Distinguishing Probability Weighting from Risk Misperceptions in Field Data | Zendy

Levon Barseghyan | Zendy; Francesca Molinari | Zendy; Ted O’Donoghue | Zendy; Joshua C. Teitelbaum | Zendy

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Distinguishing Probability Weighting from Risk Misperceptions in Field Data

Author(s) -

Levon Barseghyan,

Francesca Molinari,

Ted O’Donoghue,

Joshua C. Teitelbaum

Publication year - 2013

Publication title -

american economic review

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 16.936

H-Index - 297

eISSN - 1944-7981

pISSN - 0002-8282

DOI - 10.1257/aer.103.3.580

Subject(s) - weighting , ranking (information retrieval) , econometrics , economics , identification (biology) , actuarial science , deductible , field (mathematics) , rank (graph theory) , key (lock) , computer science , mathematics , artificial intelligence , medicine , computer security , botany , combinatorics , pure mathematics , radiology , biology

We outline 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.

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