Panel data inference under spatial dependence

Badi Baltagi and Alain Pirotte

Economic Modelling, 2010, vol. 27, issue 6, 1368-1381

Abstract: This paper focuses on inference based on the standard panel data estimators of a one-way error component regression model when the true specification is a spatial error component model. Among the estimators considered, are pooled OLS, random and fixed effects, maximum likelihood under normality, etc. The spatial effects capture the cross-section dependence, and the usual panel data estimators ignore this dependence. Two popular forms of spatial autocorrelation are considered, namely, spatial autoregressive random effects (SAR-RE) and spatial moving average random effects (SMA-RE). We show that when the spatial coefficients are large, test of hypothesis based on the standard panel data estimators that ignore spatial dependence can lead to misleading inference.

Keywords: Panel; data; Hausman; test; Random; effect; Spatial; autocorrelation; Maximum; likelihood (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (27)

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Related works:
Working Paper: Panel Data Inference under Spatial Dependence (2010)
Working Paper: Panel Data Inference Under Spatial Dependence (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:27:y:2010:i:6:p:1368-1381

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