| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/t0241 |
| 来源ID | Technical Working Paper 0241 |
| When to Control for Covariates? Panel-Asymptotic Results for Estimates of Treatment Effects | |
| Joshua D. Angrist; Jinyong Hahn | |
| 发表日期 | 1999-05-01 |
| 出版年 | 1999 |
| 语种 | 英语 |
| 摘要 | The problem of how to control for covariates is endemic in evaluation research. Covariate-matching provides an appealing control strategy, but with continuous or high-dimensional covariate vectors, exact matching may be impossible or involve small cells. Matching observations that have the same propensity score produces unbiased estimates of causal effects whenever covariate-matching does, and also has an attractive dimension-reducing property. On the other hand, conventional asymptotic arguments show that covariate-matching is (asymptotically) more efficient that propensity score-matching. This is because the usual asymptotic sequence has cell sizes growing to infinity, with no benefit from reducing the number of cells. Here, we approximate the large sample behavior of difference matching estimators using a panel-style asymptotic sequence with fixed cell sizes and the number of cells increasing to infinity. Exact calculations in simple examples and Monte Carlo evidence suggests this generates a substantially improved approximation to actual finite-sample distributions. Under this sequence, propensity-score-matching is most likely to dominate exact matching when cell sizes are small, the explanatory power of the covariates conditional on the propensity score is low, and/or the probability of treatment is close to zero or one. Finally, we introduce a random-effects type combination estimator that provides finite-sample efficiency gains over both covariate-matching and propensity-score-matching. |
| 主题 | Econometrics ; Estimation Methods |
| URL | https://www.nber.org/papers/t0241 |
| 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/564632 |
| 推荐引用方式 GB/T 7714 | Joshua D. Angrist,Jinyong Hahn. When to Control for Covariates? Panel-Asymptotic Results for Estimates of Treatment Effects. 1999. |
| 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 | ||
| t0241.pdf（1313KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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