Distinguishing Probability Weighting from Risk Misperceptions in Field Data

Authors

Levon Barseghyan, Cornell University
Francesca Molinari, Cornell University
Ted O'Donoghue, Cornell University
Joshua C. Teitelbaum, Georgetown University Law CenterFollow

Document Type

Article

Publication Date

2013

Abstract

The paper outlines a strategy for distinguishing rank-dependent probability weighting from systematic risk misperceptions in field data. Our strategy relies on singling out a field environment with two key properties: (i) the objects of choice are money lotteries with more than two outcomes and (ii) the ranking of outcomes differs across lotteries. We first present an abstract model of risky choice that elucidates the identification problem and our strategy. The model has numerous applications, including insurance choices and gambling. We then consider the application of insurance deductible choices and illustrate our strategy using simulated data.

Comments

doi:http://www.aeaweb.org/articles.php?doi=10.1257/aer.103.3.580

Publication Citation

103 Am. Econ. Rev. Papers & Proceedings 580-585 (2013)

Scholarly Commons Citation

Barseghyan, Levon; Molinari, Francesca; O'Donoghue, Ted; and Teitelbaum, Joshua C., "Distinguishing Probability Weighting from Risk Misperceptions in Field Data" (2013). Georgetown Law Faculty Publications and Other Works. 1155.
https://scholarship.law.georgetown.edu/facpub/1155