| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w15210 |
| 来源ID | Working Paper 15210 |
| A Simple Nonparametric Estimator for the Distribution of Random Coefficients | |
| Patrick Bajari; Jeremy T. Fox; Kyoo il Kim; Stephen P. Ryan | |
| 发表日期 | 2009-08-06 |
| 出版年 | 2009 |
| 语种 | 英语 |
| 摘要 | We propose a simple nonparametric 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. We prove consistency and provide the rate of convergence under deterministic and stochastic choices for the sieve approximating space. We present a Monte Carlo study and an empirical application to dynamic programming discrete choice with a serially-correlated unobserved state variable. |
| 主题 | Econometrics ; Estimation Methods ; Health, Education, and Welfare ; Education ; Industrial Organization ; Development and Growth ; Development |
| URL | https://www.nber.org/papers/w15210 |
| 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/572886 |
| 推荐引用方式 GB/T 7714 | Patrick Bajari,Jeremy T. Fox,Kyoo il Kim,et al. A Simple Nonparametric Estimator for the Distribution of Random Coefficients. 2009. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w15210.pdf（1647KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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