全球智库信息集成服务系统(G2TT): A Simple Nonparametric Approach to Estimating the Distribution of Random Coefficients in Structural Models

G2TT

来源类型	Working Paper
规范类型	报告
DOI	10.3386/w17283
来源ID	Working Paper 17283
	A Simple Nonparametric Approach to Estimating the Distribution of Random Coefficients in Structural Models
	Jeremy T. Fox; Kyoo il Kim
发表日期	2011-08-11
出版年	2011
语种	英语
摘要	We explore a nonparametric mixtures estimator for recovering the joint distribution of random coefficients in economic models. The estimator is based on linear regression subject to linear inequality constraints and is computationally attractive compared to alternative, nonparametric estimators. We provide conditions under which the estimated distribution function converges to the true distribution in the weak topology on the space of distributions. We verify the consistency conditions for discrete choice, continuous outcome and selection models.
主题	Econometrics ; Estimation Methods ; Industrial Organization
URL	https://www.nber.org/papers/w17283
来源智库	National Bureau of Economic Research (United States)
引用统计
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/574958
推荐引用方式 GB/T 7714	Jeremy T. Fox,Kyoo il Kim. A Simple Nonparametric Approach to Estimating the Distribution of Random Coefficients in Structural Models. 2011.