Subhan Ullah
Dealing with endogeneity bias: The generalized method of moments (GMM) for panel data
Ullah, Subhan; Akhtar, Pervaiz; Zaefarian, Ghasem
Authors
Pervaiz Akhtar
Ghasem Zaefarian
Abstract
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.
Citation
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. https://doi.org/10.1016/j.indmarman.2017.11.010
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 |
DOI | https://doi.org/10.1016/j.indmarman.2017.11.010 |
Keywords | Endogeneity bias; Generalized method of moments; Methodological issues; Panel data |
Public URL | https://hull-repository.worktribe.com/output/502959 |
Publisher URL | https://www.sciencedirect.com/science/article/pii/S0019850117308532 |
Contract Date | Jan 26, 2018 |
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