| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w26374 |
| 来源ID | Working Paper 26374 |
| Inference for Linear Conditional Moment Inequalities | |
| Isaiah Andrews; Jonathan Roth; Ariel Pakes | |
| 发表日期 | 2019-10-21 |
| 出版年 | 2019 |
| 语种 | 英语 |
| 摘要 | We show that moment inequalities in a wide variety of economic applications have a particular linear conditional structure. We use this structure to construct uniformly valid confidence sets that remain computationally tractable even in settings with nuisance parameters. We first introduce least favorable critical values which deliver non-conservative tests if all moments are binding. Next, we introduce a novel conditional inference approach which ensures a strong form of insensitivity to slack moments. Our recommended approach is a hybrid technique which combines desirable aspects of the least favorable and conditional methods. The hybrid approach performs well in simulations calibrated to Wollmann (2018), with favorable power and computational time comparisons relative to existing alternatives. |
| 主题 | Econometrics ; Estimation Methods |
| URL | https://www.nber.org/papers/w26374 |
| 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/584048 |
| 推荐引用方式 GB/T 7714 | Isaiah Andrews,Jonathan Roth,Ariel Pakes. Inference for Linear Conditional Moment Inequalities. 2019. |
| 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 | ||
| w26374.pdf（2901KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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