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Cited by 1,101Spatial and Panel Data AnalysisAdvanced Causal Inference TechniquesStatistical Methods and Bayesian Inference

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

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Ullah, Subhan, Akhtar, Pervaiz, Zaefarian, Ghasem·2018·Industrial Marketing Management
DOI 10.1016/j.indmarman.2017.11.010
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Crossref · 10.1016/j.indmarman.2017.11.010

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Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • GMM is best suited to control autocorrelation among independent variables and error terms.

    “GMM is best suited to control autocorrelation among independent variables and error terms, which might affect the results' accuracy [65].”

    From Do institutional governance and state fragility affect institutional quality in Asian economies? (2023) · cites this paper as [65]

    The Introduction (p. 5) defines endogeneity as correlation between an explanatory variable and the error term, and the GMM discussion (p. 25) says GMM addresses endogeneity. But the paper uses “autocorrelation” for error terms across time and describes the Arellano–Bond test (p. 27) as a check for it; it does not say GMM is best suited to control autocorrelation among independent variables and error terms. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

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Cites

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Research works printed but not linked: 4

  1. Antonakis, J., Bendahan, S., & Lalive, R. (2014). Causality and endogeneity: Problems and solutions The Oxford handbook of leadership and organizations.
  2. Gujarati, D.N. (2009). Basic Econometrics. Tata McGraw-Hill Education.
  3. Roberts, M. R., & Whited, T. M. (2012). Endogeneity in empirical corporate finance. SSRN paper. Simon School Working Paper No. FR 11-29 .
  4. Schultz, E. L., Tan, D. T. & Walsh, K. D. (2010) Endogeneity and the corporate governanceperformance relation, Australian Journal of Management, 35(2), 145 -163.

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Related

Authors
Ullah, S., Akhtar, P., & Zaefarian, G.
Affiliations
  • University of Hull (GB)
  • University of Leeds (GB)
Corresponding author
Ullah, Subhan
ORCID
Venue
Industrial Marketing Management
Publisher
Elsevier BV
Published
2018-05
Volume
71
Pages
69-78
ISSN
0019-8501 (ISSN-L)
DOI
10.1016/j.indmarman.2017.11.010
OpenAlex
W2780744508
Cited by
1,101
References
45
Citations by year
2026: 151 · 2025: 184 · 2024: 212 · 2023: 175 · 2022: 143 · 2021: 135 · 2020: 71 · 2019: 22 · 2018: 8
FWCI
89.85
Type
journal article
Language
en
Open access
Licence
Locations
  • Industrial Marketing Management (publishedVersion)
  • White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
  • Kent Academic Repository (University of Kent) (acceptedVersion)
  • Repository@Nottingham (University of Nottingham) (acceptedVersion, other-oa)
  • Repository@Hull (Worktribe) (University of Hull) (submittedVersion, cc-by)
  • Repository@Nottingham (University of Nottingham) (submittedVersion, cc-by-nc-nd)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Keywords
endogeneity bias, generalized method of moments, panel data, unobserved heterogeneity, simultaneity, R&D investment, corporate governance, firm performance, listed companies, marketing research methodology

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