From Aggregate Betting Data to Individual Risk Preferences
证明，即使没有个体决策数据，也能从风险资产市场均衡的加总条件中识别个体风险态度的分布。以赛马博彩为例，估计美国数据发现期望效用模型拟合很差，强调非线性概率加权的重要性。
We show that even in the absence of data on individual decisions, the distribution of individual attitudes towards risk can be identified from the aggregate conditions that characterize equilibrium on markets for risky assets. Taking parimutuel horse races as a textbook model of contingent markets, we allow for heterogeneous bettors with very general risk preferences, including non-expected utility. Under a standard single-crossing condition on preferences, we identify the distribution of preferences among the population of bettors and we derive testable implications. We estimate the model on data from U.S. races. Specifications based on expected utility fit the data very poorly. Our results stress the crucial importance of nonlinear probability weighting. They also suggest that several dimensions of heterogeneity may be at work.