LSE LSE Research Laboratory LSE
LSE Research Laboratory (RLAB)

Abstract for:

Estimating and Forecasting with a Dynamic Spatial Panel Data Model

Badi H.  Baltagi,  Bernard  Fingleton,  Alain  Pirotte,  November 2011
Paper No' SERCDP0095: | Full paper (pdf)
Save Reference as: BibTeX BibTeX File | Endote EndNote Import File
Keywords: Panel data; spatial lag; error components; linear predictor; GMM; spatial autocorrelation

JEL Classification: C33

Is hard copy/paper copy available? YES - Paper Copy Still In Print.
This Paper is published under the following series: SERC Discussion Papers
Share this page: Google Bookmarks Google Bookmarks | Facebook Facebook | Twitter Twitter

Abstract:

This paper focuses on the estimation and predictive performance of several estimators for the dynamic and autoregressive spatial lag panel data model with spatially correlated disturbances. In the spirit of Arellano and Bond (1991) and Mutl (2006), a dynamic spatial GMM estimator is proposed based on Kapoor, Kelejian and Prucha (2007) for the Spatial AutoRegressive (SAR) error model. The main idea is to mix non-spatial and spatial instruments to obtain consistent estimates of the parameters. Then, a linear predictor of this spatial dynamic model is derived. Using Monte Carlo simulations, we compare the performance of the GMM spatial estimator to that of spatial and non-spatial estimators and illustrate our approach with an application to new economic geography.