Dynamic Panel Data Models Featuring Endogenous Interaction and Spatially Correlated Errors

Jan Jacobs, Jenny Ligthart and Hendrik Vrijburg ()

International Center for Public Policy Working Paper Series, at AYSPS, GSU from International Center for Public Policy, Andrew Young School of Policy Studies, Georgia State University

Abstract: We extend the three-step generalized methods of moments (GMM) approach of Kapoor, Kelejian, and Prucha (2007), which corrects for spatially correlated errors in static panel data models, by introducing a spatial lag and a one-period lag of the dependent variable as additional explanatory variables. Combining the extended Kapoor, Kelejian, and Prucha (2007) approach with the dynamic panel data model GMM estimators of Arellano and Bond (1991) and Blundell and Bond (1998) and supplementing the dynamic instruments by lagged and weighted exogenous variables as suggested by Kelejian and Robinson (1993) yields new spatial dynamic panel data estimators. The performance of these spatial dynamic panel data estimators is in- vestigated by means of Monte Carlo simulations. We show that di erences in bias as well as root mean squared error between spatial GMM estimates and corresponding GMM estimates in which spatial error correlation is ignored are small.

Keywords: Dynamic panel models; spatial lag; spatial error; GMM estimation (search for similar items in EconPapers)
Pages: 40 pages
Date: 2009-12-01
New Economics Papers: this item is included in nep-ecm, nep-geo and nep-ure
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Citations: View citations in EconPapers (34)

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Related works:
Working Paper: Dynamic Panel Data Models Featuring Endogenous Interaction and Spatially Correlated Errors (2009)
Working Paper: Dynamic Panel Data Models Featuring Endogenous Interaction and Spatially Correlated Errors (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:ays:ispwps:paper0915

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