Time Will Tell: Recovering Preferences When Choices Are Noisy
成果类型：
Article
署名作者：
Alos-Ferrer, Carlos; Fehr, Ernst; Netzer, Nick
署名单位：
University of Zurich
刊物名称：
JOURNAL OF POLITICAL ECONOMY
ISSN/ISSBN：
0022-3808
DOI：
10.1086/713732
发表日期：
2021
页码：
1828-1877
关键词：
摘要：
When choice is stochastic, revealed preference analysis often relies on random utility models. However, it is impossible to infer preferences without assumptions on the distribution of utility noise. We show that this difficulty can be overcome by using response time data. A simple condition on response time distributions ensures that choices reveal preferences without distributional assumptions. Standard models from economics and psychology generate data fulfilling this condition. Sharper results are obtained under symmetric or Fechnerian noise, where response times allow uncovering preferences or predicting choice probabilities out of sample. Application of our tools is simple and generates remarkable prediction accuracy.
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