Document Type

Working Paper

Date

2007

Embargo Period

6-28-2012

Keywords

Panel data, Spatially auto correlated residuals, Pretest estimator, Maximum-likelihood estimation

Language

English

Disciplines

Econometrics

Description/Abstract

This paper examines the consequences of model misspecification using a panel data model with spatially auto correlated 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 auto correlated; (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 described in Baltagi et al. (2006) which allows the spatial correlation parameter for the individual 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.

Additional Information

Harvest from RePEc at http://repec.org

Source

Metadata from RePEc

Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.

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Econometrics Commons

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