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Estimation and model selection in general spatial dynamic panel data models.

ABSTRACT: Commonly used methods for estimating parameters of a spatial dynamic panel data model include the two-stage least squares, quasi-maximum likelihood, and generalized moments. In this paper, we present an approach that uses the eigenvalues and eigenvectors of a spatial weight matrix to directly construct consistent least-squares estimators of parameters of a general spatial dynamic panel data model. The proposed methodology is conceptually simple and efficient and can be easily implemented. We show that the proposed parameter estimators are consistent and asymptotically normally distributed under mild conditions. We demonstrate the superior performance of our approach via extensive simulation studies. We also provide a real data example.

SUBMITTER: Jin B

PROVIDER: S-EPMC7071865 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Estimation and model selection in general spatial dynamic panel data models.

Jin Baisuo B Wu Yuehua Y Rao Calyampudi Radhakrishna CR Hou Li L

Proceedings of the National Academy of Sciences of the United States of America 20200224 10

Commonly used methods for estimating parameters of a spatial dynamic panel data model include the two-stage least squares, quasi-maximum likelihood, and generalized moments. In this paper, we present an approach that uses the eigenvalues and eigenvectors of a spatial weight matrix to directly construct consistent least-squares estimators of parameters of a general spatial dynamic panel data model. The proposed methodology is conceptually simple and efficient and can be easily implemented. We sho ...[more]

PMID: 32094164

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