Improved GMM estimation of random effects panel data models with spatially correlated error components

Authors


  • Financial support by Deutsche Forschungsgemeinschaft (SFB 823, project A1) is gratefully acknowledged. We are grateful to two anonymous referees who provided numerous helpful comments which improved the paper.

Abstract

We modify a previously suggested GMM estimator in a spatial panel regression model, which has recently received considerable interest in empirical applications, by taking into account the difference between disturbances and regression residuals. Consistency and asymptotic normality of the estimator are derived. Analytic results, simulation evidence and an empirical application to Indonesian rice data illustrate the improvement in finite samples.

Resumen

Hemos modificado un estimador GMM sugerido previamente en un modelo de regresión de panel espacial, que ha recibido recientemente un gran interés en las aplicaciones empíricas, teniendo en cuenta la diferencia entre las perturbaciones y los residuos de la regresión. Se deducen la consistencia y normalidad asintótica del estimador. Los resultados analíticos, las pruebas de simulación y una aplicación empírica que utiliza datos de arroz de Indonesia ilustran la mejora en muestras finitas.

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