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Estimation of dynamic panel data models with a lot of heterogeneity

Kruiniger, H. (2022) 'Estimation of dynamic panel data models with a lot of heterogeneity.', Econometric reviews., 41 (2). pp. 117-146.

Abstract

The commonly used 1-step and 2-step System GMM estimators for the panel AR(1) model are inconsistent under mean stationarity when the ratio of the variance of the individual e§ects to the variance of the idiosyncratic errors is unbounded when N ! 1. The reason for their inconsistency is that their weight matrices select moment conditions that do not identify the autoregressive parameter. This paper proposes a new 2-step System estimator that is still consistent in this case provided that T > 3: Unlike the commonly used 2-step System estimator, the new estimator uses an estimator of the optimal weight matrix that remains consistent in this case. We also show that the commonly used 1-step and 2-step Arellano-Bond GMM estimators and the Random E§ects Quasi MLE remain consistent under the same conditions. To illustrate the usefulness of our new System estimator we revisit the growth study of Levine et al. (2000).

Item Type:Article
Full text:(AM) Accepted Manuscript
Available under License - Creative Commons Attribution Non-commercial 4.0.
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1080/07474938.2021.1899507
Publisher statement:This is an Accepted Manuscript of an article published by Taylor & Francis in Econometric Reviews on 1st July 2021, available online: http://www.tandfonline.com/10.1080/07474938.2021.1899507.
Date accepted:07 February 2021
Date deposited:02 June 2021
Date of first online publication:01 July 2021
Date first made open access:01 July 2022

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