A simple estimator for the distribution of random coefficients

• 成果类型: Article
• 署名作者: Fox, Jeremy T.; Kim, Kyoo Il; Ryan, Stephen P.; Bajari, Patrick
• 署名单位: University of Michigan System; University of Michigan; National Bureau of Economic Research; University of Minnesota System; University of Minnesota Twin Cities; Massachusetts Institute of Technology (MIT)
• 刊物名称: QUANTITATIVE ECONOMICS
• ISSN/ISSBN: 1759-7323
• DOI: 10.3982/QE49
• 发表日期: 2011
• 页码: 381-418
• 关键词: Random coefficients; mixtures; demand; logit; mixed logit; dynamic programming; teacher labor supply

摘要

We propose a simple mixtures estimator for recovering the joint distribution of parameter heterogeneity in economic models, such as the random coefficients logit. The estimator is based on linear regression subject to linear inequality constraints, and is robust, easy to program, and computationally attractive compared to alternative estimators for random coefficient models. For complex structural models, one does not need to nest a solution to the economic model during optimization. We present a Monte Carlo study and an empirical application to dynamic programming discrete choice with a serially correlated unobserved state variable.