Forecasting with Spatial Panel Data

Badi Baltagi, Georges Bresson and Alain Pirotte ()
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Alain Pirotte: University of Paris 2

No 4242, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: This paper compares various forecasts using panel data with spatial error correlation. 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, using Monte Carlo experiments. In addition, we check the performance of these forecasts under misspecification of the spatial error process, various spatial weight matrices, and heterogeneous rather than homogeneous panel data models.

Keywords: BLUP; panel data; spatial dependence; forecasting; heterogeneity (search for similar items in EconPapers)
JEL-codes: C33 (search for similar items in EconPapers)
Pages: 37 pages
Date: 2009-06
New Economics Papers: this item is included in nep-ecm, nep-for, nep-geo and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Published - published in: Computational Statistics and Data Analysis, 2012, 56 (11), 3381–3397

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Related works:
Journal Article: Forecasting with spatial panel data (2012)
Working Paper: Forecasting with Spatial Panel Data (2007)
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