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Estimation of dynamic panel data models with a lot of heterogeneity

Kruiniger, H.

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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).

Citation

Kruiniger, H. (2022). Estimation of dynamic panel data models with a lot of heterogeneity. Econometric Reviews, 41(2), 117-146. https://doi.org/10.1080/07474938.2021.1899507

Journal Article Type Article
Acceptance Date Feb 7, 2021
Online Publication Date Jul 1, 2021
Publication Date 2022
Deposit Date Jun 1, 2021
Publicly Available Date Jul 1, 2022
Journal Econometric Reviews
Print ISSN 0747-4938
Electronic ISSN 1532-4168
Publisher Taylor and Francis Group
Peer Reviewed Peer Reviewed
Volume 41
Issue 2
Pages 117-146
DOI https://doi.org/10.1080/07474938.2021.1899507
Public URL https://durham-repository.worktribe.com/output/1274414

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