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ISOTONIC PROPENSITY SCORE MATCHING

delete2025-11-01
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OA
AI
M
Mengshan Xu
T
Taisuke Otsu *
DOI：10.1017/S0266466625100133delete
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摘要

摘要

En 中文
我们提出了一种基于等高回归估计倾向得分的平均处理效应的一对多匹配估计量。这种方法基于倾向得分函数单调性的假设，该条件在许多经济应用中可以得到证明。我们表明，等高估计量的性质有助于解决现有匹配方法中的许多问题，包括效率、匹配数量的选择、调谐参数的选择、对倾向得分误设的稳健性以及自助法的有效性。作为副产品，为我们的提议匹配方法开发了一个一致收敛的等高估计量。
Keyword:
EFFICIENT ESTIMATION
BINARY CHOICE
SEMIPARAMETRIC EFFICIENCY
NONPARAMETRIC ESTIMATORS
REGRESSION-MODELS
SAMPLE PROPERTIES
BIAS
BOOTSTRAP
CAUSAL
INFERENCE
AI总结

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期刊

E
Econometric Theory
IF:
1
论文数:
29
被引数:
0

机构

U
University of Mannheim
学者数:
1.9K
论文数: 2.2K
被引数: 3.2K
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