Testing for Heteroskedasticity and Spatial Correlation in a Random Effects Panel Data Model

Badi Baltagi (), Seuck Heun Song and Jae Hyeok Kwon

No 108, Center for Policy Research Working Papers from Center for Policy Research, Maxwell School, Syracuse University

Abstract: A panel data regression model with heteroskedastic as well as spatially correlated disturbance is considered, and a joint LM test for homoskedasticity and no spatial correlation is derived. In addition, a conditional LM test for no spatial correlation given heteroskedasticity, as well as a conditional LM test for homoskedasticity given spatial correlation, are also deerived. These LM tests are compared with marginal LM tests that ignore heteroskedasticity in testing for spatial correlation, or spatial correlation in testing for homoskedasticity. Monte Carlo results show that these LM tests as well as their LR counterparts perform well even for small N and T. However, misleading inference can occur when using marginal rather than joint or conditional LM tests when spatial correlation or heteroskedasticity is present.

Keywords: Panel data; heteroskedasticity; spatial correlation; Lagrange multiplier tests; random effects (search for similar items in EconPapers)
JEL-codes: C12 C23 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-geo and nep-ure
Date: 2008-07

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Related works:
Journal Article: Testing for heteroskedasticity and spatial correlation in a random effects panel data model (2009)
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Persistent link: http://EconPapers.repec.org/RePEc:max:cprwps:108

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