Random Choice and Learning

• 成果类型: Article
• 署名作者: Natenzon, Paulo
• 署名单位: Washington University (WUSTL)
• 刊物名称: JOURNAL OF POLITICAL ECONOMY
• ISSN/ISSBN: 0022-3808
• DOI: 10.1086/700762
• 发表日期: 2019
• 页码: 419-457
• 关键词: Stochastic choice; rational inattention; decision-making; attraction; VIOLATIONS; Similarity

摘要

Context-dependent individual choice challenges the principle of utility maximization. I explain context dependence as the optimal response of an imperfectly informed agent to the ease of comparison of the options. I introduce a discrete choice model, the Bayesian probit, which allows the analyst to identify stable preferences from context-dependent choice data. My model accommodates observed behavioral phenomena-including the attraction and compromise effects-that lie beyond the scope of any random utility model. I use data from frog mating choices to illustrate how the model can outperform the random utility framework in goodness of fit and out-of-sample prediction.