Nonparametric identification and estimation of random coefficients in multinomial choice models

• 成果类型: Article
• 署名作者: Fox, Jeremy T.; Gandhi, Amit
• 署名单位: Rice University; National Bureau of Economic Research; University of Wisconsin System; University of Wisconsin Madison
• 刊物名称: RAND JOURNAL OF ECONOMICS
• ISSN/ISSBN: 0741-6261
• DOI: 10.1111/1756-2171.12125
• 发表日期: 2016
• 页码: 118-139
• 关键词: simultaneous-equations models; demand; MARKET

摘要

We show how to nonparametrically identify the distribution of unobservables, such as random coefficients, that characterizes the heterogeneity among consumers in multinomial choice models. We provide general identification conditions for a class of nonlinear models and then verify these conditions using the primitives of the multinomial choice model. We require that the distribution of unobservables lie in the class of all distributions with finite support, which under our most general assumptions, resembles a product space where some of the product members are function spaces. We show how identification leads to the consistency of a nonparametric estimator.