| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/t0200 |
| 来源ID | Technical Working Paper 0200 |
| Nonparametric Applications of Bayesian Inference | |
| Gary Chamberlain; Guido W. Imbens | |
| 发表日期 | 1996-08-01 |
| 出版年 | 1996 |
| 语种 | 英语 |
| 摘要 | The paper evaluates the usefulness of a nonparametric approach to Bayesian inference by presenting two applications. The approach is due to Ferguson (1973, 1974) and Rubin (1981). Our first application considers an educational choice problem. We focus on obtaining a predictive distribution for earnings corresponding to various levels of schooling. This predictive distribution incorporates the parameter uncertainty, so that it is relevant for decision making under uncertainty in the expected utility framework of microeconomics. The second application is to quantile regression. Our point here is to examine the potential of the nonparametric framework to provide inferences without making asymptotic approximations. Unlike in the first application, the standard asymptotic normal approximation turns out to not be a good guide. We also consider a comparison with a bootstrap approach. |
| URL | https://www.nber.org/papers/t0200 |
| 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/563174 |
| 推荐引用方式 GB/T 7714 | Gary Chamberlain,Guido W. Imbens. Nonparametric Applications of Bayesian Inference. 1996. |
| 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 | ||
| t0200.pdf（605KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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