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 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
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:
Contact details of provider:
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 &bull Diffusion Processes
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
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)
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Zheng, Xinye & Li, Fanghua & Song, Shunfeng & Yu, Yihua, 2013.
"Central government's infrastructure investment across Chinese regions: A dynamic spatial panel data approach,"
China Economic Review,
Elsevier, vol. 27(C), pages 264-276.
- Zheng, Xinye & Li, Fanghua & Song, Shunfeng & Yu, Yihua, 2013. "Central Government's Infrastructure Investment across Chinese Regions: A Dynamic Spatial Panel Data Approach," MPRA Paper 50407, University Library of Munich, Germany.
- J. Elhorst, 2012. "Dynamic spatial panels: models, methods, and inferences," Journal of Geographical Systems, Springer, vol. 14(1), pages 5-28, January.
- David Bartolini & Raffaella Santolini, 2012. "Political yardstick competition among Italian municipalities on spending decisions," The Annals of Regional Science, Springer, vol. 49(1), pages 213-235, August.
- 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.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Paul Benson).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.