Reprint: Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic

Xu Guo, Runze Li, Jingyuan Liu and Mudong Zeng

Journal of Econometrics, 2024, vol. 239, issue 2

Abstract: Mediation analysis draws increasing attention in many research areas such as economics, finance and social sciences. In this paper, we propose new statistical inference procedures for high dimensional mediation models, in which both the outcome model and the mediator model are linear with high dimensional mediators. Traditional procedures for mediation analysis cannot be used to make statistical inference for high dimensional linear mediation models due to high-dimensionality of the mediators. We propose an estimation procedure for the indirect effects of the models via a partially penalized least squares method, and further establish its theoretical properties. We further develop a partially penalized Wald test on the indirect effects, and prove that the proposed test has a χ2 limiting null distribution. We also propose an F-type test for direct effects and show that the proposed test asymptotically follows a χ2-distribution under null hypothesis and a noncentral χ2-distribution under local alternatives. Monte Carlo simulations are conducted to examine the finite sample performance of the proposed tests and compare their performance with existing ones. We further apply the newly proposed statistical inference procedures to study stock reaction to COVID-19 pandemic via an empirical analysis of studying the mediation effects of financial metrics that bridge company’s sector and stock return.

Keywords: Mediation analysis; Penalized least squares; Sparsity; Wald test (search for similar items in EconPapers)
JEL-codes: C12 C13 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:239:y:2024:i:2:s0304407623003664

DOI: 10.1016/j.jeconom.2023.105650

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