Another look at the instrumental variable estimation of error-components models
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The System GMM approach is particularly suitable for this study because it addresses key econometric challenges such as endogeneity, unobserved heterogeneity, and measurement errors.
“the System GMM approach, as developed by Arellano and Bover (1995) and Blundell and Bond (1998), is particularly suitable for this study because it addresses key econometric challenges such as endogeneity, unobserved heterogeneity, and measurement errors.”
From Remittance–economic growth linkage in Africa: the roles of financial development and inflation (2025) · cites this paper as Arellano and Bover (1995)
The paper uses a dynamic panel SYS-GMM estimator, which allows control for potential endogeneity problems.
“Secondly, as estimation strategy, we use a dynamic panel systemgeneralised method of moments (SYS-GMM) estimator, which allows us to control for potential endogeneity problems.”
From Finance-growth nexus in sub-Saharan Africa (2021) · cites this paper as Arellano & Bover 1995
The dynamic panel system GMM estimator was chosen to control country-specific effects, autocorrelation, and simultaneity bias.
“This estimator, requiring a large number of cross-section units and a small number of time periods, was chosen in order to control: (1) country-specific effects, (2) autocorrelation problems, due to the presence of the lagged dependent variable in the model, and (3) simultaneity bias, caused by potential endogeneity of some of the explanatory variables.”
From Finance-growth nexus in sub-Saharan Africa (2021) · cites this paper as Arellano & Bover 1995
PLS allows intuitive estimation and interpretation of the measures while preventing instability and proliferation challenges related to other models.
“PLS allows intuitive estimation and interpretation of the measures while preventing instability and proliferation challenges related to other models (Arellano & Bover, 1995;Baltagi, 2008).”
From The Impact of Liquidity and Leverage on the Financial Performance of the Johannesburg Stock Exchange-Listed Consumer Goods Firms (2025) · cites this paper as Arellano & Bover, 1995
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“Model estimation uses the dynamic panel system GMM estimator developed by Arellano and Bover (1995) and Blundell and Bond (1998).”
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“…inflows and economic growth, while examining the moderating roles of financial development and inflation. the System GMM approach, as developed by Arellano and Bover (1995) and Blundell and Bond (1998), is particularly suitable for this study because it addresses key econometric challenges such…”
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“Arellano and Bover (1995) explains how more moment conditions might be used to improve efficiency if the system included the original equations in the levels (Roodman, 2020).”
- Authors
- Arellano, M., & Bover, O.
- Affiliations
- Centro de Estudios Monetarios y Financieros (ES)
- Bank of Spain (ES)
- Corresponding author
- Arellano, Manuel
- Venue
- Journal of Econometrics
- Publisher
- Elsevier BV
- Published
- 1995-07
- Volume
- 68
- Issue
- 1
- Pages
- 29-51
- ISSN
- 0304-4076 (ISSN-L)
- OpenAlex
- W2035554302
- Cited by
- 19,880
- References
- 19
- Citations by year
- 2026: 1339 · 2025: 1328 · 2024: 1354 · 2023: 1483 · 2022: 1372 · 2021: 1435 · 2020: 1240 · 2019: 1134 · 2018: 989 · 2017: 929 · 2016: 881 · 2015: 884 · 2014: 849 · 2013: 734 · 2012: 710
- FWCI
- 44.68
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Econometrics (publishedVersion)
- 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
- instrumental variable estimation, error components model, random effects models, panel data models, optimal estimators
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