Isotonic propensity score matching

Fuente: arXiv
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Main Authors: Xu, Mengshan, Otsu, Taisuke
Format: Preprint
Published: 2022
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author Xu, Mengshan
Otsu, Taisuke
author_facet Xu, Mengshan
Otsu, Taisuke
contents We propose a one-to-many matching estimator of the average treatment effect based on propensity scores estimated by isotonic regression. This approach is predicated on the assumption of monotonicity in the propensity score function, a condition that can be justified in many economic applications. We show that the nature of the isotonic estimator can help us to fix many problems of existing matching methods, including efficiency, choice of the number of matches, choice of tuning parameters, robustness to propensity score misspecification, and bootstrap validity. As a by-product, a uniformly consistent isotonic estimator is developed for our proposed matching method.
format Preprint
id arxiv_https___arxiv_org_abs_2207_08868
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Isotonic propensity score matching
Xu, Mengshan
Otsu, Taisuke
Econometrics
Methodology
We propose a one-to-many matching estimator of the average treatment effect based on propensity scores estimated by isotonic regression. This approach is predicated on the assumption of monotonicity in the propensity score function, a condition that can be justified in many economic applications. We show that the nature of the isotonic estimator can help us to fix many problems of existing matching methods, including efficiency, choice of the number of matches, choice of tuning parameters, robustness to propensity score misspecification, and bootstrap validity. As a by-product, a uniformly consistent isotonic estimator is developed for our proposed matching method.
title Isotonic propensity score matching
topic Econometrics
Methodology
url https://arxiv.org/abs/2207.08868