| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w17408 |
| 来源ID | Working Paper 17408 |
| Heaping-Induced Bias in Regression-Discontinuity Designs | |
| Alan I. Barreca; Jason M. Lindo; Glen R. Waddell | |
| 发表日期 | 2011-09-08 |
| 出版年 | 2011 |
| 语种 | 英语 |
| 摘要 | This study uses Monte Carlo simulations to demonstrate that regression-discontinuity designs arrive at biased estimates when attributes related to outcomes predict heaping in the running variable. After showing that our usual diagnostics are poorly suited to identifying this type of problem, we provide alternatives. We also demonstrate how the magnitude and direction of the bias varies with bandwidth choice and the location of the data heaps relative to the treatment threshold. Finally, we discuss approaches to correcting for this type of problem before considering these issues in several non-simulated environments. |
| 主题 | Econometrics ; Estimation Methods ; Health, Education, and Welfare ; Health |
| URL | https://www.nber.org/papers/w17408 |
| 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/575082 |
| 推荐引用方式 GB/T 7714 | Alan I. Barreca,Jason M. Lindo,Glen R. Waddell. Heaping-Induced Bias in Regression-Discontinuity Designs. 2011. |
| 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 | ||
| w17408.pdf（1468KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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