Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model
研究了人们在信息获取有成本时如何选择离散行动，发现最优策略会导致概率选择符合广义多项Logit模型，该模型依赖于真实收益和先验信念。
Individuals must often choose among discrete actions with imperfect information about their payoffs. Before choosing, they have an opportunity to study the payoffs, but doing so is costly. This creates new choices such as the number of and types of questions to ask. We model these situations using the rational inattention approach to information frictions. We find that the decision maker's optimal strategy results in choosing probabilistically in line with a generalized multinomial logit model, which depends both on the actions' true payoffs as well as on prior beliefs.