Uniform Confidence Band for Marginal Treatment Effect Function

Fuente: arXiv
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Hauptverfasser: Tsuda, Toshiki, Jin, Yanchun, Okui, Ryo
Format: Preprint
Veröffentlicht: 2025
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author Tsuda, Toshiki
Jin, Yanchun
Okui, Ryo
author_facet Tsuda, Toshiki
Jin, Yanchun
Okui, Ryo
contents This paper presents a method for constructing uniform confidence bands for the marginal treatment effect (MTE) function. The shape of the MTE function offers insight into how the unobserved propensity to receive treatment is related to the treatment effect. Our approach visualizes the statistical uncertainty of an estimated function, facilitating inferences about the function's shape. The proposed method is computationally inexpensive and requires only minimal information: sample size, standard errors, kernel function, and bandwidth. This minimal data requirement enables applications to both new analyses and published results without access to original data. We derive a Gaussian approximation for a local quadratic estimator and consider the approximation of the distribution of its supremum in polynomial order. Monte Carlo simulations demonstrate that our bands provide the desired coverage and are less conservative than those based on the Gumbel approximation. An empirical illustration regarding the returns to education is included.
format Preprint
id arxiv_https___arxiv_org_abs_2501_17455
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Uniform Confidence Band for Marginal Treatment Effect Function
Tsuda, Toshiki
Jin, Yanchun
Okui, Ryo
Econometrics
This paper presents a method for constructing uniform confidence bands for the marginal treatment effect (MTE) function. The shape of the MTE function offers insight into how the unobserved propensity to receive treatment is related to the treatment effect. Our approach visualizes the statistical uncertainty of an estimated function, facilitating inferences about the function's shape. The proposed method is computationally inexpensive and requires only minimal information: sample size, standard errors, kernel function, and bandwidth. This minimal data requirement enables applications to both new analyses and published results without access to original data. We derive a Gaussian approximation for a local quadratic estimator and consider the approximation of the distribution of its supremum in polynomial order. Monte Carlo simulations demonstrate that our bands provide the desired coverage and are less conservative than those based on the Gumbel approximation. An empirical illustration regarding the returns to education is included.
title Uniform Confidence Band for Marginal Treatment Effect Function
topic Econometrics
url https://arxiv.org/abs/2501.17455