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

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Author Info
Badi H. Baltagi () (Center for Policy Research, Maxwell School, Syracuse University, Syracuse, NY 13244-1020)
Seuck Heun Song
Jae Hyeok Kwon

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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.

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File URL: http://www-cpr.maxwell.syr.edu/cprwps/pdf/wp108.pdf
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Publisher Info
Paper provided by Center for Policy Research, Maxwell School, Syracuse University in its series Center for Policy Research Working Papers with number 108.

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Length: 42 pages
Date of creation: Jul 2008
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Handle: RePEc:max:cprwps:108

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Related research
Keywords: Panel data; heteroskedasticity; spatial correlation; Lagrange multiplier tests; random effects;

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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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This page was last updated on 2009-11-27.


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