| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w28436 |
| 来源ID | Working Paper 28436 |
| Using Monotonicity Restrictions to Identify Models with Partially Latent Covariates | |
| Minji Bang; Wayne Gao; Andrew Postlewaite; Holger Sieg | |
| 发表日期 | 2021-02-08 |
| 出版年 | 2021 |
| 语种 | 英语 |
| 摘要 | This paper develops a new method for identifying econometric models with partially latent covariates. Such data structures arise naturally in industrial organization and labor economics settings where data are collected using an “input-based sampling” strategy, e.g., if the sampling unit is one of multiple labor input factors. We show that the latent covariates can be nonparametrically identified, if they are functions of a common shock satisfying some plausible monotonicity assumptions. With the latent covariates identified, semiparametric estimation of the outcome equation proceeds within a standard IV framework that accounts for the endogeneity of the covariates. We illustrate the usefulness of our method using two applications. The first focuses on pharmacies: we find that production function differences between chains and independent pharmacies may partially explain the observed transformation of the industry structure. Our second application investigates education achievement functions and illustrates important differences in child investments between married and divorced couples. |
| 主题 | Econometrics ; Labor Economics ; Labor Supply and Demand ; Industrial Organization |
| URL | https://www.nber.org/papers/w28436 |
| 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/586109 |
| 推荐引用方式 GB/T 7714 | Minji Bang,Wayne Gao,Andrew Postlewaite,et al. Using Monotonicity Restrictions to Identify Models with Partially Latent Covariates. 2021. |
| 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 | ||
| w28436.pdf（487KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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