There is evidence that people do not fully take into account how other people's actions depend on these other people's information. This paper defines and applies a new equilibrium concept in games with private information, cursed equilibrium, which assumes that each player correctly predicts the distribution of other players' actions, but underestimates the degree to which these actions are correlated with other players' information. We apply the concept to common-values auctions, where cursed equilibrium captures the widely observed phenomenon of the winner's curse, and to bilateral trade, where cursedness predicts trade in adverse-selections settings for which conventional analysis predicts no trade. We also apply cursed equilibrium to voting and signalling models. We test a single-parameter variant of our model that embeds Bayesian Nash equilibrium as a special case and find that parameter values that correspond to cursedness fit a broad range of experimental datasets better than the parameter value that corresponds to Bayesian Nash equilibrium. Copyright The Econometric Society 2005.

In social-learning environments, we investigate implications of the assumption that people naïvely believe that each previous person's action reflects solely that person's private information. Naïve herders inadvertently over-weight early movers' private signals by neglecting that interim herders' actions also embed these signals. Such “social confirmation bias” leads them to herd with positive probability on incorrect actions even in extremely rich-information settings where rational players never do. Moreover, because they become fully confident even when wrong, naïve herders can be harmed, on average, by observing others. (JEL D82, D83)

Banning affirmative action from college admissions cannot prevent an admissions office that cares about diversity from achieving it in ways other than explicitly considering race. We model college admissions where candidates from two groups with different average qualiÞcations compete for a Þxed number of seats. Under affirmative action, an admissions office that cares both about quality and diversity admits the best-qualiÞed candidates from each group. Under a ban, it may promote diversity by partially ignoring candidates' qualiÞcations and therefore not admitting the best-qualiÞed candidates from either group. A ban always reduces diversity and may also lower quality. (JEL J71, J15, I28)

Rationality leads people to imitate those with similar tastes but different information. But people who imitate common sources develop correlated beliefs, and rationality demands that later social learners take this redundancy into account. This implies severe limits to rational imitation. We show that (i) in most natural observation structures besides the canonical single-file case, full rationality dictates that people must "anti-imitate" some of those they observe; and (ii) in every observation structure full rationality dictates that people who do not anti-imitate can, in essence, imitate at most one person among predecessors who share common information. We also show that in a very broad class of settings, virtually any learning rule in which people regularly do imitate more than one person without anti-imitating others will lead to a positive (and, in some environments, arbitrarily high) probability of people converging to confident and wrong long-run beliefs. When testing either the rationality or the efficiency of social learning, researchers should not focus on whether people follow others' behavior-but instead whether they follow it too much. (JEL B49) * We thank Paul Heidhues, seminar participants at Berkeley, DIW Berlin, Hebrew University, ITAM, LSE, Oxford, Penn, Tel Aviv University, and WZB, as well as the editor and referees, for their comments. We are grateful to the Russell Sage Foundation for its hospitality, and Katie Winograd and especially Claire Gabriel for their help with the historical literature on treating syphilis and other medical practices, and Tristan Gagnon-Bartsch and Min Zhang for excellent research assistance.