Snowberg gratefully acknowledges the support of NSF grants SES-1156154 and SMA-1329195. Yariv gratefully acknowledges the support of NSF grant SES-0963583 and the Gordon and Betty Moore Foundation grant 1158. We thank Marco Castillo, Yoram Halevy, Muriel Niederle, and Lise Vesterlund for comments and suggestions, as well as seminar audiences at Caltech, SITE, and UBC. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.
Without heterogeneity in ideology-preferences and opinions over political actions-there would be little need for the institutions studied by political economists.1 However, the sources of ideology have received scant attention: since Marx, political economists have largely viewed ideology as driven by wealth or income-despite the fact that these variables explain little of the variation in ideology ( This paper proposes a complementary theory in which differences in ideology are also due to imperfect information processing. This theory predicts that overconfidence in one's own beliefs leads to ideological extremeness, increased voter 1 Without heterogeneity, institutions will still be useful for coordination (Weingast 1997). Traditionally, opinions have not been considered part of ideology; however, recent work has provided compelling arguments that ideology should include some beliefs (McMurray 2013a, b).
The favorite-long shot bias describes the long-standing empirical regularity that betting odds provide biased estimates of the probability of a horse winning: long shots are overbet whereas favorites are underbet. Neoclassical explanations of this phenomenon focus on rational gamblers who overbet long shots because of risk-love. The competing behavioral explanations emphasize the role of misperceptions of probabilities. We provide novel empirical tests that can discriminate between these competing theories by assessing whether the models that explain gamblers' choices in one part of their choice set (betting to win) can also rationalize decisions over a wider choice set, including compound bets in the exacta, quinella, or trifecta pools. Using a new, large-scale data set ideally suited to implement these tests, we find evidence in favor of the view that misperceptions of probability drive the favorite-long shot bias, as suggested by prospect theory. We thank David Siegel of Equibase for supplying the data, and Scott Hereld and Ravi Pillai for their valuable assistance in managing the data.
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