Estimating and Forecasting with a Dynamic Spatial Panel Data Model

27 Pages Posted: 10 Jan 2014

See all articles by Badi H. Baltagi

Badi H. Baltagi

Syracuse University - Maxwell School of Citizenship and Public Affairs; IZA Institute of Labor Economics; Syracuse University - Center for Policy Research

Bernard Fingleton

University of Cambridge - Department of Land Economy; University of Cambridge - Department of Land Economy

Alain Pirotte

ERMES (CNRS), Université Panthéon-Assas Paris II; INRETS-DEST

Date Written: February 2014

Abstract

This study 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 generalized method of moments (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.

JEL Classification: C33

Suggested Citation

Baltagi, Badi H. and Fingleton, Bernard and Fingleton, Bernard and Pirotte, Alain, Estimating and Forecasting with a Dynamic Spatial Panel Data Model (February 2014). Oxford Bulletin of Economics and Statistics, Vol. 76, Issue 1, pp. 112-138, 2014, Available at SSRN: https://ssrn.com/abstract=2377080 or http://dx.doi.org/10.1111/obes.12011

Badi H. Baltagi (Contact Author)

Syracuse University - Maxwell School of Citizenship and Public Affairs ( email )

400 Eggers Hall
Syracuse, NY 13244
United States

IZA Institute of Labor Economics

Schaumburg-Lippe-Str. 7 / 9
Bonn, D-53072
Germany

Syracuse University - Center for Policy Research ( email )

Syracuse, NY 13244
United States
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HOME PAGE: http://www.maxwell.syr.edu/cpr_about.aspx?id=6442451316

Bernard Fingleton

University of Cambridge - Department of Land Economy ( email )

19 Silver Street
Cambridge, CB3 9EP
United Kingdom

University of Cambridge - Department of Land Economy ( email )

19 Silver Street
Cambridge, CB3 9EP
United Kingdom

Alain Pirotte

ERMES (CNRS), Université Panthéon-Assas Paris II ( email )

12 Place du Panthéon
Paris, Cedex 5, 75005
France

INRETS-DEST

23 rue Alfred Nobel
Champs sur Marne, 77420
France

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