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Dealing with endogeneity bias: The generalized method of moments (GMM) for panel data

Ullah, Subhan; Akhtar, Pervaiz; Zaefarian, Ghasem


Subhan Ullah

Pervaiz Akhtar

Ghasem Zaefarian


Endogeneity bias can lead to inconsistent estimates and incorrect inferences, which may provide misleading conclusions and inappropriate theoretical interpretations. Sometimes such bias can even lead to coefficients having the wrong sign. Although this is a long-standing issue, it is now emerging in marking and management science, with high-ranked journals increasingly exploring the issue. In this paper we methodologically demonstrate how to detect and deal with endogeneity issues in panel data. For illustration purposes, we used a dataset consisting of 15 years of observations (i.e., 2002 to 2016) from 101 UK listed companies, and examined the direct effect of R&D expenditures, corporate governance, and firms’ characteristics on firm performance. The result of our analyses indicate significant differences in our findings reported under ordinary least square (OLS), fixed effects and the generalized method of moments (GMM) estimations, due to endogeneity bias. We provide generic STATA commands that can be used by marketing researchers in implementing a GMM model that better controls for the three sources of endogeneity, namely, unobserved heterogeneity, simultaneity and dynamic endogeneity.


Ullah, S., Akhtar, P., & Zaefarian, G. (2018). Dealing with endogeneity bias: The generalized method of moments (GMM) for panel data. Industrial marketing management, 71, 69-78.

Journal Article Type Article
Acceptance Date Nov 21, 2017
Online Publication Date Jan 10, 2018
Publication Date 2018-05
Deposit Date Jan 26, 2018
Publicly Available Date Jan 11, 2020
Print ISSN 0019-8501
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 71
Pages 69-78
Keywords Endogeneity bias; Generalized method of moments; Methodological issues; Panel data
Public URL
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