From Aggregate Betting Data to Individual Risk Preferences∗

As a textbook model of contingent markets, horse races are an attractive environ-ment to study the attitudes towards risk of bettors. We innovate on the literature by explicitly considering heterogeneous bettors and allowing for very general risk prefer-ences, including non-expected utility. We build on a standard single-crossing condition on preferences to derive testable implications; and we show how parimutuel data allow us to uniquely identify the distribution of preferences among the population of bettors. We then estimate the model on data from US races. Within the expected utility class, the most usual specifications (CARA and CRRA) fit the data very badly. Our results show evidence for both heterogeneity and nonlinear probability weighting. ∗This paper was first circulated and presented under the title ”What you are is what you bet: eliciting risk attitudes from horse races. ” We thank many seminar audiences for their comments. We are especially grateful to Jeffrey Racine for advice on nonparametric and semiparametric approaches, and to Simon Wood for help with his R package mgcv. Bernard Salanie ́ thanks the Georges Meyer endowment for its support during a leave at the Toulouse School of Economics. Pierre Andre Chiappori gratefully acknowledges financial support from NSF (Award 1124277.