Testing for Endogeneity: A Moment-Based Bayesian Approach

Fuente: arXiv
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Main Authors: Chib, Siddhartha, Shin, Minchul, Simoni, Anna
Format: Preprint
Published: 2026
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author Chib, Siddhartha
Shin, Minchul
Simoni, Anna
author_facet Chib, Siddhartha
Shin, Minchul
Simoni, Anna
contents A standard assumption in the Bayesian estimation of linear regression models is that the regressors are exogenous in the sense that they are uncorrelated with the model error term. In practice, however, this assumption can be invalid. In this paper, using the exponentially tilted empirical likelihood framework, we develop a Bayes factor test for endogeneity that compares a base model that is correctly specified under exogeneity but misspecified under endogeneity against an extended model that is correctly specified in either case. We provide a comprehensive study of the log-marginal exponentially tilted empirical likelihood. We demonstrate that our testing procedure is consistent from a frequentist point of view: as the sample grows, it almost surely selects the base model if and only if the regressors are exogenous, and the extended model if and only if the regressors are endogenous. The methods are illustrated with simulated data, and problems concerning the causal effect of automobile prices on automobile demand and the causal effect of potentially endogenous airplane ticket prices on passenger volume.
format Preprint
id arxiv_https___arxiv_org_abs_2603_07780
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Testing for Endogeneity: A Moment-Based Bayesian Approach
Chib, Siddhartha
Shin, Minchul
Simoni, Anna
Econometrics
Statistics Theory
A standard assumption in the Bayesian estimation of linear regression models is that the regressors are exogenous in the sense that they are uncorrelated with the model error term. In practice, however, this assumption can be invalid. In this paper, using the exponentially tilted empirical likelihood framework, we develop a Bayes factor test for endogeneity that compares a base model that is correctly specified under exogeneity but misspecified under endogeneity against an extended model that is correctly specified in either case. We provide a comprehensive study of the log-marginal exponentially tilted empirical likelihood. We demonstrate that our testing procedure is consistent from a frequentist point of view: as the sample grows, it almost surely selects the base model if and only if the regressors are exogenous, and the extended model if and only if the regressors are endogenous. The methods are illustrated with simulated data, and problems concerning the causal effect of automobile prices on automobile demand and the causal effect of potentially endogenous airplane ticket prices on passenger volume.
title Testing for Endogeneity: A Moment-Based Bayesian Approach
topic Econometrics
Statistics Theory
url https://arxiv.org/abs/2603.07780