Distinguishing Probability Weighting from Risk Misperceptions in Field Data
提出一种策略，利用多结果彩票和结果排序差异，在实地数据中区分概率加权与系统性风险误解，并用保险免赔额选择的模拟数据说明。
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.