Random Effects, Fixed Effects and Hausman’s Test for the Generalized Mixed Regressive Spatial Autoregressive Panel

Badi Baltagi and Long Liu
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Long Liu: Department of Economics, College of Business, University of Texas at San Antonio

No 174, Center for Policy Research Working Papers from Center for Policy Research, Maxwell School, Syracuse University

Abstract: This paper suggests random and fixed effects spatial two-stage least squares estimators for the generalized mixed regressive spatial autoregressive panel data model. This extends the generalized spatial panel model of Baltagi, Egger and Pfaffermayr (2013) by the inclusion of a spatial lag dependent variable. The estimation method utilizes the Generalized Moments method suggested by Kapoor, Kelejian, and Prucha (2007) for a spatial autoregressive panel data model. We derive the asymptotic distributions of these estimators and suggest a Hausman test a la Mutl and Pfaffermayr (2011) based on the difference between these estimators. Monte Carlo experiments are performed to investigate the performance of these estimators as well as the corresponding Hausman test.

Keywords: Panel Data; Fixed Effects; Random Effects; Spatial Model; Hausman Test (search for similar items in EconPapers)
JEL-codes: C12 C13 C23 (search for similar items in EconPapers)
Pages: 24 pages
Date: 2014-12
New Economics Papers: this item is included in nep-ecm and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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