Forecasting with Spatial Panel Data Baltagi, Badi H.; Bresson, Georges; Pirotte, Alain

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Baltagi, Badi H. ; Bresson, Georges ; Pirotte, Alain
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Computational Statistics and Data Analysis
Analysis; Mathematics
To link to full-text access for this article, visit this link: Byline: Badi H. Baltagi, Georges Bresson, Alain Pirotte Abstract: Various forecasts using panel data with spatial error correlation are compared using Monte Carlo experiments. The true data generating process is assumed to be a simple error component regression model with spatial remainder disturbances of the autoregressive or moving average type. The best linear unbiased predictor is compared with other forecasts ignoring spatial correlation, or ignoring heterogeneity due to the individual effects. In addition, the root mean squared error performance of these forecasts is examined under misspecification of the spatial error process, various spatial weight matrices, and heterogeneous rather than homogeneous panel data models. Article History: Received 8 December 2009; Revised 29 July 2010; Accepted 11 August 2010
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