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FROM AGGREGATE BETTING DATA TO INDIVIDUAL RISK PREFERENCES
by
Chiappori, Pierre-André
, Gandhi, Amit
, Salanié, Bernard
, Salanié, François
in
Aggregate data
/ Attitudes
/ attitudes towards risk
/ Economic models
/ Economics and Finance
/ Expected utility
/ Heterogeneity
/ Humanities and Social Sciences
/ Identification
/ Markets
/ Population distribution
/ revealed preferences
/ Risk
/ Risk preferences
/ Weighting
2019
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FROM AGGREGATE BETTING DATA TO INDIVIDUAL RISK PREFERENCES
by
Chiappori, Pierre-André
, Gandhi, Amit
, Salanié, Bernard
, Salanié, François
in
Aggregate data
/ Attitudes
/ attitudes towards risk
/ Economic models
/ Economics and Finance
/ Expected utility
/ Heterogeneity
/ Humanities and Social Sciences
/ Identification
/ Markets
/ Population distribution
/ revealed preferences
/ Risk
/ Risk preferences
/ Weighting
2019
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Do you wish to request the book?
FROM AGGREGATE BETTING DATA TO INDIVIDUAL RISK PREFERENCES
by
Chiappori, Pierre-André
, Gandhi, Amit
, Salanié, Bernard
, Salanié, François
in
Aggregate data
/ Attitudes
/ attitudes towards risk
/ Economic models
/ Economics and Finance
/ Expected utility
/ Heterogeneity
/ Humanities and Social Sciences
/ Identification
/ Markets
/ Population distribution
/ revealed preferences
/ Risk
/ Risk preferences
/ Weighting
2019
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FROM AGGREGATE BETTING DATA TO INDIVIDUAL RISK PREFERENCES
Journal Article
FROM AGGREGATE BETTING DATA TO INDIVIDUAL RISK PREFERENCES
2019
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Overview
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.
Publisher
Econometric Society,Blackwell Publishing Ltd
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