Spatial Dynamic Panel Model and System GMM: A Monte Carlo Investigation
AbstractThis 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.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 13405.
Date of creation: Jul 2008
Date of revision: Feb 2009
Spatial Econometrics; Dynamic Panel Model; System GMM; Monte Carlo Simulations;
Other versions of this item:
- Kukenova, Madina & Monteiro, Jose-Antonio, 2008. "Spatial Dynamic Panel Model and System GMM: A Monte Carlo Investigation," MPRA Paper 11569, University Library of Munich, Germany, revised Nov 2008.
- José-Antonio Monteiro & Madina Kukenova, 2009. "Spatial Dynamic Panel Model and System GMM: A Monte Carlo Investigation," IRENE Working Papers 09-01, IRENE Institute of Economic Research.
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
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