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A Monte Carlo Study for Pure and Pretest Estimators of a Panel Data Model with Spatially Autocorrelated Disturbances

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Author Info
Badi H. Baltagi () (Center for Policy Research, Maxwell School, Syracuse University, Syracuse, NY 13244-1020)
Peter Egger () (University of Munich and CESifo, Poschingerstr. 5, 91679 Munich, Germany)
Michael Pfaffermayr () (Department of Economics, University of Innsbruck, Universitaetsstrasse 15, 6020 Innsbruck, Austrai; Austrian Institute of Economic Research, and CE Sifo)

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Abstract

This paper examines the consequences of model misspecification using a panel data model with spatially autocorrelated disturbances. The performance of several maximum likelihood estimators assuming different specifications for this model are compared using Monte Carlo experiments. These include (i) MLE of a random effects model that ignore the spatial correlation; (ii) MLE described in Anselin (1988) which assumes that the individual effects are not spatially autocorrelated; (iii) MLE described in Kapoor et al. (2006) which assumes that both the individual effects and the remainder error are governed by the same spatial autocorrelation; (iv) MLE descrdibed in Baltagi et al. (2006) which allows the spatial correlation parameter for the iondividual effects to be different from that of the remainder error term. The latter model encompasses the other models and allows the researcher to test these specifications as restrictions on the general model using LM and LR tests. In fact, based on these tests, we suggest a pretest estimator which is shown to perform well in Monte Carlo experiments, ranking a close second to the true MLE in mean squared error performance.

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Paper provided by Center for Policy Research, Maxwell School, Syracuse University in its series Center for Policy Research Working Papers with number 98.

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Length: 27 pages
Date of creation: Dec 2007
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Handle: RePEc:max:cprwps:98

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Related research
Keywords: Panel data; Spatially autocorrelated residuals; Pretest estimator; Maximum-likelihood estimation;

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Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data

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  1. Badi H. Baltagi & Peter Egger & Michael Pfafermayr, 2009. "A Generalized Spatial Panel Data Model with Random Effects," Center for Policy Research Working Papers 113, Center for Policy Research, Maxwell School, Syracuse University. [Downloadable!]
  2. Giles, Judith A & Giles, David E A, 1993. " Pre-test Estimation and Testing in Econometrics: Recent Developments," Journal of Economic Surveys, Blackwell Publishing, vol. 7(2), pages 145-97, June.
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