Dynamic Panel Data Models Featuring Endogenous Interaction and Spatially Correlated Errors
AbstractWe 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 dierences 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.
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Bibliographic InfoPaper provided by International Center for Public Policy, Andrew Young School of Policy Studies, Georgia State University in its series International Center for Public Policy Working Paper Series, at AYSPS, GSU with number paper0915.
Length: 40 pages
Date of creation: 01 Dec 2009
Date of revision:
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Web page: http://aysps.gsu.edu/isp/index.html
Dynamic panel models; spatial lag; spatial error; GMM estimation;
Other versions of this item:
- Jacobs, J.P.A.M. & Ligthart, J.E. & Vrijburg, H., 2009. "Dynamic Panel Data Models Featuring Endogenous Interaction and Spatially Correlated Errors," Discussion Paper 2009-92, Tilburg University, Center for Economic Research.
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-01-23 (All new papers)
- NEP-ECM-2010-01-23 (Econometrics)
- NEP-GEO-2010-01-23 (Economic Geography)
- NEP-URE-2010-01-23 (Urban & Real Estate Economics)
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- Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2011.
"Estimating and Forecasting with a Dynamic Spatial Panel Data Model,"
SERC Discussion Papers
0095, Spatial Economics Research Centre, LSE.
- Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2012. "Estimating and Forecasting With A Dynamic Spatial Panel Data Model," Center for Policy Research Working Papers 149, Center for Policy Research, Maxwell School, Syracuse University.
- J. Elhorst, 2012. "Dynamic spatial panels: models, methods, and inferences," Journal of Geographical Systems, Springer, vol. 14(1), pages 5-28, January.
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