Spatial Dynamic Panel Model and System GMM: A Monte Carlo Investigation

Madina Kukenova and Jose-Antonio Monteiro

MPRA Paper from University Library of Munich, Germany

Abstract: This paper investigates the �finite sample properties of estimators for spatial dynamic panel models in the presence of several endogenous variables. So far, none of the available estimators in spatial econometrics allows considering spatial dynamic models with one or more endogenous variables. We propose to apply system-GMM, since it can correct for the endogeneity of the dependent variable, the spatial lag as well as other potentially endogenous variables using internal and/or external instruments. The Monte-Carlo investigation compares the performance of spatial MLE, spatial dynamic MLE (Elhorst (2005)), spatial dynamic QMLE (Yu et al. (2008)), LSDV, difference-GMM (Arellano & Bond (1991)), as well as extended-GMM (Arellano & Bover (1995), Blundell & Bover (1998)) in terms of bias, root mean squared error and standard-error accuracy. The results suggest that, in order to account for the endogeneity of several covariates, spatial dynamic panel models should be estimated using extended GMM. On a practical ground, this is also important, because system-GMM avoids the inversion of high dimension spatial weights matrices, which can be computationally unfeasible for large N and/or T.

Keywords: Spatial Econometrics; Dynamic Panel Model; System GMM; Monte Carlo Simulations (search for similar items in EconPapers)
JEL-codes: C15 C33 (search for similar items in EconPapers)
Date: 2008-07, Revised 2009-02
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (75)

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Related works:
Working Paper: Spatial Dynamic Panel Model and System GMM: A Monte Carlo Investigation (2009)
Working Paper: Spatial Dynamic Panel Model and System GMM: A Monte Carlo Investigation (2008)
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