first-price auction

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pages: 1,535 words: 337,071

Networks, Crowds, and Markets: Reasoning About a Highly Connected World by David Easley, Jon Kleinberg

Albert Einstein, AltaVista, clean water, conceptual framework, Daniel Kahneman / Amos Tversky, Douglas Hofstadter, Erdős number, experimental subject, first-price auction, fudge factor, George Akerlof, Gerard Salton, Gerard Salton, Gödel, Escher, Bach, incomplete markets, information asymmetry, information retrieval, John Nash: game theory, Kenneth Arrow, longitudinal study, market clearing, market microstructure, moral hazard, Nash equilibrium, Network effects, Pareto efficiency, Paul Erdős, planetary scale, prediction markets, price anchoring, price mechanism, prisoner's dilemma, random walk, recommendation engine, Richard Thaler, Ronald Coase, sealed-bid auction, search engine result page, second-price auction, second-price sealed-bid, Simon Singh, slashdot, social web, Steve Jobs, stochastic process, Ted Nelson, The Market for Lemons, The Wisdom of Crowds, trade route, transaction costs, ultimatum game, Vannevar Bush, Vickrey auction, Vilfredo Pareto, Yogi Berra, zero-sum game

In other words, truthful bidding is a good idea even if the competing bidders in the auction don’t know that they ought to be bidding truthfully as well. We now turn to first-price auctions, where we’ll find that the situation is much more complex. In particular, each bidder now has to reason about the behavior of her competitors in order to arrive at an optimal choice for her own bid. 9.5. FIRST-PRICE AUCTIONS AND OTHER FORMATS 267 9.5 First-Price Auctions and Other Formats In a sealed-bid first-price auction, the value of your bid not only affects whether you win but also how much you pay. As a result, most of the reasoning from the previous section has to be redone, and the conclusions are now different. To begin with, we can set up the first-price auction as a game in essentially the same way that we did for second-price auctions. As before, bidders are players, and each bidder’s strategy is an amount to bid as a function of her true value.

First, the discussion in this section shows that when we analyze bidder behavior in sealed-bid auctions, we’re also learning about their interactive analogues — with the descending-bid auction as the analogue of the sealed-bid first-price auction, and the ascending-bid auction as the analogue of the sealed-bid second-price auction. Second, a purely superficial comparison of the first-price and second-price sealed-bid 264 CHAPTER 9. AUCTIONS auctions might suggest that the seller would get more money for the item if he ran a first-price auction: after all, he’ll get paid the highest bid rather than the second-highest bid. It may seem strange that in a second-price auction, the seller is intentionally undercharging the bidders. But such reasoning ignores one of the main messages from our study of game theory — that when you make up rules to govern people’s behavior, you have to assume that they’ll adapt their behavior in light of the rules. Here, the point is that bidders in a first-price auction will tend to bid lower than they do in a second-price auction, and in fact this lowering of bids will tend to offset what would otherwise look like a difference in the size of the winning bid.

Finding the optimal trade-off between these two factors is a complex problem that depends on knowledge of the other bidders and their distribution of possible values. For example, it is intuitively natural that your bid should be higher — i.e. shaded less, closer to your true value — in a first-price auction with many competing bidders than in a first-price auction with only a few competing bidders (keeping other properties of the bidders the same). This is simply because with a large pool of other bidders, the highest competing bid is likely to be larger, and hence you need to bid higher to get above this and be the highest bid. We will discuss how to determine the optimal bid for a first-price auction in Section 9.7. All-pay auctions. There are other sealed-bid auction formats that arise in different settings. One that initially seems counter-intuitive in its formulation is the all-pay auction: each bidder submits a bid; the highest bidder receives the item; and all bidders pay their bids, regardless of whether they win or lose.

pages: 543 words: 153,550

Model Thinker: What You Need to Know to Make Data Work for You by Scott E. Page

"Robert Solow", Airbnb, Albert Einstein, Alfred Russel Wallace, algorithmic trading, Alvin Roth, assortative mating, Bernie Madoff, bitcoin, Black Swan, blockchain, business cycle, Capital in the Twenty-First Century by Thomas Piketty, Checklist Manifesto, computer age, corporate governance, correlation does not imply causation, cuban missile crisis, deliberate practice, discrete time, distributed ledger,, Estimating the Reproducibility of Psychological Science, Everything should be made as simple as possible, experimental economics, first-price auction, Flash crash, Geoffrey West, Santa Fe Institute, germ theory of disease, Gini coefficient, High speed trading, impulse control, income inequality, Isaac Newton, John von Neumann, Kenneth Rogoff, knowledge economy, knowledge worker, Long Term Capital Management, loss aversion, low skilled workers, Mark Zuckerberg, market design, meta analysis, meta-analysis, money market fund, Nash equilibrium, natural language processing, Network effects, p-value, Pareto efficiency, pattern recognition, Paul Erdős, Paul Samuelson, phenotype, pre–internet, prisoner's dilemma, race to the bottom, random walk, randomized controlled trial, Richard Feynman, Richard Thaler, school choice, sealed-bid auction, second-price auction, selection bias, six sigma, social graph, spectrum auction, statistical model, Stephen Hawking, Supply of New York City Cabdrivers, The Bell Curve by Richard Herrnstein and Charles Murray, The Great Moderation, The Rise and Fall of American Growth, the rule of 72, the scientific method, The Spirit Level, The Wisdom of Crowds, Thomas Malthus, Thorstein Veblen, urban sprawl, value at risk, web application, winner-take-all economy, zero-sum game

The same logic applies to all bidders, so all should bid their true values (the mechanism is incentive compatible). It follows that in a second-price auction, the bidder with the highest value wins the auction, and the amount paid equals the second-highest bidder’s value. In a first-price auction, each participant submits a bid, and the highest bid wins, with the bidder paying an amount equal to that bid. As in a second-price auction, the bids are submitted simultaneously, so no one knows the others’ bids. A participant’s optimal bidding strategy in a first-price auction depends on the participant’s belief about the values (and therefore the likely bids) of the other bidders. We will assume that bidders do not know other bidders’ values but that they do have correct beliefs about the distribution over those values. To be specific, we assume that the bidders’ values are uniformly distributed between zero and $100 and that all of the bidders know this distribution.

Other bidders not following optimal strategies could cause a bidder to have a higher or lower expected payoff, but they do not change the optimal strategy: a bidder should stay in as long as the price is less than her value. Similarly, in a second-price auction, a bidder should always follow the same strategy of bidding her true value. However, figuring out that truthful bidding is optimal requires multiple steps of logic. Recall that dominant strategies are optimal regardless of the strategies of others. Both ascending-bid and second-price auctions have dominant strategies. First-price auctions do not. In a first-price auction, changes in the bidding strategy of one bidder can change the optimal strategy for another bidder. If one bidder always bids either zero or 50, then the other bidder should always bid either 1 or 51. There would be no reason to bid 60 or 70 as the winner would pay more for the object than necessary. Given the behavior of the other bidder, whenever a bid of 60 wins the auction, so does a bid of 51.

In first- and second-price auctions, bidders make a single bid, which allows no opportunity for emotional appeals during the auction. Finally, in the first-price auction and the ascending-bid auction, the price equals the highest bid. In the second-price auction, it equals the second-highest bid. This leaves the appearance that the seller could have received a higher price and, in part, explains why governments do not use second-price auctions. Imagine the headline if a government received three bids for oil rights, one at $6 million, one at $8 million, and one at $12 million: “Government Gets $12 Million Bid but Sells Land for $8 Million.” Anyone who knows auction theory would know that had the government run a first-price auction or an ascending-bid auction, then the top bid would not have been $12 million. It would have been $8 million.

pages: 523 words: 143,139

Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian, Tom Griffiths

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In a Vickrey auction, on the other hand, honesty is the dominant strategy. This is the mechanism designer’s holy grail. You do not need to strategize or recurse. Now, it seems like the Vickrey auction would cost the seller some money compared to the first-price auction, but this isn’t necessarily true. In a first-price auction, every bidder is shading their bid down to avoid overpaying; in the second-price Vickrey auction, there’s no need to—in a sense, the auction itself is optimally shading their bid for them. In fact, a game-theoretic principle called “revenue equivalence” establishes that over time, the average expected sale price in a first-price auction will converge to precisely the same as in a Vickrey auction. Thus the Vickrey equilibrium involves the same bidder winning the item for the same price—without any strategizing by any of the bidders whatsoever.

they’re shading their bids based on their prediction of yours!: The equilibrium strategy for a sealed-bid first-price auction with two players is to bid exactly half what you think the item is worth. More generally, in this auction format with n players, you should bid exactly (n−1)⁄n times what you think the item is worth. Note that this strategy is the Nash equilibrium but is not a dominant strategy; that is to say, nothing is better if everyone else is doing it, too, but isn’t necessarily optimal under all circumstances. Caveat emptor. Also, if you don’t know the number of bidders in the auction, the optimal strategy gets complicated in a hurry; see, for instance, An, Hu, and Shum, “Estimating First-Price Auctions with an Unknown Number of Bidders: A Misclassification Approach.” Actually, even the seemingly clean results—(n−1)⁄n—require some serious assumptions, namely that the bidders are “risk neutral” and that their different values for the item are distributed evenly across some given range.

Meanwhile, governments use auctions to sell rights to bands of the telecommunications spectrum (such as cell phone transmission frequencies), raising tens of billions of dollars in revenue. In fact, many global markets, in everything from homes to books to tulips, operate via auctions of various styles. One of the simplest auction formats has each participant write down their bid in secret, and the one whose bid is highest wins the item for whatever price they wrote down. This is known as a “sealed-bid first-price auction,” and from an algorithmic game theory perspective there’s a big problem with it—actually, several. For one thing, there’s a sense in which the winner always overpays: if you value an item at $25 and I value it at $10, and we both bid our true valuations ($25 and $10), then you end up buying it for $25 when you could have had it for just a hair over $10. This problem, in turn, leads to another one, which is that in order to bid properly—that is, in order not to overpay—you need to predict the true valuation of the other players in the auction and “shade” your bid accordingly.

pages: 252 words: 73,131

The Inner Lives of Markets: How People Shape Them—And They Shape Us by Tim Sullivan

"Robert Solow", Airbnb, airport security, Al Roth, Alvin Roth, Andrei Shleifer, attribution theory, autonomous vehicles, barriers to entry, Brownian motion, business cycle, buy and hold, centralized clearinghouse, Chuck Templeton: OpenTable:, clean water, conceptual framework, constrained optimization, continuous double auction, creative destruction, deferred acceptance, Donald Trump, Edward Glaeser, experimental subject, first-price auction, framing effect, frictionless, fundamental attribution error, George Akerlof, Goldman Sachs: Vampire Squid, Gunnar Myrdal, helicopter parent, information asymmetry, Internet of things, invisible hand, Isaac Newton, iterative process, Jean Tirole, Jeff Bezos, Johann Wolfgang von Goethe, John Nash: game theory, John von Neumann, Joseph Schumpeter, Kenneth Arrow, late fees, linear programming, Lyft, market clearing, market design, market friction, medical residency, multi-sided market, mutually assured destruction, Nash equilibrium, Occupy movement, Pareto efficiency, Paul Samuelson, Peter Thiel,, pez dispenser, pre–internet, price mechanism, price stability, prisoner's dilemma, profit motive, proxy bid, RAND corporation, ride hailing / ride sharing, Robert Shiller, Robert Shiller, Ronald Coase, school choice, school vouchers, sealed-bid auction, second-price auction, second-price sealed-bid, sharing economy, Silicon Valley, spectrum auction, Steve Jobs, Tacoma Narrows Bridge, technoutopianism, telemarketer, The Market for Lemons, The Wisdom of Crowds, Thomas Malthus, Thorstein Veblen, trade route, transaction costs, two-sided market, uber lyft, uranium enrichment, Vickrey auction, Vilfredo Pareto, winner-take-all economy

Thus, supposing either of these parties receives two bids on one lot of 20 and 25 cents apiece, they would start the lot at 21 cents, at which price it would be given to the person sending the 25 cent order, unless some one present advanced, when they would continue to bid, stopping at the limit of 25 cents . . . Persons sending bids should give the number of the lots and the highest price they are willing to give, when the lot will be bought for them as low as possible consistent with the representation of other bids. In a live (first-price) auction, a bidder keeps raising his paddle until the price goes above what he’s willing to pay for the lot that’s up for bid. And what price do we expect the winner to ultimately pay? If there are just two bidders who value the lot at 20 and 25 cents, respectively, the first will stay in the running until the price hits 21 cents, at which point the gavel will fall. The lot goes to the buyer who values it for more, who gets the lot for “close” to the runner-up’s walk-away price.

Consider how it would have simplified John Henry’s job in making an offer on Matsuzaka. Suppose, for the sake of argument, that Henry set the value of the right to negotiate with Matsuzaka at $60 million. That is, for a price of $60 million, he’d take it. If it were a dollar more, he’d walk away. (Of course, we’ll never know what his walk-away price was, beyond the fact that it was above $51,111,111.11.) In a first-price auction, we’ve already seen that it’s not clear where Henry should set his bid—sure, it should be less than $60 million, but how much less? For each dollar you drop your bid, you’re less and less likely to come out on top. But then again, you’re a dollar richer if you do. In a second-bid auction, there would’ve been no such uncertainty as to what Henry should’ve bid. Start by asking whether it could’ve made sense for Henry to bid more than $60 million, just to make sure he won (and knowing he wouldn’t have had to pay the full amount anyway).

The Problems with Vickrey Auctions Vickrey probably wouldn’t have been troubled by the fact that online shoppers don’t care much for his auction; he was, after all, far more interested in allocation decisions of larger social consequence. But his design also sees scarce application in areas like government procurement, which had been Vickrey’s primary motivation for building something better than a first-price auction in the first place. Nor has the Vickrey auction seen much action in the sale of state assets, where it matters not just how much revenue is generated but also that the asset—whether an oil concession or wireless spectrum—goes to the bidder who values it the most (because, it is presumed, he will make the most productive use of it). This lack of use of the Vickrey auction was something of a puzzle to economists who were captivated by the way that, in its elegant simplicity, the mechanism helped magically cure the bidders’ headaches over strategizing and overpaying.

pages: 298 words: 43,745

Understanding Sponsored Search: Core Elements of Keyword Advertising by Jim Jansen

AltaVista, barriers to entry, Black Swan, bounce rate, business intelligence, butterfly effect, call centre, Claude Shannon: information theory, complexity theory, correlation does not imply causation,, first-price auction, information asymmetry, information retrieval, intangible asset, inventory management, life extension, linear programming, longitudinal study, megacity, Nash equilibrium, Network effects, PageRank, place-making, price mechanism, psychological pricing, random walk, Schrödinger's Cat, sealed-bid auction, search engine result page, second-price auction, second-price sealed-bid, sentiment analysis, social web, software as a service, stochastic process, telemarketer, the market place, The Present Situation in Quantum Mechanics, the scientific method, The Wisdom of Crowds, Vickrey auction, Vilfredo Pareto, yield management

A Generalized Second Price auction achieves this stability by encouraging advertisers to not bid too high as an adversarial technique (i.e., there is no use in bidding extremely high to try and force a competitor to bid higher, to really “win” the top space, etc.). From an overall auction perspective, this has the advantage of keeping the auction stable, with few wide or wild price swings once the auction reaches a point of stability. This is especially true relative to a first-price auction [22] (i.e., you pay what you bid). The first-price auction has no point of equilibrium or stability, so the bids can constantly be in flux. However, stability is a range, not an exact point, and there can be situations in a sponsored-search auction where it may be advantageous to bid somewhat higher than optimal to hurt a competitor [c.f., 23]. However, this strategy has limitations and beyond a certain bid point it becomes counterproductive, returning the auction to equilibrium.

On February 21, 1998, launched a sponsored-search model in which the search engines ranked “Web sites based on how much the sites are willing to pay to be placed at the top of the search under a real-time competitive bidding process [2].” Advertisements for these Web sites appeared on the search engine results page, and the ad displayed based on the searcher was actively seeking at the time. The conceptualization was relatively straightforward, with a transparent ranking factor (i.e., money), advertisers bidding on exact phrases, and editors checking for relevance. This concept is a first-price auction, where the top bidder gets the top advertising position. also provided nonsponsored listings, provided by Potpourri: was the rebranded search engine, World-Wide Web Worm, which was the first Web search engine. Created in September 1993 by Oliver McBryan at the University of Colorado, the World-Wide Web Worm is the grandfather of all Web search engines. It started it all!

Google’s first sponsored-search auction was in February 2002, adopting Overture’s pay-per-click revenue model, but they continued their sales-by-impression model in parallel [12] before finally dropping it altogether in favor of the pay-per-click model. Additionally, Google’s sponsored-search model was introduced with some significant changes relative to the Overture model. First, developers of Google’s AdWords platform changed the pricing scheme from a first-price auction to a more stable second-price auction. In a single-item second-price auction, the highest bidder wins but only pays the second-highest bid price plus some small delta, which is a fancy word for additional amount. (Note: We’ll discuss the significance of this in Chapter 8 where we cover bidding practices.) Second, Google also changed the standard allocation scheme. Instead of ranking advertisements by bid price alone, they computed a quality score derived from the bid amount and the click-through rate.

pages: 282 words: 80,907

Who Gets What — and Why: The New Economics of Matchmaking and Market Design by Alvin E. Roth

Affordable Care Act / Obamacare, Airbnb, algorithmic trading, barriers to entry, Berlin Wall, bitcoin, Build a better mousetrap, centralized clearinghouse, Chuck Templeton: OpenTable:, commoditize, computer age, computerized markets, crowdsourcing, deferred acceptance, desegregation, experimental economics, first-price auction, Flash crash, High speed trading, income inequality, Internet of things, invention of agriculture, invisible hand, Jean Tirole, law of one price, Lyft, market clearing, market design, medical residency, obamacare, proxy bid, road to serfdom, school choice, sealed-bid auction, second-price auction, second-price sealed-bid, Silicon Valley, spectrum auction, Spread Networks laid a new fibre optics cable between New York and Chicago, Steve Jobs, The Wealth of Nations by Adam Smith, two-sided market, uber lyft, undersea cable

In contrast, a sealed bid auction, in which you can’t see when the other bidders drop out, might make it risky to bid at all, since a company with an unrealistically high estimate of how much recoverable oil is in the ground might suffer the “winner’s curse”—that is, win the auction only because it overestimated the value of winning and paid too much. But first-price auctions, in which the winning bidder pays what she bids, have their own charms and exist in many varieties. One version of a first-price auction is used to sell cut flowers in bulk, in a “descending bid” auction. The auctioneer sets up a “clock” that has the current bid on it, starting with a very high bid and quickly descending, until some bidder stops the clock by offering the price it currently shows, which is higher than any of the other bidders have offered to pay, as they haven’t already stopped the clock.

Notice that while a second-price auction makes it safe for bidders to bid the true value to them, it doesn’t necessarily impose a cost on the seller, even though the seller receives only the amount of the second-highest bid. That’s because in a first-price sealed bid auction, for example, it isn’t safe for bidders to bid their true value; they have to bid less than that if they are going to make any profit, since if they win the auction, they will have to pay the full amount of their bid. So the seller in a first-price auction receives the amount of the highest bid, which is, however, less than the true value of the highest bidder. By comparison, in a second-price auction, the seller receives only the second-highest bid, but the bids are higher. That is, when the rules of the auction change, the bids change, too. In fact, there are reasons to think that these two effects balance out. The situation changes when you don’t know how much the object is worth to you.

pages: 272 words: 83,798

A Little History of Economics by Niall Kishtainy

"Robert Solow", Alvin Roth, British Empire, Capital in the Twenty-First Century by Thomas Piketty, car-free, central bank independence, clean water, Corn Laws, creative destruction, credit crunch, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, Eugene Fama: efficient market hypothesis, first-price auction, floating exchange rates, follow your passion, full employment, George Akerlof, greed is good, Hyman Minsky, inflation targeting, invisible hand, John Nash: game theory, John von Neumann, Joseph Schumpeter, Kenneth Arrow, loss aversion, market clearing, market design, means of production, moral hazard, Nash equilibrium, new economy, Occupy movement, Pareto efficiency, Paul Samuelson, prisoner's dilemma, RAND corporation, rent-seeking, Richard Thaler, rising living standards, road to serfdom, Robert Shiller, Robert Shiller, Ronald Reagan, sealed-bid auction, second-price auction, The Chicago School, The Great Moderation, The Market for Lemons, The Wealth of Nations by Adam Smith, Thomas Malthus, Thorstein Veblen, trade route, Vickrey auction, Vilfredo Pareto, washing machines reduced drudgery, wealth creators, Winter of Discontent

People are commonly scared of risky situations – those in which they have a chance of winning a lot or winning nothing. Shading your bid in a first-price sealed-bid auction is risky. If you bid £250,000 for a house that you value at £300,000 then you might win and make a £50,000 profit, but you might be outbid and end up with nothing. If you hate risk you’ll tend to shade less, perhaps bidding £290,000. In the first-price auction your aversion to risk makes you bid close to your true valuation, and that’s what you’ll pay if you win. In the second-price auction, you’d only have to pay the second-highest bid. In this case it’s possible that the seller would get more money in a first-price than a second-price auction. There are many different kinds of auctions in theory, but in the real world economists have to tailor their designs to the context.

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pages: 324 words: 93,175

The Upside of Irrationality: The Unexpected Benefits of Defying Logic at Work and at Home by Dan Ariely

Alvin Roth, assortative mating, Burning Man, business process, cognitive dissonance, corporate governance, Daniel Kahneman / Amos Tversky, end world poverty, endowment effect, Exxon Valdez, first-price auction, Frederick Winslow Taylor, George Akerlof, happiness index / gross national happiness, hedonic treadmill, IKEA effect, Jean Tirole, job satisfaction, knowledge economy, knowledge worker, loss aversion, Peter Singer: altruism, placebo effect, Richard Thaler, Saturday Night Live, second-price auction, software as a service, The Wealth of Nations by Adam Smith, ultimatum game, Upton Sinclair, young professional

Here is the logic: if the creators realized that they were uniquely overimpressed with their own frogs and cranes, they would bid more when using the second-price auction (when only their value matters) than when using the first-price auction (when they should also take into account the values of others). In contrast, if the creators did not realize that they were the only ones who overvalued their origami and they thought that others shared their perspective, they would bid a similarly high amount in both bidding procedures. So did the origami builders understand that others didn’t see their creations as they did? We found that creators bid the same amount when they considered only their own evaluation for the product (second-price auction) as when they also considered what noncreators would bid for it (first-price auction). The lack of difference between the two bidding approaches suggested not only that we overvalue our own creations but also that we are largely unaware of this tendency; we mistakenly think that others love our work as much as we do.

Mining of Massive Datasets by Jure Leskovec, Anand Rajaraman, Jeffrey David Ullman

cloud computing, crowdsourcing,, first-price auction, G4S, information retrieval, John Snow's cholera map, Netflix Prize, NP-complete, PageRank, pattern recognition, random walk, recommendation engine, second-price auction, sentiment analysis, social graph, statistical model, web application

Charging Advertisers for Clicks: In our simplified model, when a user clicks on an advertiser’s ad, the advertiser is charged the amount they bid. This policy is known as a first-price auction. In reality, search engines use a more complicated system known as a second-price auction, where each advertiser pays approximately the bid of the advertiser who placed immediately behind them in the auction. For example, the first-place advertiser for a search might pay the bid of the advertiser in second place, plus one cent. It has been shown that second-price auctions are less susceptible to being gamed by advertisers than first-price auctions and lead to higher revenues for the search engine. 8.4.5A Lower Bound on Competitive Ratio for Balance In this section we shall prove that in the simple case of the Balance Algorithm that we are considering, the competitive ratio is 3/4.

., 67 Ethernet, 19, 20 Euclidean distance, 87, 101, 452 Euclidean space, 87, 91, 228, 230, 233, 249 Exponentially decaying window, see Decaying window Extrapoliation, 450 Facebook, 16, 176, 326 Fact table, 50 Failure, 20, 26, 39, 40, 42 Faloutsos, C., 383, 414 False negative, 83, 93, 216 False positive, 83, 93, 132, 216 Family of functions, 94 Fang, M., 226 Fayyad, U.M., 265 Feature, 252, 297, 298 Feature selection, 421 Feature vector, 416, 455 Fetterly, D., 67 Fikes, A., 67 File, 21, 198, 215 Filtering, 130 Fingerprint, 107 First-price auction, 279 Fixedpoint, 96, 182 Flajolet, P., 153 Flajolet–Martin Algorithm, 134, 376 Flow graph, 39 Fortunato, S., 382 Fotakis, D., 382 French, J.C., 265 Frequent bucket, 208, 209 Frequent itemset, 4, 192, 201, 204, 340, 415 Frequent pairs, 202 Frequent-items table, 203 Freund, Y., 458 Friends, 326 Friends relation, 49 Frieze, A.M., 122 Frobenius norm, 388, 402 Furnas, G.W., 414 Gaber, M.M., 18 Ganti, V., 122, 265 Garcia-Molina, H., 18, 190, 226, 265, 382 Garofalakis, M., 153 Gaussian elimination, 159 Gehrke, J., 153, 265 Generalization, 421 Generated subgraph, 339 Genre, 297, 309, 321 GFS, see Google file system Ghemawat, S., 67 Gibbons, P.B., 153, 383 Gionis, A., 122, 153 Girvan, M., 382 Girvan–Newman Algorithm, 333 Global minimum, 314 GN Algorithm, see Girvan–Newman Algorithm Gobioff, H., 67 Golub, G.H., 414 Google, 155, 166, 276 Google file system, 22 Google+, 326 Gradient descent, 17, 320, 355, 442 Granzow, M., 414 Graph, 42, 54, 325, 326, 361, 368 Greedy algorithm, 270, 271, 274, 278 GRGPF Algorithm, 252 Grouping, 24, 31, 35 Grouping attribute, 31 Groupon, 329 Gruber, R.E., 67 Guha, S., 266 Gunda, P.K., 67 Gyongi, Z., 190 Hadoop, 22, 67 Hadoop distributed file system, 22 Hamming distance, 63, 91, 98 Harris, M., 321 Harshman, R., 414 Hash function, 8, 74, 78, 83, 129, 131, 134 Hash key, 9, 285 Hash table, 8, 10, 11, 200, 207, 209, 211, 285, 287, 362 Haveliwala, T.H., 190 HDFS, see Hadoop distributed file system Head, 372 Heavy hitter, 362 Henzinger, M., 122 Hierarchical clustering, 230, 232, 249, 310, 331 Hinge loss, 441 HITS, 182 Hive, 66, 67 Hopcroft, J.E., 374 Horn, H., 67 Howe, B., 67 Hsieh, W.C., 67 Hub, 182, 183 Hyperlink-induced topic search, see HITS Hyperplane, 436 Hyracks, 38 Identical documents, 111 Identity matrix, 386 IDF, see Inverse document frequency Image, 125, 297, 298 IMDB, see Internet Movie Database Imielinski, T., 226 Immediate subset, 218 Immorlica, N., 122 Important page, 155 Impression, 268 In-component, 159 Inaccessible page, 178 Independent rows or columns, 397 Index, 10, 362 Indyk, P., 122, 153 Initialize clusters, 242 Input, 54 Insertion, 90 Instance-based learning, 419 Interest, 196 Internet Movie Database, 297, 321 Interpolation, 450 Intersection, 31, 33, 38, 71 Into Thin Air, 295 Inverse document frequency, see also TF.IDF, 8 Inverted index, 155, 268 Ioannidis, Y.E., 382 IP packet, 125 Isard, M., 67 Isolated component, 160 Item, 191, 193, 194, 293, 308, 310 Item profile, 297, 299 Itemset, 191, 199, 201 Jaccard distance, 87, 88, 95, 298, 453 Jaccard similarity, 69, 77, 87, 177 Jacobsen, H.

The Armchair Economist: Economics and Everyday Life by Steven E. Landsburg

Albert Einstein, Arthur Eddington, business cycle, diversified portfolio, first-price auction, German hyperinflation, Golden Gate Park, information asymmetry, invisible hand, Kenneth Arrow, means of production, price discrimination, profit maximization, Ralph Nader, random walk, Ronald Coase, Sam Peltzman, sealed-bid auction, second-price auction, second-price sealed-bid, statistical model, the scientific method, Unsafe at Any Speed

The answer is yes if there happen to be two high bidders in the audience and no if Cursed Winners and Glum Losers 177 there happens to be just one. Because bidders are unlikely to reveal their bidding strategies in advance of the auction, the seller can never know for certain on any given night whether an English auction is preferable to, say, a Dutch auction. Even to decide between a first-price and a second-price sealed bid auction can be difficult for the seller. On the one hand, in a first-price auction he collects the high bid, while in a second-price auction he collects only the amount of the second-highest bid. On the other hand, bidders generally submit higher bids in a second-price auction. They submit even higher bids in a third-price auction. Which is best for the seller? Again the answer depends on who shows up to bid, and what the bidders' strategies are. Given his limited information, the seller is in no position to choose the rule that will maximize the selling price at any one auction.

pages: 350 words: 103,988

Reinventing the Bazaar: A Natural History of Markets by John McMillan

"Robert Solow", accounting loophole / creative accounting, Albert Einstein, Alvin Roth, Andrei Shleifer, Anton Chekhov, Asian financial crisis, congestion charging, corporate governance, corporate raider, crony capitalism, Dava Sobel, Deng Xiaoping, experimental economics, experimental subject, fear of failure, first-price auction, frictionless, frictionless market, George Akerlof, George Gilder, global village, Hernando de Soto, I think there is a world market for maybe five computers, income inequality, income per capita, informal economy, information asymmetry, invisible hand, Isaac Newton, job-hopping, John Harrison: Longitude, John von Neumann, Kenneth Arrow, land reform, lone genius, manufacturing employment, market clearing, market design, market friction, market microstructure, means of production, Network effects, new economy, offshore financial centre, ought to be enough for anybody, pez dispenser, pre–internet, price mechanism, profit maximization, profit motive, proxy bid, purchasing power parity, Ronald Coase, Ronald Reagan, sealed-bid auction, second-price auction, Silicon Valley, spectrum auction, Stewart Brand, The Market for Lemons, The Nature of the Firm, The Wealth of Nations by Adam Smith, trade liberalization, transaction costs, War on Poverty, Xiaogang Anhui farmers, yield management

An alternative way of running the bidding is the Dutch auction, used to sell flowers at Aalsmeer, in which the price starts high and falls until a bidder claims the item. Another is the sealed-bid auction, in which there is a single round of sealed bids; the high bidder wins and pays his or her bid. Commercial real estate is sometimes sold this way. A variant is the second-price auction, in which there is a single round of bidding and the high bidder wins, but unlike first-price auctions, the price paid is the second-highest bid. Second-price auctions are used for selling stamps. eBay chose open auctions. Economic theory endorses this decision: the open auction yields, on average, a price that is closer to the item’s true value than do the other forms of auction.3 This is because bidders have more information in an open auction. If you win, the level of your winning bid reflects others’ bids as well your own prior estimate of the item’s value.

pages: 898 words: 266,274

The Irrational Bundle by Dan Ariely

accounting loophole / creative accounting, air freight, Albert Einstein, Alvin Roth, assortative mating, banking crisis, Bernie Madoff, Black Swan, Broken windows theory, Burning Man, business process, cashless society, Cass Sunstein, clean water, cognitive dissonance, computer vision, corporate governance, credit crunch, Credit Default Swap, Daniel Kahneman / Amos Tversky, delayed gratification, Donald Trump, end world poverty, endowment effect, Exxon Valdez, first-price auction, Frederick Winslow Taylor, fudge factor, George Akerlof, Gordon Gekko, greed is good, happiness index / gross national happiness, hedonic treadmill, IKEA effect, Jean Tirole, job satisfaction, Kenneth Arrow, knowledge economy, knowledge worker, lake wobegon effect, late fees, loss aversion, Murray Gell-Mann, new economy, Peter Singer: altruism, placebo effect, price anchoring, Richard Feynman, Richard Thaler, Saturday Night Live, Schrödinger's Cat, second-price auction, Shai Danziger, shareholder value, Silicon Valley, Skype, software as a service, Steve Jobs, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, ultimatum game, Upton Sinclair, Walter Mischel, young professional

Here is the logic: if the creators realized that they were uniquely overimpressed with their own frogs and cranes, they would bid more when using the second-price auction (when only their value matters) than when using the first-price auction (when they should also take into account the values of others). In contrast, if the creators did not realize that they were the only ones who overvalued their origami and they thought that others shared their perspective, they would bid a similarly high amount in both bidding procedures. So did the origami builders understand that others didn’t see their creations as they did? We found that creators bid the same amount when they considered only their own evaluation for the product (second-price auction) as when they also considered what noncreators would bid for it (first-price auction). The lack of difference between the two bidding approaches suggested not only that we overvalue our own creations but also that we are largely unaware of this tendency; we mistakenly think that others love our work as much as we do.