–28, 237 GM, 80 Goldman Sachs, 133, 195 gold standard, 139 Google, 8, 48, 78, 83, 90–91, 93, 141, 218 acquisitions by, 191 business model of, 37 data sales by, 37, 44 innovation by acquisition of startups, 78 IPO of, 194–95 protests against, 1–3, 5, 98–99 grain receipts, 128 great decoupling, 53 Great Depression, 137, 158–59 Great Exhibition, 1851, 19 Greenspan, Alan, 132–33 growth, 1–11 bazaars, and economic expansion in late Middle Ages, 16–18 central currency and, 126, 129–31, 133–36 digital industrialism, growth agenda of, 14–15, 23–24 highly centralized e-commerce platforms and, 29 startups, hypergrowth expected of, 187–91 as trap (See growth trap) growth trap, 4–5, 68–123 central currency as core mechanism of, 133–34 corporations as program and, 68–82 platform monopolies and, 82–93, 101 recoding corporate model and, 93–97 steady-state enterprises and, 98–123 guaranteed minimum income programs, 62–65 guaranteed minimum wage public jobs, 65–66 guilds, 17 Hagel, John, 76–77 Hardin, Garrett, 215–16 Harvard Business Review,108–9 Heiferman, Scott, 196–97 Henry VIII, King, 215, 229 Hewlett-Packard UK, 112 high-frequency trading (HFT), 179–80 Hilton, 115 Hobby Lobby case, 72 Hoffman, Reid, 61 Holland, Addie Rose, 205–6 holograms, 235 Homeport New Orleans, 121 housing industry, 135 Huffington, Arianna, 34, 35, 201 Huffington Post, 34, 201 human role in economy, 13–67 aristocracy’s efforts to control peasant economy, 17–18 bazaars and, 16–18 big data and, 39–44 chartered monopolies and, 18 decreasing employment and, 30–39 digital marketplace, impact of, 24–30 industrialism and, 13–16, 18–24, 44 “likes” economy and, 30–39 reevaluation of employment and adopting policies to decrease it and, 54–67 sharing economy and, 44–54 Hurwitz, Charles, 117 IBM, 90–91, 112 inclusive capitalism, 111–12 income disparity corporate model and, 81–82 digital technology as accelerating, 53–54 Gini coefficient of, 81–82, 92 growth trap and, 4 power-law dynamics and, 27–28, 30 public service options for reducing, 65–66 IndieGogo, 30, 199 individual retirement accounts (IRAs), 171 industrial farming, 134–35 industrialism, 18–24 branding and, 20 digital, 13–16, 23–24, 44, 53–54, 93, 101–2, 201, 214, 226 disempowerment of workers and, 18–19 human connection between producer and consumer, loss of, 19–20 isolation of human consumers from one another and, 20–21 mass marketing and, 19–20 mass media and, 20–21 purpose of, 18–19, 22 value system of, 18–19 inflation, 169 Instagram, 31 Intercontinental Exchange, 182 interest, 129–31 investors/investing, 70, 72, 168–223 algorithmic trading and, 179–84 bounded, 210–15 commons model for running businesses and, 215–23 crowdfunding and, 198–201 derivative finance, volume of, 182 digital technology and, 169–70, 175–84 direct public offerings (DPOs) and, 205–6 discount brokerages and, 176–78 diversification and, 208, 211 dividends and, 208–10 flow, investing in, 208–10 high-frequency trading (HFT) and, 179–80 in low-interest rate environment, 169–70 microfinancing platforms and, 202–4 platform cooperatives and, 220–23 poor performance of do-it-yourself traders and, 177–78 retirement savings and, 170–75 startups and, 184–205 ventureless capital and, 196–205 irruption, 98 i-traffic, 196 iTunes, 27, 29, 34, 89 J.

…

., 229 Circuit City, 90 Citizens United case, 72 Claritas, 32 click workers, 50 climate change, 135, 227–28, 237 coin of the realm, 128–29 collaboration as corporate strategy, 106–7 colonialism, 71–72 commons, 215–23 co-owned networks and, 220–23 history of, 215–16 projects inspired by, 217–18 successful, elements of, 216–17 tragedy of, 215–16 worker-owned collectives and, 219–20 competencies, of corporations, 79–80 Connect+Develop, 107 Consumer Electronics Show, 19 Consumer Reports,33 contracting with small and medium-sized enterprises, 112 cooperative currencies, 160–65 favor banks, 161 LETS (Local Exchange Trading System), 163–65 time dollar systems, 161–63 co-owned networks, 220–23 corporations, 68–82 acquisition of startups, growth through, 78 amplifying effect of, 70, 73 Big Shift and, 76 cash holdings of, 76, 77–78 competency of, 79–80 cost reduction, growth through, 79–80 decentralized autonomous corporations (DACs), 149–50 Deloitte’s study of return on assets (ROA) of, 76–77 distributive alternative to platform monopolies, 93–97 evaluation of, 69–74 extractive nature of, 71–72, 73, 74, 75, 80–82 growth targets, meeting, 68–69 income inequality and, 81–82 limits to corporate model, 75–76, 80–82 managerial and financial methods to deliver growth by, 77–79 monopolies (See monopolies) obsolescence created by, 70–71, 73 offshoring and, 78–79 personhood of, 72, 73–74, 90, 91 recoding of, 93–97, 125–26 repatriation and, 80 retrieval of values of empire and, 71–72, 73 as steady-state enterprises, 97–123 Costco, 74 cost reduction, and corporate growth, 79–80 Couchsurfing.com, 46 crashes of 1929, 99 of 2007, 133–34 biotech crash, of 1987, 6 flash crash, 180 Creative Commons, 215 creative destruction, 83–87 credit, 132–33 credit-card companies, 143–44 crowdfunding, 38–39, 198–201 crowdsharing apps, 45–49 crowdsourcing platforms, 49–50 Crusades, 16 Cumbrian Pounds, 156 Curitiba, Brazil modified LETS program, 164–65 Daly, Herman, 184 data big, 39–44 getting paid for our own, 44–45 “likes” economy and, 32, 34–36 in pre-digital era, 40 Datalogix, 32 da Vinci, Leonardo, 236 debt, 152–54 decentralized autonomous corporations (DACs), 149–50 deflation, 169 Dell, 115–16 Dell, Michael, 115–16 Deloitte Center for the Edge, 76–77 destructive destruction, 100 Detroit Dollars, 156 digital distributism, 224–39 artisanal era mechanisms and values retrieved by, 233–34 developing distributive businesses, 237–38 digital industrialism compared, 226 digital technology and, 230–31 historical ideals of distributism, 228–30 leftism, distinguished, 231 Pope Francis’s encyclical espousing distributed approach to land, labor and capital, 227–28 Renaissance era values, rebirth of, 235–37 subsidiarity and, 231–32 sustainable prosperity as goal of, 226–27 digital economy, 7–11 big data and, 39–44 destabilizing form of digitally accelerated capitalism, creation of, 9–10 digital marketplace, development of, 24–30 digital transaction networks and, 140–51 disproportionate relationship between capital and value in, 9 distributism and, 224–39 externalizing cost of replacing employees in, 14–15 industrialism and, 13–16, 23–24, 44, 53–54, 93, 101–2, 201, 214, 226 industrial society, distinguished, 11 “likes” and similar metrics, economy of, 30–39 platform monopolies and, 82–93, 101 digital industrialism, 13–16, 23–24, 101–2, 201 digital distributism compared, 226 diminishing returns of, 93 externalizing costs and, 14–15 growth agenda and, 14–15, 23–24 human data as commodity under, 44 income disparity and, 53–54 labor and land pushed to unbound extremes by, 214 “likes” economy and, 33 reducing bottom line as means of creating illusion of growth and, 14 digital marketplace, 24–30 early stages of e-commerce, 25–26 highly centralized sales platforms of, 29 initial treatment of Internet as commons, 25 “long tail” of widespread digital access and, 26 positive reinforcement feedback loop and, 28 power-law dynamics and, 26–29 removal of humans from selection process in, 28 digital transaction networks, 140–51 Bitcoin, 143–49, 150–51, 152 blockchains and, 144–51 central authorities, dependence on, 142 decentralized autonomous corporations (DACs) and, 149–50 PayPal, 140–41 theft and, 142 direct public offerings (DPOs), 205–6 discount brokerages, 176–78 diversification, 208, 211 dividends, 113–14, 208–10 dividend traps, 113 Dorsey, Jack, 191–92 Draw Something, 192, 193 Drexler, Mickey, 116 dual transformation, 108–9 dumbwaiter effect, 19 Dutch East India Company, 71, 89, 131 eBay, 16, 26, 29, 45, 140 education industry, 95–97 Eisenhower administration, 52–53, 63, 75 Elberse, Anita, 28 employee-owned companies, 116–18 Enron, 133, 171n Eroski, 220 eSignal, 178 EthicalBay, 221 E*Trade, 176, 177 Etsy, 16, 26, 30 expense reduction, and corporate growth, 78–79 Facebook, 4, 31, 83, 93, 96, 201 data gathering and sales by, 41, 44 innovation by acquisition of startups, 78 IPO of, 192–93, 195 psychological experiments conducted on users by, 32–33 factors of production, 212–14 Fairmondo, 221 Family Assistance Plan, 63 family businesses, 103–4, 231–32 FarmVille, 192 favor banks, 161 Febreze Set & Refresh, 108 Federal Reserve, 137–38 feedback loop, and positive reinforcement, 28 Ferriss, Tim, 201 feudalism, 17 financial services industry, 131–33, 171–73, 175 Fisher, Irving, 158 flash crash, 180 flexible purpose corporations, 119–20 flow, investing in, 208–10 Forbes,88, 173, 174 40-hour workweek, reduction of, 58–60 401(k) plans, 171–74 Francis, Pope, 227, 228, 234 Free, Libre, Open Knowledge (FLOK) program, 217–18 Free (Anderson), 33 free money theory, local currencies based on, 156–59 barter exchanges, 159 during Great Depression, 158–59 self-help cooperatives, 159 stamp scrip, 158–59 tax anticipation scrip, 159 Wörgls, 157–58 frenzy, 98–99 Fried, Jason, 59 Friedman, Milton, 64 Friendster, 31 Frito-Lay, 80 front running, 180–81 Fulfillment by Amazon, 89 Fureai Kippu (Caring Relationship Tickets), 162 Future of Work initiative, 56n Gallo, Riso, 103–4 Gap, 116 Gates, Bill, 186 General Electric, 132 General Public License (GPL) for software, 216 Gesell, Silvio, 157 GI Bill, 99 Gimein, Mark, 147 Gini coefficient of income inequality, 81–82, 92 global warming, 135, 227–28, 237 GM, 80 Goldman Sachs, 133, 195 gold standard, 139 Google, 8, 48, 78, 83, 90–91, 93, 141, 218 acquisitions by, 191 business model of, 37 data sales by, 37, 44 innovation by acquisition of startups, 78 IPO of, 194–95 protests against, 1–3, 5, 98–99 grain receipts, 128 great decoupling, 53 Great Depression, 137, 158–59 Great Exhibition, 1851, 19 Greenspan, Alan, 132–33 growth, 1–11 bazaars, and economic expansion in late Middle Ages, 16–18 central currency and, 126, 129–31, 133–36 digital industrialism, growth agenda of, 14–15, 23–24 highly centralized e-commerce platforms and, 29 startups, hypergrowth expected of, 187–91 as trap (See growth trap) growth trap, 4–5, 68–123 central currency as core mechanism of, 133–34 corporations as program and, 68–82 platform monopolies and, 82–93, 101 recoding corporate model and, 93–97 steady-state enterprises and, 98–123 guaranteed minimum income programs, 62–65 guaranteed minimum wage public jobs, 65–66 guilds, 17 Hagel, John, 76–77 Hardin, Garrett, 215–16 Harvard Business Review,108–9 Heiferman, Scott, 196–97 Henry VIII, King, 215, 229 Hewlett-Packard UK, 112 high-frequency trading (HFT), 179–80 Hilton, 115 Hobby Lobby case, 72 Hoffman, Reid, 61 Holland, Addie Rose, 205–6 holograms, 235 Homeport New Orleans, 121 housing industry, 135 Huffington, Arianna, 34, 35, 201 Huffington Post, 34, 201 human role in economy, 13–67 aristocracy’s efforts to control peasant economy, 17–18 bazaars and, 16–18 big data and, 39–44 chartered monopolies and, 18 decreasing employment and, 30–39 digital marketplace, impact of, 24–30 industrialism and, 13–16, 18–24, 44 “likes” economy and, 30–39 reevaluation of employment and adopting policies to decrease it and, 54–67 sharing economy and, 44–54 Hurwitz, Charles, 117 IBM, 90–91, 112 inclusive capitalism, 111–12 income disparity corporate model and, 81–82 digital technology as accelerating, 53–54 Gini coefficient of, 81–82, 92 growth trap and, 4 power-law dynamics and, 27–28, 30 public service options for reducing, 65–66 IndieGogo, 30, 199 individual retirement accounts (IRAs), 171 industrial farming, 134–35 industrialism, 18–24 branding and, 20 digital, 13–16, 23–24, 44, 53–54, 93, 101–2, 201, 214, 226 disempowerment of workers and, 18–19 human connection between producer and consumer, loss of, 19–20 isolation of human consumers from one another and, 20–21 mass marketing and, 19–20 mass media and, 20–21 purpose of, 18–19, 22 value system of, 18–19 inflation, 169 Instagram, 31 Intercontinental Exchange, 182 interest, 129–31 investors/investing, 70, 72, 168–223 algorithmic trading and, 179–84 bounded, 210–15 commons model for running businesses and, 215–23 crowdfunding and, 198–201 derivative finance, volume of, 182 digital technology and, 169–70, 175–84 direct public offerings (DPOs) and, 205–6 discount brokerages and, 176–78 diversification and, 208, 211 dividends and, 208–10 flow, investing in, 208–10 high-frequency trading (HFT) and, 179–80 in low-interest rate environment, 169–70 microfinancing platforms and, 202–4 platform cooperatives and, 220–23 poor performance of do-it-yourself traders and, 177–78 retirement savings and, 170–75 startups and, 184–205 ventureless capital and, 196–205 irruption, 98 i-traffic, 196 iTunes, 27, 29, 34, 89 J.

Red Flags: Why Xi's China Is in Jeopardy by George Magnus

"World Economic Forum" Davos, 3D printing, 9 dash line, Admiral Zheng, AlphaGo, Asian financial crisis, autonomous vehicles, balance sheet recession, banking crisis, Bear Stearns, Bretton Woods, Brexit referendum, BRICs, British Empire, business process, capital controls, carbon footprint, Carmen Reinhart, cloud computing, colonial exploitation, corporate governance, crony capitalism, currency manipulation / currency intervention, currency peg, demographic dividend, demographic transition, Deng Xiaoping, Doha Development Round, Donald Trump, financial deregulation, financial innovation, financial repression, fixed income, floating exchange rates, full employment, general purpose technology, Gini coefficient, global reserve currency, Great Leap Forward, high net worth, high-speed rail, hiring and firing, Hyman Minsky, income inequality, industrial robot, information security, Internet of things, invention of movable type, Joseph Schumpeter, Kenneth Rogoff, Kickstarter, labour market flexibility, labour mobility, land reform, Malacca Straits, means of production, megacity, megaproject, middle-income trap, Minsky moment, money market fund, moral hazard, non-tariff barriers, Northern Rock, offshore financial centre, old age dependency ratio, open economy, peer-to-peer lending, pension reform, price mechanism, purchasing power parity, regulatory arbitrage, rent-seeking, reserve currency, rising living standards, risk tolerance, Shenzhen special economic zone , smart cities, South China Sea, sovereign wealth fund, special drawing rights, special economic zone, speech recognition, The Wealth of Nations by Adam Smith, total factor productivity, trade route, urban planning, vertical integration, Washington Consensus, women in the workforce, working-age population, zero-sum game

The growth in services should be actively encouraged, both in megacities such as Beijing or Shanghai, which are already well -served, but also and importantly in other cities, especially those inland, which are not.28 Modern service industries, which remain relatively closed, could be deregulated and opened up, for example in a wide range of communication, professional, business, entertainment and information services. Income inequality should be lowered across both income groups and regions. China has a relatively high Gini coefficient (a measure of income inequality between 0 and 1, where, theoretically, a reading of 0 means that income is equally shared by all, and a reading of 1 means income accrues to just 1 person). The latest data from official sources in China revealed a Gini coefficient of 0.47 in 2015, compared with 0.3 in the 1980s. Gini coefficients around 0.3–0.4 are generally thought to be high. Another measure of income inequality shows that 1 per cent of Chinese households own a third of the country’s wealth, while just 1 per cent of wealth is owned by the bottom 25 per cent.29 Rebalancing is complex and Xi’s China will be unwilling to adopt many of the reform proposals and suggestions that Western thinking normally urges.

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(i) Butterfield and Swire Group (i) C929 (i) Cairncross, Sir Alec (i) Calcutta (i) Calomiris, Charles (i) Cambodia (i), (ii), (iii), (iv) Cameroon (i) Canada Chinese investment (i) immigration rates and WAP (i) TPP (i), (ii) US steel imports (i) Canton (i) Canyon Bridge Capital Partners (i) capital, movement of Asian crisis (i), (ii) insecurity manifested (i) problems with (i) reasons for and control of (i) Shanghai free trade zone (i) vigilance and restrictions (i) Caribbean (i) cars (i), (ii) Carter, Jimmy (i) Caucasus Mountains (i) Census Bureau (US) (i) Central Asia (i), (ii), (iii) central bank (i) see also banks Central Commission for Discipline Inspection (i), (ii), (iii) Central Military Commission (i), (ii), (iii) centralisation (i), (ii) ‘century of humiliation’ (i), (ii), (iii), (iv) CFIUS (Committee on Foreign Investment in the United States) (i) Chamber of Commerce (US) (i) Chengdu (i) Chiang Kai-shek (i) children (i) Chile (i), (ii) China (under Xi Jinping) economic contradictions (i) international relations divergence (i) politics back in command (i) Socialism with Chinese Characteristics for a new Era (i) technology divergence from the West (i) ‘China 2030’ (World Bank and Chinese State Council) (i) China Banking Regulatory Commission (CBRC) created (i) merger (i), (ii) national financial security campaign (i) new rules issued (i) WMPs (i) China Construction Bank (i), (ii), (iii) China Development Bank (i), (ii) China Development Forum (i) ‘China Financial Markets: A US Retreat on Global Trade Will Not Lead to a Shift in Power’ (Michael Pettis) (i) n12 China Foreign Exchange Trade System (i) China–Hong Kong Bond Connect Scheme (i) China Household Finance Survey (i) China Insurance Regulatory Commission (i), (ii), (iii), (iv) China Investment Corporation (i), (ii) n7 China Labour Bulletin (i) China Minsheng Bank (i) China Mobile (i) China–Pakistan Economic Corridor (i), (ii), (iii) China Railway Group (i) China Securities Regulatory Commission chief of dismissed (i) corporate governance guidance by (i) created (i) local government financing and (i) national financial security campaign (i) new rules issued (i) permission to use homes as security (i) stock market crash (i) China Telecom (i) China Unicom (i) ChinaChem (i) Chinalco (i) Chinese Academy of Social Sciences (i) Chinese Dream (i), (ii), (iii), (iv) Chinese People’s Political Consultative Conference (i) Chongqing (i), (ii), (iii), (iv) Christchurch (Dorset) (i) Christians (i), (ii), (iii) Cirque du Soleil (i) Cisco (i) Clinton, Bill (i) Clinton, Hillary (i) cloud, the (i), (ii), (iii) Club Med (i) CNR (i) Coalbrookdale (Shropshire) (i) colonialism (i) Columbus, Christopher (i) Comac C919 (i) Commerce, Department of (i), (ii), (iii) Commercial Bank of China (i) Communist Party see also Party Congresses in numerical order at head of index Belt and Road Initiative promises (i) Cultural Revolution’s effect (i) Deng’s commitment to (i) Department of Propaganda (i) destructive policy under Mao (i) embryo of (i) founding members (i) grip on power (i), (ii) legitimacy of (i), (ii), (iii) primacy of (i) movement towards (i) social and economic model of (i) SOEs and (i) state control, maintenance of (i) usurping machinery of government (i) vested interest opposed to reform (i) Xi and: anti-corruption campaigns (i); centralisation of power (i); National Financial Work Conference (i); position as head of (i); power derived from (i); socialism Chinese style (i); Xi reboots (i) Comprehensive and Progressive Agreement for Trans-Pacific Partnership (i), (ii) Comprehensive Economic Dialogue (i), (ii) Conference Board (i) Confucius (i), (ii), (iii), (iv) Congress (US) (i) Connaught Street (Hong Kong) (i) constitution (i) consumption trends (i), (ii) cooperatives (i) Corporation Law (1993) (i) Corruption Perception Index (i) see also anti-corruption campaigns credit gaps (i) credit intensity (i) CSR (i) Cultural Revolution cause of instability and suffering (i) macroeconomic effects (i) Mao’s legacy (i) Western mission following (i) Xi and (i) currencies (i), (ii), (iii), (iv) see also Renminbi currency reserves (i) current accounts (i) Czech Republic (i) Dalai Lama (i) Dalian (i), (ii) Dalian Wanda (i), (ii) data protection (i) Davos (i), (ii), (iii), (iv) de Gaulle, Charles (i) debt and finance (i) see also banks; shadow banks bad debt (i) bank assets and liabilities (i), (ii) debt crisis (i) debt trap (i), (ii) efficiency of investment (i), (ii) GDP and debt (i) government debt (i) growth and size of debt (i), (ii), (iii) household debt (i) LGFVs (i) systemic risk (i) ‘Decision on Major Issues Concerning Comprehensively Deepening Reforms, The’ (18th Congress of the Central Committee) (i) Democratic Republic of Congo (i) demographics age-related spending (i) demographic dividends (i), (ii) effects of one-child policy abandonment (i) fertility and one-child policy (i) labour force trends (i) macroeconomic essence of ageing (i) Dempsey, Martin (i) Deng Xiaoping cat quotation (i) commitment to Communist Party (i) Cultural Revolution comment (i) economic reforms (i), (ii), (iii), (iv) enrichment under (i) inspirational but ageing (i) ‘last action’ of (i) low profile for China (i) market-based systems (i) Party and state (i) ‘Reform and Opening Up’ (i), (ii) Southern Tour (i), (ii), (iii) Xi, Mao and (i) Denmark (i), (ii) Design of Trade Agreements Database (i) Deutsche Bank (i) Deutschmark (i) Development Research Center (State Council) (i), (ii) Diamer-Bhasha dam (i) Diaoyu islands (i), (ii), (iii) dim sum bonds (i) disease (i) Djibouti (i), (ii), (iii), (iv) Document 9 (2013) (i) Doha round (i) Duterte, Rodrigo (i) East Africa (i) see also Africa East China Sea (i), (ii) East India Company (i) East Wind Train (i) eastern Europe (i), (ii) economic freedom (i) economic traps (i), (ii) education (i), (ii), (iii) EEC (i) see also European Union Egypt (i) energy (i) Enlightenment, the (i) environment, the (i) Environmental Protection, Ministry of (i) Equatorial Guinea (i) Ericsson (i) ‘Essay on Universal History, The Manners and Spirit of Nations, An’ (Voltaire) (i) Estonia (i) Ethiopia (i) Euro (i) Europe (i), (ii) see also European Union; individual countries; West, the European Central Bank (i) European Commission (i) European Union Chinese investment (i) currencies (i) data protection regulation (i) frictions and insecurities (i), (ii) MES (i) pensions and healthcare spending (i) renewable energy comparison (i) TTIP (i) Eurozone (i) exchange rates (i), (ii), (iii) Export–Import Bank of China (i), (ii) exports (i), (ii) external surpluses (i) Facebook (i) failures, banks (i) family structures (i) Federal Reserve (i) Fenby, Jonathan (i) fertility rates (i), (ii), (iii) Finance Ministry (i), (ii) financial innovation (i) financial policy (i) financial stability (i) Finland (i) First Five-Year Plan (1953–57) (i) First Opium War (i), (ii), (iii) First World War (i), (ii), (iii) fiscal control (i) Fists of Righteous Harmony (i) Five-Year Plans see 1st Five-Year Plan; 13th Five-Year Plan Florida (i) Foochow (i), (ii) Ford, Henry (i) Foreign Affairs, Ministry of (i), (ii) foreign trade and investment (i) investment tensions (i) standing up for globalisation (i) TPP and US withdrawal (i) trade tensions with US (i) Forsea Life Insurance (i) Fort Meyers, Florida (i) Fosun International (i), (ii) four economic traps (i), (ii) Four Seasons Hotel (Hong Kong) (i) Foxconn (i) Fragile by Design (Charles Calomiris and Stephen Haber) (i) France Boxer Rebellion (i) early attempts in China (i), (ii) falling fertility (i) immigration rates (i) Qing dynasty and (i) treaty ports controlled by (i) Frankfurt (i) Fraser Institute (i) Free and Open Indo-Pacific Strategy (i) free trade agreements (FTAs) (i) Freedom House (i) freight trains (i) see also high-speed rail; transport Friedman, Milton (i) FTZs (free trade zones) (i) Fu Chengyu (i) Fujian (i), (ii), (iii) Fuzhou (i) see also Foochow G20 (i) Gate of Heavenly Peace (i) Gateway terminal (London) (i) GATT (General Agreement on Trade and Tariffs) (i) GDP 1st century to 18th century (i) 19th century (i) 2017 (i) assets and liabilities (i) bank assets and (i) budgetary revenues (i) changes in production (i) consumption share (i) credit growth and (i) credit intensity of (i) data bias (i) debt (i), (ii), (iii) economic stimulus package (i) education spending (i) Eurasia (i) exports and imports (i) external surpluses (i) government revenues (i) growth of financial assets (i) industrial investment share (i) investment rate (i) local government and (i) pensions and health care (i), (ii) problem with targeting (i) productivity increases (i) public sector debt (i) real estate (i) research and development (i) residential housing investment (i) service sector (i) shadow sector (i) SOEs (i) stimulus package (i) trade surplus (i) TVEs share (i) General Data Protection Regulation (EU) (i) General Motors (i) geo-economics (i) geography (i) Geography of Peace, The (Nicholas John Spykman) (i) George III, King (i) Germany Boxer Rebellion (i) claims and spheres of influence (i) control of treaty port (i) Deutschmark (i) research and development (i) robots (i) Gewirtz, Julian (i), (ii) n16 Gilgit-Baltistan (i) Gill, Indermit (i) Gini coefficients (i) Global Innovation Index (i) global leadership (i) global reserves (i) Global Trade Alert (i) globalisation (i), (ii), (iii), (iv) Goldman Sachs (i) Google (i) governance (i), (ii), (iii) ‘Governance Indicators’ (World Bank) (i) government departments see under name of department GPs (medical general practitioners) (i) GPT (general purpose technology) (i), (ii) Grand Canal (i), (ii) Grand Chip GmbH (i) Great Divergence (i) Great Divergence, The: China, Europe and the Making of the Modern World Economy (Kenneth Pomeranz) (i) Great Leap Forward (i), (ii), (iii), (iv) Great Wall of China (i) Greece (i), (ii), (iii), (iv) Green, Michael (i) Groningen Growth and Development Centre (i) growth (i) see also GDP Guangdong (i), (ii), (iii) Guangxi (i) Guangzhou free trade zone (i) growing importance of (i) real estate prices (i) SOEs in (i) Sun Zhigang (i) treaty ports (i) ‘Guidelines on AI Basic Research Urgent Management Projects’ (National Natural Science Foundation) (i) ‘Guiding Opinions of the Central Committee of the Communist Party of China and the State Council on Deepening State-Owned Enterprise Reform’ (i) Guizhou-Cloud Big Data (i) Guo Shuqing (i), (ii) Gutenberg, Johannes (i) Gwadar (i), (ii) Haber, Stephen (i) Hague, The (i) Hambantota (i) healthcare (i) Hebei province (i), (ii), (iii) Hewlett Packard (i) high-speed rail (i) see also freight trains; transport Hilton Hotels (i) Himalayas (i) HNA (i), (ii) Holland (i) Hong Kong ageing population (i) Asian Tiger economies (i) development of Western technology by (i) exports and insurance (i) fertility rates (i) handover anniversary (i) high growth maintained (i) importance of British era (i) middle- to high-income (i) Mutual Fund Connect (i) Renminbi bonds (i) separatism issue (i), (ii) Shanghai and China Hong Kong Bond Connect Schemes (i) Shanghai stock market and (i) trade with China (i) Treaty of Nanking (i) Hong Kong and Shanghai Bank (i) housing (i), (ii), (iii) Hu Jintao eruption of economy under (i) focus of (i) ‘lost decade’?

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Its leaders have been cognisant of them for a while. In 2007, former premier Wen Jiabao said at the National People’s Congress that the Chinese economy was becoming unstable, unbalanced, uncoordinated and unsustainable.6 Wen was worried by a long list of concerns including over-investment, unbalanced trade, inequality of incomes between cities and the countryside, wasteful and inefficient use of energy and other resources, and environmental damage. A decade on, most of these problems are still awaiting effective solutions. In May 2016, the People’s Daily published an 11,000-word, front-page interview with an ‘authoritative source’ – widely believed but never confirmed to be Liu He, a close economic adviser to President Xi Jinping – that warned that China was on a dangerous and unstable path, and needed to extensively reform its economic model with urgency.7 The interview appeared in the wake of a turbulent economic and financial period in China, encompassing a 40 per cent plunge in the value of the Shanghai composite stock market index, an unexplained, albeit minor, devaluation of the Renminbi, and capital flight that contributed a loss of about $1 trillion to China’s prized foreign exchange reserves.

Creating Unequal Futures?: Rethinking Poverty, Inequality and Disadvantage by Ruth Fincher, Peter Saunders

barriers to entry, classic study, ending welfare as we know it, financial independence, full employment, gentrification, Gini coefficient, income inequality, income per capita, labour market flexibility, labour mobility, longitudinal study, low skilled workers, low-wage service sector, marginal employment, minimum wage unemployment, New Urbanism, open economy, pink-collar, positional goods, purchasing power parity, shareholder value, spread of share-ownership, The Bell Curve by Richard Herrnstein and Charles Murray, urban planning, urban renewal, very high income, women in the workforce, working poor, working-age population

The Economist (November 5–11, 1994, pp. 19–23) cited similar figures, giving the United States, Australia, New Zealand and Switzerland the highest level of income inequality among thirteen countries, and Sweden and Japan the lowest inequality. Table 2.2 presents the results of a survey by Atkinson (1994), which shows income inequality in seventeen OECD countries in the late 1980s. The level of income inequality, as measured by the Gini coefficient, was highest in the United States, with Australia being ranked as the sixth most unequal of these countries, with a Gini coefficient 15 per cent higher than the mean. As emphasised by Atkinson (1994), however, these rankings are based on individual studies from each country and the figures may therefore not be comparable across countries.

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Table 2.2 Income inequality in OECD countries, late 1980s Country Year Gini coefficent Gini as % of mean Rank Australia Belgium Canada Denmark Finland France Germany Ireland Italy Japan Netherlands New Zealand Norway Portugal Sweden United Kingdom United States Mean 1989 1988 1983 1987 1985 1984 1990 1987 1989 1989 1989 1989 1989 1989 1989 1989 1989 – .322 .234 .382 .209 .200 .372 .260 .352 .297 .296 .296 .295 .244 .312 .210 .324 .431 .279 115 84 137 75 72 133 93 126 106 106 106 106 87 112 75 116 154 100 6 14 2 15 17 3 12 4 8 8 8 8 13 7 15 5 1 – Source: Atkinson 1994, pp. 41–2. differences in income inequality in selected countries in the middle of the 1980s, measured using identical analytical procedures for all countries.10 The Gini coefficient is greatest in the United States, followed by Italy, Australia and then France. Inequality is lower in Sweden than in any other country, followed by Belgium, Luxembourg and then Germany. A further measure of income inequality is shown in Table 2.3. This is the ratio of the income share of the highest equivalent income quintile to the share of the lowest quintile, which is a measure of the distance between the highest and lowest income groups.11 The range is widest in the United States, followed by Australia and then Canada and Italy.

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Most of these studies have used a poverty line set at 50 per cent of equivalent median income. Thus, these are studies of the extent of relative low income rather than deprivation, and as such they measure one aspect of inequality rather than poverty (Veit-Wilson 1993). Nevertheless, they are very pertinent 58 PDF OUTPUT c: ALLEN & UNWIN r: DP2\BP4401W\MAIN p: (02) 6232 5991 f: (02) 6232 4995 36 DAGLISH STREET CURTIN ACT 2605 58 UNDERSTANDING POVERTY AND SOCIAL EXCLUSION Table 2.3 Income inequality in countries in LIS database, mid-1980s Year Gini coefficient Income share ratio a 1985–86 1985 1987 1984 1984 1986 1985 1987 1987 1986 1986 .31 .23 .28 .30 .25 .31 .23 .26 .21 .29 .34 5.07 3.19 4.33 4.55 3.49 4.86 3.22 3.85 3.04 4.54 6.46 Country Australia Belgium Canada France Germany Italy Luxembourg Netherlands Sweden United Kingdom United States Note: Source: a This is the ratio of the income share of the highest quintile of the income distribution to the share of the lowest quintile.

The Meritocracy Myth by Stephen J. McNamee

Abraham Maslow, affirmative action, Affordable Care Act / Obamacare, American ideology, antiwork, Bernie Madoff, British Empire, business cycle, classic study, collective bargaining, computer age, conceptual framework, corporate governance, deindustrialization, delayed gratification, demographic transition, desegregation, deskilling, Dr. Strangelove, equal pay for equal work, estate planning, failed state, fixed income, food desert, Gary Kildall, gender pay gap, Gini coefficient, glass ceiling, helicopter parent, income inequality, informal economy, invisible hand, job automation, joint-stock company, junk bonds, labor-force participation, longitudinal study, low-wage service sector, marginal employment, Mark Zuckerberg, meritocracy, Michael Milken, mortgage debt, mortgage tax deduction, new economy, New Urbanism, obamacare, occupational segregation, old-boy network, pink-collar, plutocrats, Ponzi scheme, post-industrial society, prediction markets, profit motive, race to the bottom, random walk, Savings and loan crisis, school choice, Scientific racism, Steve Jobs, The Bell Curve by Richard Herrnstein and Charles Murray, The Spirit Level, the strength of weak ties, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, too big to fail, trickle-down economics, upwardly mobile, We are the 99%, white flight, young professional

One standard measurement of the extent of inequality is the Gini coefficient, which measures the extent of the discrepancy between the actual distribution of income and a hypothetical situation in which each quintile of the population receives the same percentage of income. Values of the Gini coefficient range between zero and one, where zero indicates complete equality and one indicates complete inequality. Thus, the higher the number, the greater the degree of inequality. Using reports from the U.S. Census Bureau, Levine (2012b) demonstrates that the Gini coefficient for the United States has steadily and incrementally increased from 0.386 in 1968 to 0.469 in 2010—representing a 21.5 percent increase over a forty-two-year span. Increases in wealth inequality are even more dramatic. The ratio of wealth of the top 1 percent of wealth holders to median wealth had increased from 125 times the median in 1962 to 225 times by 2009 (Mishel et al. 2012, 383).

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Because of the amount of ownership highly concentrated in this group, the top 1 percent of wealth holders are often referred to as “the ownership class” and are used as a proxy threshold for inclusion in the American “upper class.” In short, the degree of economic inequality in the United States is substantial by any measure. In fact, the United States now has greater income inequality and higher rates of poverty than other industrial countries (Wilkinson and Pickett 2009; Grusky and Krichell-Katz 2012; Mishel et al. 2012; Kerbo 2006; Smeeding, Ericson, and Jantti 2011; Salverda, Nolan, and Smeeding 2009; Sieber 2005). Moreover, the extent of this inequality is increasing. One standard measurement of the extent of inequality is the Gini coefficient, which measures the extent of the discrepancy between the actual distribution of income and a hypothetical situation in which each quintile of the population receives the same percentage of income.

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., 1 , 2.1-2.2 entrepreneurial capitalists, 1 , 2 , 3 entrepreneurial traits, 1 , 2 franchisees not considered as entrepreneurs, 1 irregular economy, participation in, 1.1-1.2 luck as part of success, 1 , 2 random-walk hypothesis, 1 social capital, use of, 1 , 2 , 3 upward mobility, aiming for, 1 , 2 See also self-employment Etcoff, Nancy, 1.1-1.2 ethics See moral character F Forbes magazine income listings, 1.1-1.2 , 2.1-2.2 , 3 franchises, 1.1-1.2 , 2 free-market economy, 1.1-1.2 , 2 T The Frontier in American History (Turner), 1.1-1.2 F frontier influence in America, 1 , 2 , 3 , 4 functional theory of inequality, 1 G gambling, 1 , 2 , 3 , 4.1-4.2 , 5 Gates, Bill, 1 , 2 , 3 , 4.1-4.2 , 5 Gendall, Murray, 1 Gilded Age, 1 , 2 , 3 Gini coefficient, 1.1-1.2 Gladwell, Malcolm, 1 , 2 glass ceiling, 1 , 2 , 3.1-3.2 , 4 government programs education funding, 1 , 2 , 3 health care, 1 , 2 highway subsidies and suburb development, 1 , 2 home ownership, encouraging, 1 , 2 land giveaways, 1 the poor as targets of, 1 , 2 , 3 proposed asset-building policies, 1.1-1.2 “thousand points of light” as alternative, 1 transfer payment, 1 Granovetter, Mark, 1.1-1.2 Great Depression, 1 , 2 , 3 Great Recession African Americans affected by, 1 , 2 age discrimination during, 1 class issues resulting from, 1 debt and bankruptcies, rise of, 1.1-1.2 factors leading to, 1.1-1.2 home ownership during, 1.1-1.2 , 2 mortgage debt as contributor, 1 retirement delays caused by, 1 self-employment increase, 1 white-collar crime leading to, 1 H Hamermesh, Daniel S., 1.1-1.2 , 2 hard work beauty achieved through, 1 capitalism, associated with, 1 , 2 consumption as reward, 1 as determinant of inequality, 1 increased work hours as a coping strategy, 1.1-1.2 modest effects of, 1 self-made men and, 1 as a success factor, 1 , 2 , 3.1-3.2 , 4 , 5 , 6 health health care plans, 1.1-1.2 , 2 , 3 , 4.1-4.2 , 5 , 6 older workers, 1 wealth affecting, 1 , 2 , 3.1-3.2 , 4 , 5 Herrnstein, Richard, 1.1-1.2 , 2 hierarchy-of-needs theory, 1 , 2 higher education See college hiring practices, 1.1-1.2 , 2 , 3 Hispanics, 1 , 2 , 3 , 4 , 5 , 6 , 7 Hochschild, Jennifer, 1 hockey player success, 1.1-1.2 Home Advantage (Lareau), 1.1-1.2 home ownership, 1.1-1.2 , 2.1-2.2 , 3 , 4.1-4.2 homosexuality and discriminatory practices, 1.1-1.2 , 2 human capital, 1 , 2.1-2.2 , 3 , 4 , 5 , 6 I IBM, 1.1-1.2 immigrants, 1.1-1.2 , 2 , 3 , 4 , 5 , 6 , 7 individualism as culturally dominant, 1 democracy, expressed through, 1 , 2.1-2.2 as greatly valued, 1 , 2 immigrants and, 1.1-1.2 as part of the entrepreneurial personality, 1 pioneer spirit reinforcing, 1 through self-employment, 1 self-help books promoting, 1 inequalities charitable giving as a means of reducing, 1.1-1.2 conflict and functional theories of, 1.1-1.2 economic inequalities, 1 , 2 , 3 , 4.1-4.2 , 5 , 6 , 7 , 8 educational system and, 1 , 2.1-2.2 , 3.1-3.2 , 4 , 5 , 6 , 7 , 8 , 9 gender inequality, 1.1-1.2 government spending as a factor, 1 , 2 ideologies of, 1.1-1.2 labor unions working to reduce, 1 matrix of domination, 1 residential inequalities, 1 , 2 taxes and, 1.1-1.2 , 2 in wages and income, 1.1-1.2 , 2.1-2.2 , 3.1-3.2 , 4 , 5 , 6.1-6.2 in wealth, 1 , 2 , 3.1-3.2 , 4 , 5 , 6 , 7 , 8 , 9 inheritance advantages of wealth inheritance, 1 , 2.1-2.2 , 3 attitudes towards, 1 , 2 baby boomers and, 1.1-1.2 , 2 conflict theories, within, 1 cultural capital and, 1 , 2.1-2.2 , 3 , 4 domestic partnerships and, 1 estate and inheritance taxes, 1.1-1.2 , 2 of estates, 1 , 2 Forbes magazine, heirs listed in, 1.1-1.2 inequalities, perpetuating, 1 , 2 , 3 luck and, 1 as a natural right, 1 nepotism and, 1.1-1.2 as a nonmerit factor, 1.1-1.2 , 2 , 3 , 4 , 5 , 6 , 7 , 8 old money and, 1.1-1.2 parental motivation, 1.1-1.2 , 2 primogeniture, 1 relay race, compared to, 1 , 2.1-2.2 , 3 , 4 , 5 wealth distribution through, 1 women and inheritance of wealth, 1 In Praise of Nepotism: A Natural History (Bellow), 1.1-1.2 A An Inquiry into the Nature and Causes of the Wealth of Nations (Smith), 1 I integrity, 1 , 2.1-2.2 inter vivo transfers, 1.1-1.2 , 2 , 3 , 4 investments, economic, 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11.1-11.2 , 12 , 13 IQ and IQ tests, 1.1-1.2 , 2.1-2.2 , 3 , 4 , 5 , 6 irregular economy, 1 , 2.1-2.2 , 3 , 4 J Jencks, Christopher, 1 , 2 jobs See occupations Jones, Janelle, 1.1-1.2 K Kildall, Gary, 1.1-1.2 Kozol, Jonathan, 1 L labor unions, 1 , 2 , 3.1-3.2 Lareau, Annette, 1.1-1.2 Lears, Jackson, 1 Lewis, Oscar, 1.1-1.2 Livingstone, David W., 1 , 2 lookism, 1 , 2 , 3 , 4 , 5 , 6 lottery, 1 , 2 , 3.1-3.2 , 4 lower class See working class luck denial of, 1.1-1.2 , 2 with gambling, 1 getting ahead, as a factor in, 1 , 2 , 3.1-3.2 lottery and, 1 , 2 as a nonmerit factor, 1 as part of capitalism, 1 in striking it rich, 1 , 2 wealth attainment and, 1 , 2.1-2.2 , 3 M marriage career interruptions due to, 1 marrying into money, 1 , 2 the poor and, 1 , 2.1-2.2 sexual discrimination and, 1.1-1.2 , 2 trailing partners and hiring practices, 1 upper class and, 1 , 2 , 3 , 4.1-4.2 , 5 Marx, Karl, 1 Maslow, Abraham, 1 , 2 Massey, Douglas S., 1 , 2 Matthew effect, 1 , 2 matrix of domination, 1.1-1.2 Medicare, 1 , 2.1-2.2 mentors, 1 , 2.1-2.2 , 3 , 4 , 5.1-5.2 meritocracy affirmative action and, 1 American promotion of merit, 1.1-1.2 , 2 , 3.1-3.2 , 4 , 5 , 6 coping strategies, 1 , 2 credentials, lack of as a barrier, 1.1-1.2 as a desired outcome, 1 discrimination as the antithesis of merit, 1.1-1.2 , 2.1-2.2 , 3 , 4 , 5 , 6 , 7.1-7.2 , 8 , 9.1-9.2 , 10 , 11 education as a merit filter, 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 employment opportunities, 1.1-1.2 , 2.1-2.2 , 3 entrepreneurial success, 1 fairness of the system, 1 , 2.1-2.2 , 3 , 4 , 5 folklore of, 1 government spending and, 1.1-1.2 , 2 in the hiring process, 1.1-1.2 , 2 human capital factors, 1 , 2 , 3 income based on merit, 1 inheritance as a nonmerit factor, 1 , 2.1-2.2 , 3 , 4 , 5.1-5.2 , 6 , 7.1-7.2 , 8 , 9 , 10 , 11 , 12 , 13.1-13.2 intergenerational wealth transfers, 1.1-1.2 legacy preferences as nonmerit based, 1.1-1.2 , 2 luck as a nonmerit factor, 1 , 2 , 3 , 4 , 5.1-5.2 market trends, 1.1-1.2 meritocratic aristocracy, 1.1-1.2 nepotism as nonmeritorious, 1.1-1.2 the new elite as extra-meritorious, 1 noblesse oblige increasing potential for, 1 nonmerit factors suppressing merit, 1 , 2 , 3 , 4 , 5 Barack Obama as example of, 1.1-1.2 , 2 the past, reverence for, 1 physical attractiveness as a nonmerit factor, 1 , 2 pure merit system, 1.1-1.2 reform movements and, 1 , 2 self-employment as an expression of, 1 social and cultural capital as nonmerit factors, 1.1-1.2 , 2 , 3 , 4.1-4.2 , 5.1-5.2 , 6 , 7 , 8.1-8.2 , 9 , 10 , 11 structural mobility and, 1.1-1.2 talents and abilities of the merit formula, 1 , 2 , 3 , 4 , 5 , 6 taxes and nonmerit advantages, 1.1-1.2 Mexican Americans and Mexican immigrants, 1 , 2 , 3 , 4 Microsoft, 1.1-1.2 middle class America as not middle class, 1 asset building, 1 cultural capital, 1.1-1.2 deferment of gratification, 1 education and, 1 , 2 , 3 Great Recession affecting, 1 home ownership, 1 inner cities, flight from, 1 , 2 Barack Obama, background of, 1.1-1.2 old class vs. new, 1.1-1.2 precarious status of, 1.1-1.2 sports choices of, 1 upper-middle class, 1 , 2 T The Millionaire Mind (Stanley), 1 M millionaires, 1 , 2 , 3 minority groups affirmative action, 1.1-1.2 , 2.1-2.2 asset accumulation, 1.1-1.2 core employment, underrepresentation in, 1 disadvantages of, 1 discrimination experiences, 1 , 2.1-2.2 , 3 , 4.1-4.2 , 5 , 6.1-6.2 , 7 , 8 , 9 , 10 education issues, 1.1-1.2 as inner city dwellers, 1 opportunities expanding, 1 , 2 , 3 self-employment and, 1 social capital, lack of, 1 , 2 , 3 moral character, 1.1-1.2 , 2 Mormons, 1 Murray, Charles, 1.1-1.2 , 2 , 3.1-3.2 Muslims, 1.1-1.2 N National College Athletic Association (NCAA), 1 nepotism, 1.1-1.2 , 2 net worth affirmative action and, 1 defined, 1 by income group, 1 of minority groups, 1 of Barack Obama family, 1 of one percenters, 1 , 2 , 3 of Walton heirs, 1.1-1.2 wealth scale, 1.1-1.2 new elite, 1 , 2.1-2.2 noblesse oblige, 1.1-1.2 O Obama, Barack, 1.1-1.2 , 2 , 3 , 4 Obama, Michelle, 1.1-1.2 occupations attitude as a factor, 1 , 2 blue-collar jobs, 1 , 2 , 3 , 4 , 5 CEO salaries, 1.1-1.2 , 2 changes in opportunities, 1.1-1.2 , 2 cultural capital and, 1.1-1.2 , 2 the disabled and employment difficulties, 1 discrimination, 1 , 2 , 3.1-3.2 , 4 , 5 , 6 , 7 downsizing, 1.1-1.2 , 2 , 3 , 4 , 5 , 6 education linked to, 1 , 2.1-2.2 , 3.1-3.2 , 4.1-4.2 , 5 , 6.1-6.2 , 7.1-7.2 , 8 , 9.1-9.2 , 10.1-10.2 , 11 , 12.1-12.2 , 13 , 14.1-14.2 fastest growing jobs, 1.1-1.2 , 2.1-2.2 health hazards, 1 nepotism and, 1 , 2 occupational mobility, 1.1-1.2 , 2 occupational segregation, 1 , 2.1-2.2 outsourcing, 1.1-1.2 , 2 , 3 , 4 , 5 , 6 physical attraction and occupational success, 1 self-employment and, 1 self-made men, 1.1-1.2 social capital and occupational opportunities, 1 , 2 , 3 , 4 wages, 1.1-1.2 , 2 , 3 , 4 , 5.1-5.2 , 6.1-6.2 , 7.1-7.2 , 8 white-collar jobs, 1 , 2 , 3 , 4 , 5 , 6 Occupy Wall Street (OWS), 1 old boy networks, 1 , 2 , 3.1-3.2 old money, 1.1-1.2 , 2.1-2.2 Outliers: The Story of Success (Gladwell), 1 , 2 outsourcing, 1.1-1.2 , 2 , 3 , 4 , 5 , 6 ownership class, 1 , 2 , 3 , 4 P Paterson, Tim, 1 Peale, Norman Vincent, 1.1-1.2 pensions, 1.1-1.2 , 2 , 3 , 4 , 5 , 6 pink-collar ghetto, 1.1-1.2 poverty children affected by, 1 , 2 culture-of-poverty theory, 1.1-1.2 , 2 full-time work below poverty level, 1 as a matter of attitude, 1 meritocracy and, 1 , 2 minority rates of, 1 , 2 poverty threshold, 1 regional variations in poverty rates, 1.1-1.2 , 2 senior citizens and poverty rates, 1 U.S. poverty rates, 1 T The Power of Positive Thinking (Peale), 1.1-1.2 P Protestants and the Protestant ethic, 1.1-1.2 , 2 , 3 , 4 , 5 Puritan values, 1.1-1.2 R racism and racial issues affirmative action, 1.1-1.2 athletes and, 1 crime and the legal system, 1.1-1.2 disabilities, disproportionate experience of, 1 discrimination and, 1 , 2.1-2.2 , 3.1-3.2 , 4 , 5.1-5.2 , 6 , 7 , 8 in education, 1.1-1.2 employment, affecting, 1 Great Recession worsening racial equality, 1 home ownership, 1 ideologies of inequality, as part of, 1 income gaps, 1 language skills and, 1 Obama, election of, 1 , 2 scientific racism, 1.1-1.2 segregation, 1 , 2.1-2.2 , 3 social capital and, 1 , 2 , 3 , 4 white flight, 1 , 2 random-walk hypothesis, 1 recession See Great Recession references, 1 , 2 , 3 retirement as part of the American Dream, 1 , 2 delayment as a coping strategy, 1 , 2.1-2.2 , 3 home ownership and funding of, 1 as jeopardized, 1 , 2.1-2.2 proposed supplementation, 1 self-employment and, 1 , 2 , 3 right attitude, 1 , 2.1-2.2 , 3 , 4 , 5 , 6 , 7 T The Rise of Meritocracy, 1870–2033:An Essay on Education and Equality (Young), 1 , 2 R Rivera, Lauren, 1 Rosenau, Pauline Vaillancourt, 1.1-1.2 S Schmitt, John, 1.1-1.2 schools See education segregation educational, 1 , 2 , 3 occupational, 1 , 2 , 3 , 4.1-4.2 racial, 1 , 2.1-2.2 , 3 , 4 , 5 residential, 1 , 2 , 3.1-3.2 of the wealthy, 1.1-1.2 white flight, 1 See also discrimination self-employment American Dream, as exemplifying, 1 franchises, 1 freelancing, 1 , 2 income, 1.1-1.2 irregular economy and, 1.1-1.2 , 2 , 3 , 4 petty bourgeoisie and, 1 psychological characteristics, 1 rates of, diminished, 1 , 2 , 3 , 4.1-4.2 , 5 , 6 , 7.1-7.2 , 8 risk, 1 , 2 , 3.1-3.2 , 4 subcontractors, 1 taxes, 1.1-1.2 , 2 women and minorities, 1.1-1.2 self-help books, 1 , 2 self-made individuals, 1 , 2 , 3 , 4.1-4.2 , 5 , 6 sexual harassment, 1.1-1.2 Shapiro, Thomas, 1 , 2.1-2.2 slaves and slavery, 1 , 2 , 3 , 4 , 5 , 6 , 7 small businesses, 1 , 2 , 3 , 4 , 5.1-5.2 , 6 , 7.1-7.2 , 8 , 9 Smith, Adam, 1 social capital benefits of, 1.1-1.2 , 2 defined, 1 , 2 , 3 discrimination and, 1 , 2 economic opportunities, having access to, 1 , 2 , 3 education and, 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 mentorship as a form of, 1 nepotism and, 1.1-1.2 , 2 racism and lack of, 1 , 2 , 3 , 4 restricted access, effects of, 1.1-1.2 , 2.1-2.2 social climbing, 1 , 2 , 3.1-3.2 , 4 of U.S. presidents, 1.1-1.2 weak ties, 1.1-1.2 social climbing, 1 , 2 , 3.1-3.2 , 4 social clubs, 1 , 2 , 3.1-3.2 social mobility athletic and artistic abilities, associated with, 1 , 2.1-2.2 , 3 cultural capital as a factor in, 1 education link, 1 , 2 , 3 hard work as a factor, 1 individual merit, 1 integrity hindering, 1.1-1.2 marrying for money, 1 reduction of opportunities, 1 , 2 during Republican administrations, 1 role of government, 1 , 2 social climbing, 1.1-1.2 , 2 status attainment, 1 through self-employment, 1 social reform movements, 1.1-1.2 Social Register, 1 social reproduction theory, 1.1-1.2 , 2 Social Security, 1.1-1.2 , 2 , 3 , 4 , 5.1-5.2 Something for Nothing: Luck in America (Lears), 1.1-1.2 T the South, 1 , 2.1-2.2 , 3 , 4 , 5 S Stanley, Thomas, 1 status-attainment theory, 1.1-1.2 Stevens, Mitchell, 1 stock market, 1 , 2 , 3 , 4 student loans, 1 , 2.1-2.2 success athletic success, 1 , 2.1-2.2 attitudes associated with, 1 , 2 , 3.1-3.2 birth timing and, 1.1-1.2 , 2 cultural capital, 1 , 2 , 3 , 4 discrimination, achieving success through, 1 education, as a factor in, 1 , 2 , 3 , 4 , 5 entrepreneurial success, 1 , 2 , 3 God’s grace, success as sign of, 1 , 2 hard work and, 1 , 2 , 3.1-3.2 , 4 , 5 human capital factors, 1 individualism as key to, 1 intelligence as a determinant, 1 luck as important, 1 meritocracy myth and, 1 mind-power ethic as success formula, 1.1-1.2 moral character and, 1 , 2 , 3.1-3.2 , 4 parental involvement, 1.1-1.2 , 2 , 3.1-3.2 the right stuff, being made of as key, 1.1-1.2 , 2.1-2.2 , 3 , 4 small businesses and, 1 social capital increasing likelihood of, 1 , 2 , 3 suburban living as marker of, 1 10,000 hour rule, 1 women and, 1 , 2 supply side, 1 , 2 , 3 , 4 , 5 , 6.1-6.2 Survival of the Prettiest (Etcoff), 1.1-1.2 Swift, Adam, 1.1-1.2 T talent and abilities American aristocracy, 1 American Dream, leading to, 1 of athletes and celebrities, 1 education enhancing, 1 , 2 , 3.1-3.2 functional theory of inequality, 1 jobs matched to talent, 1 success achieved through, 1 , 2 , 3 , 4 , 5 , 6 talent-use gap, 1 upward mobility and, 1 , 2.1-2.2 , 3.1-3.2 taxes capital gains, 1.1-1.2 estate taxes, 1 , 2 , 3.1-3.2 government policies linked with, 1 , 2 incentives and credits, 1.1-1.2 income taxes, lowered by Republicans, 1 irregular economy, avoiding, 1.1-1.2 progressive taxation, 1.1-1.2 , 2 , 3 , 4 property taxes and school funding, 1.1-1.2 self-employment and, 1.1-1.2 , 2 Social Security affected by, 1 , 2 the South and lower taxes, 1 tax breaks for the wealthy, 1 , 2 , 3 , 4.1-4.2 of urban areas, 1 , 2 Thurow, Lester, 1 , 2.1-2.2 Tocqueville, Alexis de, 1.1-1.2 , 2 tracking, 1 , 2.1-2.2 , 3 , 4 Turner, Frederick Jackson, 1.1-1.2 U Unequal Childhoods (Lareau), 1 upper class charitable giving and, 1 cultural capital, holders of, 1 , 2 , 3.1-3.2 , 4.1-4.2 , 5 deferred gratification, capability of, 1 distinctive lifestyle, 1.1-1.2 , 2 education, 1 , 2 endogamy, tendency towards, 1.1-1.2 as exclusive, 1.1-1.2 , 2 as isolated, 1.1-1.2 one percenters as members, 1 Plymouth Puritans as wellspring, 1 political power, 1.1-1.2 social clubs, frequenting, 1.1-1.2 virtues found in, 1 WASP background of, 1 women of, 1 , 2 , 3 upward mobility attitudes as affecting, 1 barriers to, 1 through college education, 1 credentialism and, 1 downward mobility, vs., 1 through entrepreneurialism, 1 glass ceiling as limiting, 1 integrity as suppressing, 1.1-1.2 irregular economy, as avenue, 1 marriage as a means of, 1.1-1.2 Michelle Obama as example, 1 slowing rates of, 1 See also social climbing See also social mobility V Vedder, Richard, 1 , 2 virtue, 1.1-1.2 , 2 , 3 , 4 , 5 , 6 , 7 W Walmart, 1 Walton, Sam, 1 , 2 , 3 wealth accumulation gaps, 1 , 2 , 3 advantages of wealth inheritance, 1 , 2.1-2.2 capital investments, 1 charitable giving and the wealthy, 1 , 2.1-2.2 culture of, 1 , 2 discrimination and, 1 , 2 distribution as skewed, 1.1-1.2 Forbes magazine listings, 1.1-1.2 gambling, attainment through, 1 government intervention, 1.1-1.2 , 2 Great Recession affecting, 1 guilt feelings, 1.1-1.2 hard work as negligible, 1 inequalities of, 1 , 2 , 3.1-3.2 , 4 , 5 , 6 , 7 , 8 , 9 lottery, wealth attainment through, 1 luck as a factor, 1 , 2.1-2.2 , 3 marriage rates, affecting, 1 nepotism aiding in transference of, 1 old money, 1.1-1.2 , 2.1-2.2 one percenters, 1 , 2 , 3 , 4 , 5 ostentatious displays of, 1 political power, 1.1-1.2 property ownership producing, 1 , 2 pursuit of as a moral issue, 1.1-1.2 , 2 race affecting, 1 social and cultural capital, converted to, 1 , 2 the superwealthy, 1 , 2 , 3 , 4.1-4.2 tax breaks for the wealthy, 1 taxes on, 1.1-1.2 transfers of, 1.1-1.2 , 2 , 3.1-3.2 women and, 1 See also inheritance See also self-employment Weber, Max, 1.1-1.2 welfare, 1 , 2 , 3 , 4 , 5 , 6 , 7 white Anglo-Saxon Protestants (WASPs), 1.1-1.2 , 2 white-collar crime, 1.1-1.2 , 2 Wilson, William Julius, 1 , 2 Winfrey, Oprah, 1.1-1.2 Wisconsin school, 1.1-1.2 women attractiveness as a success factor, 1 , 2 , 3.1-3.2 discrimination against, 1 , 2 , 3 , 4 , 5.1-5.2 , 6.1-6.2 , 7.1-7.2 , 8.1-8.2 , 9.1-9.2 , 10 economic disparities, 1 , 2 , 3.1-3.2 educational attainment, 1.1-1.2 , 2 family concerns, 1.1-1.2 , 2.1-2.2 , 3.1-3.2 glass ceiling, experiencing, 1 , 2 , 3.1-3.2 , 4 inferiority, feelings of, 1.1-1.2 labor force participation, increasing, 1.1-1.2 , 2 mentorships, access to, 1 , 2.1-2.2 occupational disparities, 1 , 2 , 3.1-3.2 , 4.1-4.2 , 5.1-5.2 political underrepresentation, 1.1-1.2 self-employment and, 1.1-1.2 as trailing partners, 1 of the upper class, 1 , 2 , 3 working class American Dream and, 1 cultural capital, lack of, 1.1-1.2 , 2 economic instability, 1.1-1.2 education issues, 1 , 2 , 3 hard work and, 1 health risks, 1 home ownership, 1 lower class value stretch, 1 nepotism, effect of, 1 the new lower class, 1 women and incomes, 1 work See hard work See occupations Y Young, Michael, 1 , 2 About the Authors Stephen J.

The Elusive Quest for Growth: Economists' Adventures and Misadventures in the Tropics by William R. Easterly

Andrei Shleifer, business climate, business cycle, Carmen Reinhart, central bank independence, clean water, colonial rule, correlation does not imply causation, creative destruction, endogenous growth, financial repression, foreign exchange controls, Gini coefficient, government statistician, Gunnar Myrdal, income inequality, income per capita, inflation targeting, interchangeable parts, inventory management, invisible hand, Isaac Newton, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, large denomination, low interest rates, manufacturing employment, Money creation, Network effects, New Urbanism, open economy, PalmPilot, Productivity paradox, purchasing power parity, rent-seeking, Robert Solow, Ronald Reagan, selection bias, Silicon Valley, Simon Kuznets, The Wealth of Nations by Adam Smith, Thomas Malthus, total factor productivity, trade liberalization, Tragedy of the Commons, urban sprawl, Watson beat the top human players on Jeopardy!, Yogi Berra, Yom Kippur War

Let’s look at the relationship between land inequality and economic growth. I am measuring inequality with the Gini coefficient, which goes from 0 (everyone has equal land) to 1 (1person has all the land). The fourth of the sample with the lowest inequality (average Gini coefficient of .45) hadthe highest average growth. This fourth includes such growth superstars as South Korea, Japan, and Taiwan. (Korea had the highest growth rate and the most equal land distribution in the sample.) The fourth of the sample with the highest land inequality (average Gini coefficient of 35)had the lowest growth. This highly unequal fourth includes such growth disasters as Argentina, Peru, and V e n e ~ u e l a .In ~ Argentina, for example, it was the policies of Juan and Eva Peron to redistribute income toward the descamisados (shirtless ones) that sent the Argentine economy spiraling downward until recently.

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See Hunger Foreign Assistance, 9, 25, 26,28, 31-35, 37, 38, 43, 58, 79, 101, 109, 110, 118, 274 aid contests, 119 Foreign direct investment, 131 Foreign exchange, 82, 106,114, 129, 130 France, 110,157,268 337 Frankel, Jeffrey, 231 Freedom from expropriation, 250 Freedom from government repudiation of contracts, 250 Free market, 152, 178 Free trade, 230-231,239 Gabon, 201 Gambia, 73,164 Gates, Bill, 185 Geneva, 289 Georgia, 12,233 Germany, 54,65,268 Ghana, 214,219,222-223,229,251-252, 256-257,259-261,264,267 adjustment loans, 103, 104 Ashanti Empire, 256-257,264 cocoa, 222,256-257,261,264 famine, 28 growth and aid, 5 , 2 6 , 2 7 , 4 4 , 74, 119 infrastructure, 7, 107, 108, 111, 112, 113 Rawlings government, 28 Gini coefficient, 265 Government, 148,154, 168, 177,179,181, 217-219,221,234,241,249,252,255258,261,277,279,285-286,290-291 budget deficits, 218-219, 239, 260 leaders (officials), 181, 241, 247, 250, 258,263 policies, 158, 168, 169, 213, 218, 234235,251,259 programs, 169 welfare payments, 168 Gramm-Rudman, 113 Great Depression, 30, 95 Greece, 267-268 Growth disasters, 42, 59, 60, 74 Growth theories Harrod-Domar Model, 2 8 , 2 9 , 3 6 minimum standard model (revised), 34, 35 population pressure principle, 94 Solow model with diminishing returns to investment, 50, 51, 52, 53, 54,57, 68, 69,78 surplus labor model, 30, 31,40,41 Growth Oriented Adjustment Programs, 102.

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The source for the Ghana storyis Easterly and Levine 1997;consult them for further references. 6. Leith 1974. 7.The measure of inequality is the Ginicoefficient.The data and results on land inequality and growth are from Deininger and Squire 1998; others who have found a negative relationship between inequality and growth include Alesina and Rodrik 1994; Persson and Tabellini 1994; Perotti 1996; and Clarke 1995. A contrarian positive inequality and growthresult is found by Forbes 1998,2000, using fixed effects to remove country averages; however, Deininger and Olinto 2000 find a negative effect of lnnd inequality on growth even using fixed effects. 8. Easterly, 1999b.

Grand Transitions: How the Modern World Was Made by Vaclav Smil

8-hour work day, agricultural Revolution, AltaVista, Anthropocene, Any sufficiently advanced technology is indistinguishable from magic, biodiversity loss, Biosphere 2, Boeing 747, caloric restriction, caloric restriction, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, carbon tax, circular economy, clean water, complexity theory, correlation does not imply causation, COVID-19, decarbonisation, degrowth, deindustrialization, dematerialisation, demographic dividend, demographic transition, Deng Xiaoping, disruptive innovation, energy transition, European colonialism, Extinction Rebellion, Ford Model T, garden city movement, general purpose technology, Gini coefficient, Google Hangouts, Great Leap Forward, Haber-Bosch Process, Hans Rosling, hydraulic fracturing, hydrogen economy, income inequality, income per capita, Indoor air pollution, Intergovernmental Panel on Climate Change (IPCC), invention of movable type, Johann Wolfgang von Goethe, Just-in-time delivery, knowledge economy, Law of Accelerating Returns, manufacturing employment, mass immigration, megacity, meta-analysis, microplastics / micro fibres, ocean acidification, oil shale / tar sands, old age dependency ratio, peak oil, planetary scale, planned obsolescence, power law, precision agriculture, purchasing power parity, RAND corporation, Ray Kurzweil, Republic of Letters, Robert Solow, Silicon Valley, Simon Kuznets, Singularitarianism, Skype, Steven Pinker, Suez canal 1869, the built environment, The Rise and Fall of American Growth, total factor productivity, urban decay, urban planning, urban sprawl, working-age population

Subsequently, China has seen a sharp reduction of poverty, but also a substantial increase of inequality. By 2010 China’s Gini coefficient reached 0.53–0.55, considerably higher than the US value of 0.45 and ranking among the highest recorded inequalities worldwide, particularly in comparison with countries that have comparable or higher standards of living (Xie and Zhou 2014). For comparison, the Standardized World Income Inequality Database put China’s Gini coefficient at 0.5 in 2013 (Solt 2018). China also faces considerable inequality of opportunities (gaps in access to certain financial services and unemployment insurance coverage), regional disparities, and continuing rural-urban gap.

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As a result, since 1980 income inequalities (commonly measured by the Gini coefficient) have increased in every affluent economy, as well as globally. When this trend is seen on the national basis its most notable outcome has been the emptying of the middle, with most of the national means falling below the threshold of the middle class (Milanovic 2012). The world’s fastest-growing economy has also experienced the fastest shift in inequality. Inequality in Maoist China, with its shared miseries, was low and it remained so during the first years of economic modernization: in 1985 the Gini coefficient was 0.24. Subsequently, China has seen a sharp reduction of poverty, but also a substantial increase of inequality.

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Benefits of cities continue to be shared much less equitably than they should be in societies whose main concern would be a modicum of a decent quality of life for all (especially for children) rather than the unending quest for individual riches. Excessive urban inequalities have much in common with high crime rates: they are not direct functions of city size but rather reflections of many historical, economic, social, and cultural realities. Disparities in Tokyo are obvious but not revolting; Hong Kong, despite its strong social net, has a high level of inequality; and Africa and Latin America have cities with immense gaps between poverty and affluence. Johannesburg has an exceptionally high Gini coefficient in excess of 0.75; other capitals of inequality include Ethiopia’s Addis Ababa (Gini at about 0.6), Colombia’s Bogotá, Kenya’s Nairobi, Mexico City, Peru’s Quito, and Ghana’s Accra (Hugo 2015).

Cities Under Siege: The New Military Urbanism by Stephen Graham

"hyperreality Baudrillard"~20 OR "Baudrillard hyperreality", addicted to oil, airport security, Alan Greenspan, Anthropocene, anti-communist, autonomous vehicles, Berlin Wall, call centre, carbon footprint, clean tech, clean water, congestion charging, creative destruction, credit crunch, DARPA: Urban Challenge, defense in depth, deindustrialization, digital map, disinformation, Dr. Strangelove, driverless car, edge city, energy security, European colonialism, export processing zone, failed state, Food sovereignty, gentrification, Gini coefficient, global supply chain, Global Witness, Google Earth, illegal immigration, income inequality, knowledge economy, late capitalism, Lewis Mumford, loose coupling, machine readable, market fundamentalism, mass incarceration, McMansion, megacity, military-industrial complex, moral panic, mutually assured destruction, Naomi Klein, New Urbanism, offshore financial centre, one-state solution, pattern recognition, peak oil, planetary scale, post-Fordism, private military company, Project for a New American Century, RAND corporation, RFID, Richard Florida, Scramble for Africa, Seymour Hersh, Silicon Valley, SimCity, smart transportation, surplus humans, The Bell Curve by Richard Herrnstein and Charles Murray, urban decay, urban planning, urban renewal, urban sprawl, Washington Consensus, white flight, white picket fence

Many economists would concur with Giovanni Andrea Cornia when he argues that ‘most of the recent surge in income polarization [within nations] would appear to be related to the policy drive towards domestic deregulation and external liberalization.’19 This has tended to concentrate wealth within social classes, corporations and locations that are capable of profiting from privatization and the extension of finance capital, while undermining wages, wealth and security for more marginalized people and places. In the US, for example, the Gini coefficient – the best measure of social inequality – rose from an already high level of 0.394 in 1970 to 0.462 in 2000. (A Gini score of 0 indicates perfect equality, with everyone having the the same income; a score of 1 represents perfect inequality, with one person collecting all the income and everyone else having an income of zero. A score above 0.3 implies an extremely unequal society.) Social polarization in the US is thus now exceeded by only a handful of very poor countries in Africa and Latin America.20 By 2007, the income of the wealthiest fifth of the US population averaged $168,170 a year, while the poorest fifth scraped by on an average of $11,352.

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Its income inequality – again measured by the Gini coefficient – has risen dramatically since the early 1960s, with the remodelling of the economy through radical re-regulation, privatization and neoliberalization (Figure 1.3). For the richest 10 per cent of the UK population, incomes rose in real terms by 68 per cent between 1979 and 1995. Their collective income now matches that of the nation’s poorest 70 per cent. During the same period, incomes for the poorest 10 per cent of UK households actually fell by 8 per cent (not considering housing costs). This rapidly reversed reductions in inequality achieved during the post-war Keynesian boom in the UK.

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At the same time, according to Philip Bond in the Independent, ‘the speculative capital that could be deployed or invested by the bottom 50 per cent of the British population fell from 12 per cent to just 1 per cent’.24 1.3 Radical growth in income inequality in the UK between 1961 and 2002/3 for income before housing costs (BHC) and after housing costs (AHC), as measured by the Gini coefficient. The imposition of market fundamentalism had particularly spectacular effects on the ex-Communist Comecon block after the collapse of communism in the late 1980s. Not only did this create a handful of billionaires and oligarchs but, at the same time, it increased the number of people living in poverty and deep insecurity from three million in 1988 to 170 million in 2004.25 Globally, by 2007, well over a billion people – a third of all urban dwellers – were leading a highly precarious existence in fast-growing slums and informal settlements.26 Increasingly, the developing world has come to be dominated by immiserized shanty-town populations whose daily insecurities encourage a receptivity to radical, violently anti-Western ideologies and movements.

The Spirit Level: Why Greater Equality Makes Societies Stronger by Richard Wilkinson, Kate Pickett

"Hurricane Katrina" Superdome, basic income, Berlin Wall, classic study, clean water, Diane Coyle, epigenetics, experimental economics, experimental subject, Fall of the Berlin Wall, full employment, germ theory of disease, Gini coefficient, God and Mammon, impulse control, income inequality, Intergovernmental Panel on Climate Change (IPCC), knowledge economy, labor-force participation, land reform, longitudinal study, Louis Pasteur, meta-analysis, Milgram experiment, mirror neurons, moral panic, Murray Bookchin, offshore financial centre, phenotype, plutocrats, profit maximization, profit motive, Ralph Waldo Emerson, statistical model, The Chicago School, The Spirit Level, The Wealth of Nations by Adam Smith, Thorstein Veblen, ultimatum game, upwardly mobile, World Values Survey, zero-sum game

We use the ratio of the income received by the top to the bottom 20 per cent whenever we are comparing inequality in different countries: it is easy to understand and it is one of the measures provided ready-made by the United Nations. When comparing inequality in US states, we use the Gini coefficient: it is the most common measure, it is favoured by economists and it is available from the US Census Bureau. In many academic research papers we and others have used two different inequality measures in order to show that the choice of measures rarely has a significant effect on results. DOES THE AMOUNT OF INEQUALITY MAKE A DIFFERENCE? Having got to the end of what economic growth can do for the quality of life and facing the problems of environmental damage, what difference do the inequalities shown in Figure 2.1 make?

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2 There are lots of ways of measuring income inequality and they are all so closely related to each other that it doesn’t usually make much difference which you use. Instead of the top and bottom 20 per cent, we could compare the top and bottom 10 or 30 per cent. Or we could have looked at the proportion of all incomes which go to the poorer half of the population. Typically, the poorest half of the population get something like 20 or 25 per cent of all incomes and the richest half get the remaining 75 or 80 per cent. Other more sophisticated measures include one called the Gini coefficient. It measures inequality across the whole society rather than simply comparing the extremes.

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It measures inequality across the whole society rather than simply comparing the extremes. If all income went to one person (maximum inequality) and everyone else got nothing, the Gini coefficient would be equal to 1. If income was shared equally and everyone got exactly the same (perfect equality), the Gini would equal 0. The lower its value, the more equal a society is. The most common values tend to be between 0.3 and 0.5. Another measure of inequality is called the Robin Hood Index because it tells you what proportion of a society’s income would have to be taken from the rich and given to the poor to get complete equality. To avoid being accused of picking and choosing our measures, our approach in this book has been to take measures provided by official agencies rather than calculating our own.

The Levelling: What’s Next After Globalization by Michael O’sullivan

"World Economic Forum" Davos, 3D printing, Airbnb, Alan Greenspan, algorithmic trading, Alvin Toffler, bank run, banking crisis, barriers to entry, Bernie Sanders, Big Tech, bitcoin, Black Swan, blockchain, bond market vigilante , Boris Johnson, Branko Milanovic, Bretton Woods, Brexit referendum, British Empire, business cycle, business process, capital controls, carbon tax, Celtic Tiger, central bank independence, classic study, cloud computing, continuation of politics by other means, corporate governance, credit crunch, CRISPR, cryptocurrency, data science, deglobalization, deindustrialization, disinformation, disruptive innovation, distributed ledger, Donald Trump, driverless car, eurozone crisis, fake news, financial engineering, financial innovation, first-past-the-post, fixed income, gentrification, Geoffrey West, Santa Fe Institute, Gini coefficient, Glass-Steagall Act, global value chain, housing crisis, impact investing, income inequality, Intergovernmental Panel on Climate Change (IPCC), It's morning again in America, James Carville said: "I would like to be reincarnated as the bond market. You can intimidate everybody.", junk bonds, knowledge economy, liberal world order, Long Term Capital Management, longitudinal study, low interest rates, market bubble, minimum wage unemployment, new economy, Northern Rock, offshore financial centre, open economy, opioid epidemic / opioid crisis, Paris climate accords, pattern recognition, Peace of Westphalia, performance metric, Phillips curve, private military company, quantitative easing, race to the bottom, reserve currency, Robert Gordon, Robert Shiller, Robert Solow, Ronald Reagan, Scramble for Africa, secular stagnation, Silicon Valley, Sinatra Doctrine, South China Sea, South Sea Bubble, special drawing rights, Steve Bannon, Suez canal 1869, supply-chain management, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, total factor productivity, trade liberalization, tulip mania, Valery Gerasimov, Washington Consensus

In fact, there is a weak correlation between the extent to which a country is globalized and its level of inequality, and many of the more highly globalized countries have decent social welfare systems that mitigate inequalities. For instance, Ireland is more globalized than its close neighbor England but has a lower inequality score. The most commonly used measurement of inequality is the Gini coefficient, which measures how skewed or unequal the distribution of income is across a society. It has a value of zero if there is complete equality and of one if a single household has all the income. Typically, a score of above 0.31 signals higher inequality. According to the OECD website, the United States has a score of 0.39, which is very high compared to other countries.

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According to the OECD website, the United States has a score of 0.39, which is very high compared to other countries. Mexico has a Gini of 0.46. In contrast, Canada has a lower inequality score (Gini coefficient of 0.31) partly because it has a very different approach to policy making. Inequality is a concern in the developed world because it is persistent. In the context of low growth in incomes and wealth, the tensions associated with inequality are exacerbated. In emerging countries, inequality in income seems to be much less of a political and social issue, because with incomes and wealth growing at a relatively fast pace, people continue to expect to do better in the longer run, which is not the case in developed countries.

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Evidence from a range of sources—the World Bank, OECD, and Branko Milanovic, a leading academic in the areas of development economics and inequality—shows that across the developed world inequality is high, with the United States and South Africa in the lead in this respect, followed by Turkey, Chile, Israel, the United Kingdom, and Spain.17 Among other countries, Sweden has become slightly less equal though its Gini coefficient is nonetheless at a very low level, close to that of France, the Netherlands, and Canada. There are other ways of examining differences in income distribution. For example, according to the Economic Policy Institute,18 income inequality as captured by the share of income of the top 1 percent is now back to levels not seen since the 1920s.

How to Speak Money: What the Money People Say--And What It Really Means by John Lanchester

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, asset allocation, Basel III, behavioural economics, Bernie Madoff, Big bang: deregulation of the City of London, bitcoin, Black Swan, blood diamond, Bretton Woods, BRICs, business cycle, Capital in the Twenty-First Century by Thomas Piketty, Celtic Tiger, central bank independence, collapse of Lehman Brothers, collective bargaining, commoditize, creative destruction, credit crunch, Credit Default Swap, crony capitalism, Dava Sobel, David Graeber, disintermediation, double entry bookkeeping, en.wikipedia.org, estate planning, fear index, financial engineering, financial innovation, Flash crash, forward guidance, Garrett Hardin, Gini coefficient, Glass-Steagall Act, global reserve currency, high net worth, High speed trading, hindsight bias, hype cycle, income inequality, inflation targeting, interest rate swap, inverted yield curve, Isaac Newton, Jaron Lanier, John Perry Barlow, joint-stock company, joint-stock limited liability company, junk bonds, Kodak vs Instagram, Kondratiev cycle, Large Hadron Collider, liquidity trap, London Interbank Offered Rate, London Whale, loss aversion, low interest rates, margin call, McJob, means of production, microcredit, money: store of value / unit of account / medium of exchange, moral hazard, Myron Scholes, negative equity, neoliberal agenda, New Urbanism, Nick Leeson, Nikolai Kondratiev, Nixon shock, Nixon triggered the end of the Bretton Woods system, Northern Rock, offshore financial centre, oil shock, open economy, paradox of thrift, plutocrats, Ponzi scheme, precautionary principle, proprietary trading, purchasing power parity, pushing on a string, quantitative easing, random walk, rent-seeking, reserve currency, Richard Feynman, Right to Buy, road to serfdom, Ronald Reagan, Satoshi Nakamoto, security theater, shareholder value, Silicon Valley, six sigma, Social Responsibility of Business Is to Increase Its Profits, South Sea Bubble, sovereign wealth fund, Steve Jobs, survivorship bias, The Chicago School, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Tragedy of the Commons, trickle-down economics, two and twenty, Two Sigma, Tyler Cowen, Washington Consensus, wealth creators, working poor, yield curve

Canada Speaking purely for myself, quite a few places high on the left-hand list are places I have no desire to live, which probably reflects the fact that the per capita GDP figures are skewed towards small countries that either are rich in resources or are tax havens. Gini coefficient A numeric technique for measuring a society’s inequality. It’s used to measure income inequality in particular. A Gini coefficient of 0 would mean perfect equality, in which everyone had the same income; a Gini coefficient of 1 would be perfect inequality, in which one person had all the money and everybody else had nothing. Here are the top ten least-equal countries in the world, as measured by the CIA, with the most unequal at the top:39 1.

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The promise of neoliberalism is that that doesn’t matter, as long as the poor are getting richer too. A rising tide lifts all boats, as the cliché has it. It lifts the rich boats quicker, but in the neoliberal scheme of things that’s not a problem. Inequality isn’t just the price you pay for rising prosperity; inequality is what makes rising prosperity possible. The increase in inequality therefore isn’t just some nasty accidental side effect of neoliberalism; it’s the motor driving the whole economic process. During the third of a century in which neoliberalism has been the dominant economic model, almost nobody has been willing to face this reality about the philosophical underpinnings of the system.

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The median is the person in the middle, with 50 percent above and 50 percent below. When the mean goes up and the median stays still, that is a sign of rising inequality. Imagine a football team whose star player gets a $1,000,000 pay raise. The team’s average pay will go up, but the median—the bloke in the middle—will be paid the same. That’s proof that inequality in the team has risen. In the Anglo-American world, the mean and the median have diverged sharply in the last few decades, as inequality has measurably increased. Only the people at the top are better-off; everyone else is finding life harder. In the United States there has been no increase in the median wage in the last three decades, even as average earnings have gone up sharply.

Crisis and Dollarization in Ecuador: Stability, Growth, and Social Equity by Paul Ely Beckerman, Andrés Solimano

banking crisis, banks create money, barriers to entry, business cycle, capital controls, Carmen Reinhart, carried interest, central bank independence, centre right, clean water, currency peg, declining real wages, disintermediation, financial intermediation, fixed income, floating exchange rates, Future Shock, Gini coefficient, income inequality, income per capita, labor-force participation, land reform, London Interbank Offered Rate, Mexican peso crisis / tequila crisis, microcredit, Money creation, money: store of value / unit of account / medium of exchange, offshore financial centre, old-boy network, open economy, pension reform, price stability, rent-seeking, school vouchers, seigniorage, trade liberalization, women in the workforce

Inequality and Poverty Ecuador’s recent crises have come in a context of high poverty and income inequality. Although Latin America as a whole has extremely high income inequality compared with other regions of the world, especially Europe and East Asia, Ecuador’s record is unenviable even within Latin America. Moreover, unlike some other Latin American countries, which combine high inequality with relatively high per-capita income, Ecuador’s inequality is accompanied by low per-capita income. As noted above, Ecuador’s Gini coefficient has worsened in recent years. Table 4.1 indicates that the headcount index of extreme poverty increased from 12 percent in 1995 to 17 percent in 1998, peaking at 21 per- ECUADOR: CRISIS, POVERTY, AND SOCIAL PROTECTION 131 cent in 1999.

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Unemployment has fallen heavily on the poorest groups: Among the poorest 20 percent of the population, the unemployment rate in November 1998 was 21 percent, which was almost double the then national average. In real terms, the income of a typical worker earning the minimum wage in the formal sector declined 10 percent from March 1998 to March 1999. Inequality also increased in a country that already had one of the highest levels of inequality in Latin America. The Gini coefficient increased more than 4 percentage points from 0.42 in 1994–95 to 0.47 in 1998 (Coraggio, Larrea, and Sánchez Maria Correia is a Lead Specialist on gender issues at the World Bank. The author gratefully acknowledges Wendy Cunningham and Maria Elena Ruiz Abril, both of the World Bank, for providing valuable unputs and feedback. 177 178 CRISIS AND DOLLARIZATION IN ECUADOR 2000).

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Poverty and inequality increased substantially during the crisis. The poverty headcount Suhas Parandekar is an Education Economist at the World Bank. Rob Vos is Deputy Rector and Professor of Finance and Development at the Institute of Social Studies, The Hague, and Professor of Economics at the Free University of Amsterdam. A consultant at the World Bank, Donald Winkler is affiliated with Inter-American Dialogue. 127 128 CRISIS AND DOLLARIZATION IN ECUADOR increased by 12 percentage points between 1995 and 1998 and by another 9 percentage points during 1999. The Gini coefficient of income inequality increased from 0.52 to 0.54 during the same period.1 The bottom quintile’s share of total consumption decreased from 5.3 percent in 1995 to 5.0 percent in 1999.2 Using a consumption-based poverty measure for 1999, the extreme poor—those who fall below the food poverty line— accounted for 20 percent of the total population, or 2.2 million people, and the poor accounted for 55 percent of the population, or 5.9 million people.

The Economics of Inequality by Thomas Piketty, Arthur Goldhammer

affirmative action, basic income, Capital in the Twenty-First Century by Thomas Piketty, collective bargaining, conceptual framework, deindustrialization, endogenous growth, Gini coefficient, income inequality, low skilled workers, means of production, middle-income trap, moral hazard, Pareto efficiency, purchasing power parity, Robert Solow, Simon Kuznets, Tax Reform Act of 1986, The Bell Curve by Richard Herrnstein and Charles Murray, very high income, working-age population

See also Taxes Flat tax, on capital, 64–65 France: attitudes toward inequality, 99; average and marginal rates of redistribution, 102, 102f; capital and labor shares of value added, 41t; effective minimum wage, 110–111; Generalized Social Contribution, 34, 38; household income sources, 6t; income inequality, 12–15, 12t, 24–25; income inequality (1870–1994), 16–17, 16t; income inequality, historical evolution of, 18–19, 22; minimum wage, 91; percentage of obligatory taxes, 101; profit share in, 49–55, 50t; social charges, 46–48; taxes receipts as percent of GDP, 44; unions in, 91–92; wage inequality, 8–11, 11t, 72–73 Freeman, Richard, 87–88 Friedman, Milton, 1, 3, 112 Generalized Social Contribution (CSG), in France, 34, 38 Geographic mobility, wage inequality and human capital, 96 Germany: employment, 24, 25; income inequality, 14; percentage of obligatory taxes, 101; profit share, 53; unions, 91–92; wage inequality, 10, 91, 99 Gini coefficient, 10 Globalization: market integration, 59–60; wage inequality, 73–74 Goolsbee, Austen, 107 Grameen Bank, 63 Grenelle Accords (1968), 49 Gross operating surplus (GOS), 42 Guaranteed basic income, 3, 23, 104, 112–113 Hamermesh, Daniel, 49 Health insurance: adverse selection and, 115; justifications for compulsory, 115–117; as percentage of social charges in 1966 France, 103 Herrnstein, Richard, 82, 87 Hidden underemployment, 25 Household size, income and, 12, 14, 22 Human capital: elasticity of supply of, 78–79, 82–83, 87, 107; measuring types of productivity and, 98; unequal distribution of, 58–60; wage inequality and, 88–89, 92–99 Human capital, structural causes of inequality, 78–79; affirmative action versus fiscal transfers, 86–88; discrimination in labor market and, 85–86; efficiency and, 79–81; inefficient social integration and, 83–84; role of family and education expenses, 81–83 Human capital theory, 66–68; globalization and wage inequality, 73–74; historical inequalities and, 68–69; rise of wage inequality since 1970, 70–71; skill-biased technological change and, 71–73, 76–77, 92; supply and demand and, 69–70 Incentives: basic income and, 113; credit markets and, 60, 62, 114; effects of redistribution on, 105–110; of households to save and invest, 35; human capital and investments, 78–88, 90, 93; of owners to accumulate capital and invest, 28–29 Income: distribution by deciles and centiles, 5–8, 6t; household size and, 12; inequality of, 12–16, 12t, 15t; inequality of, historical evolution, 17–25, 19f, 21t; left-right debate about inequality of, 1–3; types and distribution of, 5–8, 6t.

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Other indicators are also used in order to capture the overall inequality of the distribution and not just the gap between the extreme deciles: for instance, the Gini coefficient or the Theil and Atkinson indices (Morrisson, 1996, pp. 81–96). Nevertheless, interdecile indicators (such as P90/P10, D10/D1, P80/P20, etc.) are by far the simplest and most intuitive. The P90/P10 indicator has the merit of being available in reliable numbers for many countries, hence it will be cited frequently in this chapter. For a more complete view of wage inequality, one would need to include figures for public-sector wages in addition to private-sector wages.

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These very large disparities of wealth, much greater than wage and income inequalities, are also much less well known. Inequalities of wealth cannot be explained solely by inequalities of present and past income. Behavioral differences with respect to savings and accumulation also play a part (accounting for nearly half of wealth inequality in 1992, according to Lollivier and Verger [1996]). These specific difficulties of accounting for wealth inequality explain why measures of inequality are often limited to inequalities of wages and income. But the main reason why income inequality is always significantly greater than wage inequality is totally different: it comes from the fact that a majority of low-income households are households living on small pensions, often consisting of one person, whereas high-income households are generally couples, often with two earners and children living at home.

The Euro: How a Common Currency Threatens the Future of Europe by Joseph E. Stiglitz, Alex Hyde-White

"there is no alternative" (TINA), "World Economic Forum" Davos, Alan Greenspan, bank run, banking crisis, barriers to entry, battle of ideas, behavioural economics, Berlin Wall, Bretton Woods, business cycle, buy and hold, capital controls, carbon tax, Carmen Reinhart, cashless society, central bank independence, centre right, cognitive dissonance, collapse of Lehman Brothers, collective bargaining, corporate governance, correlation does not imply causation, credit crunch, Credit Default Swap, currency peg, dark matter, David Ricardo: comparative advantage, disintermediation, diversified portfolio, eurozone crisis, Fall of the Berlin Wall, fiat currency, financial innovation, full employment, George Akerlof, Gini coefficient, global supply chain, Great Leap Forward, Growth in a Time of Debt, housing crisis, income inequality, incomplete markets, inflation targeting, information asymmetry, investor state dispute settlement, invisible hand, Kenneth Arrow, Kenneth Rogoff, knowledge economy, light touch regulation, low interest rates, manufacturing employment, market bubble, market friction, market fundamentalism, Martin Wolf, Mexican peso crisis / tequila crisis, money market fund, moral hazard, mortgage debt, neoliberal agenda, new economy, open economy, paradox of thrift, pension reform, pensions crisis, price stability, profit maximization, purchasing power parity, quantitative easing, race to the bottom, risk-adjusted returns, Robert Shiller, Ronald Reagan, Savings and loan crisis, savings glut, secular stagnation, Silicon Valley, sovereign wealth fund, the payments system, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, transfer pricing, trickle-down economics, Washington Consensus, working-age population

We don’t have good data to see how these citizens are faring, but for a few countries, we do have data on what has been happening to inequality. These data suggest that indeed, many are facing hardship. In Spain, for instance, in the years before the crisis, inequality had been coming down, but by 2014, the Gini coefficient, a standard measure of income inequality, was about 9 percent over its 2007 level. In the case of Greece, the Gini coefficient increased by 5 percent from just 2010 to 2014. It usually takes years and years to move the Gini coefficient by a few percentage points. Data on poverty reinforce the conjecture that those in the middle and bottom have suffered particularly from the crisis.

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It does not, for instance, take into account the distribution of the benefits of growth: even in Germany, large fractions of the population have seen stagnation or even decreases in their incomes.26 From 1992 to 2010, the income share of the top 1 percent increased by about 24 percent;27 and from the mid-1980s until the mid-2000s, Germany’s Gini coefficient and poverty rates climbed steadily—the latter ultimately exceeding the average for the OECD countries.28 Germany’s success in achieving competitiveness came partly at the expense of those at the bottom, though it does a much better job of protecting those at the bottom than the United States does.29 While Germany is hardly the success that it would like to claim for itself, its modest success does not even provide a template for others.

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Indeed, central banks may have played an important role in increasing inequality. INCREASING INEQUALITY Today, in most countries around the world, inequality is viewed as one of the greatest threats to future prosperity. At Davos, where the world’s economic leaders come together every January, recent surveys of global risks have consistently placed inequality at or toward the top of the list.20 Inequality is important because divided societies don’t function well; it leads to a lack of cohesiveness that has political, economic, and social consequences. In my book The Price of Inequality, I explained the mechanisms by which greater inequality leads to poorer economic performance—lower growth and more instability.

Social Class in the 21st Century by Mike Savage

Bullingdon Club, call centre, Capital in the Twenty-First Century by Thomas Piketty, Clapham omnibus, Corn Laws, deindustrialization, deskilling, Downton Abbey, emotional labour, financial independence, gender pay gap, gentrification, Gini coefficient, income inequality, liberal capitalism, Mark Zuckerberg, megacity, meritocracy, moral panic, New Urbanism, Occupy movement, old-boy network, precariat, psychological pricing, Sloane Ranger, The Spirit Level, the strength of weak ties, unpaid internship, upwardly mobile, very high income, winner-take-all economy, young professional

In their highly influential book The Spirit Level, Richard Wilkinson and Kate Pickett use the standard metric to measure inequality between countries – the Gini coefficient – in the fifteen states who were members of the European Union prior to its major enlargement in 2004 and also the major industrial English-speaking countries of Australia, Canada and the USA.2 Figure 2.1 gives an indication of the inequalities within nations as they reflect the relative differences between countries in terms of earnings. The UK is a country of high gross income inequalities between households, coming second only to Ireland in the list of eighteen nations. Figure 2.1 shows also that those inequalities increased between 2008 and 2010 in the UK, as indeed they did in the vast majority of countries surveyed by the Organization for Economic Cooperation and Development (OECD).

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Mike Savage, Gaynor Bagnall and Brian Longhurst, Globalization and Belonging (London: 2005). CHAPTER 2: ACCUMULATING ECONOMIC CAPITAL 1. John Hills, Good Times, Bad Times: The Welfare Myth of Them and Us (Bristol: 2015), p. 37. 2. The Gini coefficient measures household income within a nation and reports a score between 0 (perfect equality) and 100 (complete inequality). For precise definition, see http://www.ons.gov.uk/ons/guide-method/method-quality/specific/social-and-welfare-methodology/the-gini-coefficient/index.html. 3. For overviews, see Peter Nolan, ‘Shaping the Future: The Political Economy of Work and Employment’, Industrial Relations Journal, 35(5), 2004, 378–87, and ‘The Changing World of Work’, Journal of Health Services Research and Policy, 9(suppl. 1), 2004, 3–9. 4.

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We will show that if we look at class in this way, we can detect a very different structure, one in which a small, wealthy elite class is pitted against a precariat with few resources, and between these two extremes there exist a patchwork of several other classes, all of which have their own distinctive mixes of capital, but none of which comes close to reaching the boundary which demarcates the top rank of the class hierarchy. The paradox of inequality We live with a fundamental paradox. The growth of economic inequality has been dramatic in recent decades. Britain is now more unequal than most comparable nations. Before taxation and welfare transfers, only Portugal and Ireland were more unequal among developed nations. Even after the mildly redistributive effect of taxation and welfare provision, Britain is still more unequal than most of its peers. Surveys show that this shift does not reflect popular perceptions about the legitimacy of inequality. Most people tend to be critical of inequality: 78 per cent of Britons are in favour of at least some forms of redistribution.1 However, when it comes to viewing their own lives, British people do not straightforwardly, or even at all, place themselves as winners and losers in this intense economic competition.

The Price of Time: The Real Story of Interest by Edward Chancellor

"World Economic Forum" Davos, 3D printing, activist fund / activist shareholder / activist investor, Airbnb, Alan Greenspan, asset allocation, asset-backed security, assortative mating, autonomous vehicles, balance sheet recession, bank run, banking crisis, barriers to entry, Basel III, Bear Stearns, Ben Bernanke: helicopter money, Bernie Sanders, Big Tech, bitcoin, blockchain, bond market vigilante , bonus culture, book value, Bretton Woods, BRICs, business cycle, capital controls, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, carried interest, cashless society, cloud computing, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, commodity super cycle, computer age, coronavirus, corporate governance, COVID-19, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, cryptocurrency, currency peg, currency risk, David Graeber, debt deflation, deglobalization, delayed gratification, Deng Xiaoping, Detroit bankruptcy, distributed ledger, diversified portfolio, Dogecoin, Donald Trump, double entry bookkeeping, Elon Musk, equity risk premium, Ethereum, ethereum blockchain, eurozone crisis, everywhere but in the productivity statistics, Extinction Rebellion, fiat currency, financial engineering, financial innovation, financial intermediation, financial repression, fixed income, Flash crash, forward guidance, full employment, gig economy, Gini coefficient, Glass-Steagall Act, global reserve currency, global supply chain, Goodhart's law, Great Leap Forward, green new deal, Greenspan put, high net worth, high-speed rail, housing crisis, Hyman Minsky, implied volatility, income inequality, income per capita, inflation targeting, initial coin offering, intangible asset, Internet of things, inventory management, invisible hand, Japanese asset price bubble, Jean Tirole, Jeff Bezos, joint-stock company, Joseph Schumpeter, junk bonds, Kenneth Rogoff, land bank, large denomination, Les Trente Glorieuses, liquidity trap, lockdown, Long Term Capital Management, low interest rates, Lyft, manufacturing employment, margin call, Mark Spitznagel, market bubble, market clearing, market fundamentalism, Martin Wolf, mega-rich, megaproject, meme stock, Michael Milken, Minsky moment, Modern Monetary Theory, Mohammed Bouazizi, Money creation, money market fund, moral hazard, mortgage debt, negative equity, new economy, Northern Rock, offshore financial centre, operational security, Panopticon Jeremy Bentham, Paul Samuelson, payday loans, peer-to-peer lending, pensions crisis, Peter Thiel, Philip Mirowski, plutocrats, Ponzi scheme, price mechanism, price stability, quantitative easing, railway mania, reality distortion field, regulatory arbitrage, rent-seeking, reserve currency, ride hailing / ride sharing, risk free rate, risk tolerance, risk/return, road to serfdom, Robert Gordon, Robinhood: mobile stock trading app, Satoshi Nakamoto, Satyajit Das, Savings and loan crisis, savings glut, Second Machine Age, secular stagnation, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, South Sea Bubble, Stanford marshmallow experiment, Steve Jobs, stock buybacks, subprime mortgage crisis, Suez canal 1869, tech billionaire, The Great Moderation, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thorstein Veblen, Tim Haywood, time value of money, too big to fail, total factor productivity, trickle-down economics, tulip mania, Tyler Cowen, Uber and Lyft, Uber for X, uber lyft, Walter Mischel, WeWork, When a measure becomes a target, yield curve