.png){kind=icon}
返回
A Simple Adjustment for Bandwidth Snooping
.png){kind=icon}
OA
AI
DOI：10.1093/restud/rdx051.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Kernel-based estimators such as local polynomial estimators in regression discontinuity designs are often evaluated at multiple bandwidths as a form of sensitivity analysis. However, if in the reported results, a researcher selects the bandwidth based on this analysis, the associated confidence intervals (CIs) may not have correct coverage, even if the estimator is unbiased. This article proposes a simple adjustment that gives correct coverage in such situations: replace the normal quantile with a critical value that depends only on the kernel and ratio of the maximum and minimum bandwidths the researcher has entertained. We tabulate these critical values and quantify the loss in coverage for conventional CIs. For a range of relevant cases, a conventional 95% CI has coverage between 70% and 90%, and our adjustment amounts to replacing the conventional critical value 1.96 with a number between 2.2 and 2.8. Our results also apply to other settings involving trimmed data, such as trimming to
Keyword:
Nonparametric estimation
Multiple testing
Regression discontinuity
Bandwidth selection
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.4
论文数:
2.5K
被引数:
2.1W
机构
引用论文
INFERENCE ON CAUSAL EFFECTS IN A GENERALIZED REGRESSION KINK DESIGN广义回归扭结设计中因果效应的推论.png)
ECONOMETRICAOAAI
ECONOMETRICAIF7.1
OAAI分享收藏
分享收藏ROBUST NONPARAMETRIC CONFIDENCE INTERVALS FOR REGRESSION-DISCONTINUITY DESIGNS回归不连续设计的鲁棒非参数置信区间ECONOMETRICAOAAI
ECONOMETRICAIF7.1
OAAI分享收藏分享收藏分享收藏分享收藏
查看更多内容