Addressing Endogeneity Without Strong Instruments: A Practical Guide to Heteroskedasticity-Based Instrumental Variables (HBIV)

This article provides an overview and guide to implementing heteroskedaticity-based instrumental variables (HBIV) in regression models with endogeneity, i.e., one or more of the regressors are correlated with the disturbance term. We discuss the problem of implementing standard instrumental variables (IV) solutions to the endogeneity problem when external instruments are either insufficient or not readily available, and when the disturbances are heteroskedastic, present a solution to the problem. We illustrate the implementation of HBIV in the presence of strong external instruments, weak external instruments, and no external instruments, using both traditional IV and HBIV. Finally, we discuss the pros and cons of using HBIV methods to address endogeneity.

[1]  Roberto Rigobon,et al.  Identification Through Heteroskedasticity , 2003, Review of Economics and Statistics.

[2]  Letizia Mencarini,et al.  Journal of Economic Behavior & Organization Is It Just a Matter of Personality? on the Role of Subjective Well-being in Childbearing Behavior , 2022 .

[3]  Joseph J. Sabia.  The Effect of Body Weight on Adolescent Academic Performance , 2007 .

[4]  David F. Larcker,et al.  On the Use of Instrumental Variables in Accounting Research , 2008 .

[5]  Mikko Ketokivi,et al.  Addressing the endogeneity dilemma in operations management research: Theoretical, empirical, and pragmatic considerations , 2017 .

[6]  Matthew Semadeni,et al.  The perils of endogeneity and instrumental variables in strategy research: : Understanding through simulations , 2014 .

[7]  A. Lewbel,et al.  Identification and estimation using heteroscedasticity without instruments: The binary endogenous regressor case , 2018 .

[8]  Philip G. Wright,et al.  The tariff on animal and vegetable oils , 1928 .

[9]  Joseph A. Clougherty,et al.  Correcting for Self-selection Based Endogeneity in Management Research , 2016 .

[10]  F. Vella,et al.  Estimating a Class of Triangular Simultaneous Equations Models Without Exclusion Restrictions , 2005 .

[11]  Arthur Lewbel,et al.  A Simple Estimator for Binary Choice Models with Endogenous Regressors , 2015 .

[12]  T. Breurch,et al.  A simple test for heteroscedasticity and random coefficient variation (econometrica vol 47 , 1979 .

[13]  Philippe Jacquart,et al.  On making causal claims: A review and recommendations , 2010 .

[14]  Christopher F. Baum,et al.  Enhanced Routines for Instrumental Variables/Generalized Method of Moments Estimation and Testing , 2007 .

[15]  R. Rigobón,et al.  Measuring the Reaction of Monetary Policy to the Stock Market , 2001 .

[16]  Roger Koenker,et al.  A note on studentizing a test for heteroscedasticity , 1981 .

[17]  M. Emran,et al.  Access to Markets and Rural Poverty: Evidence from Household Consumption in China , 2013, Review of Economics and Statistics.

[18]  G. Bascle.  Controlling for endogeneity with instrumental variables in strategic management research , 2008 .

[19]  A. Lewbel,et al.  Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models , 2012 .