| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w29787 |
| 来源ID | Working Paper 29787 |
| Causality and Econometrics | |
| James J. Heckman; Rodrigo Pinto | |
| 发表日期 | 2022-02-28 |
| 出版年 | 2022 |
| 语种 | 英语 |
| 摘要 | This paper examines the econometric causal model for policy analysis developed by the seminal ideas of Ragnar Frisch and Trygve Haavelmo. We compare the econometric causal model with two popular causal frameworks: Neyman-Holland causal model and the do-calculus. The Neyman-Holland causal model is based on the language of potential outcomes and was largely developed by statisticians. The do-calculus, developed by Judea Pearl and co-authors, relies on Directed Acyclic Graphs (DAGs) and is a popular causal framework in computer science. We make the case that economists who uncritically use these approximating frameworks often discard the substantial benefits of the econometric causal model to the detriment of more informative economic policy analyses. We illustrate the versatility and capabilities of the econometric framework using causal models that are frequently studied by economists. |
| 主题 | Econometrics ; Estimation Methods |
| URL | https://www.nber.org/papers/w29787 |
| 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/587461 |
| 推荐引用方式 GB/T 7714 | James J. Heckman,Rodrigo Pinto. Causality and Econometrics. 2022. |
| 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 | ||
| w29787.pdf（696KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
