回归不连续设计
间断(语言学)
变量(数学)
边距(机器学习)
回归
统计
回归分析
计量经济学
数学
计算机科学
机器学习
数学分析
出处
期刊:Journal of econometric methods
[De Gruyter]
日期:2015-11-04
卷期号:6 (1)
被引量:6
标识
DOI:10.1515/jem-2015-0017
摘要
Abstract In regression discontinuity (RD) with a running variable S crossing a known cutoff c , an unexpectedly small break magnitude is due to S being a mis-measured version of the genuine running variable G . Has all been lost, and is RD useless when G≠S ? This paper proves three things. First, when P ( G=S )=0, nonparametric RD identification fails. Second, when P ( G=S )>0, although the usual RD effect on the margin E (·| G=c ) is not nonparametrically identified, the “effect on the truthful margin” E (·| G=S=c ) is. Third, under a no-selection-problem assumption, the effect on the truthful margin becomes the effect on the margin; the no-selection-problem assumption is unnecessary, as long as the effect on the truthful margin is taken as a parameter of interest.
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