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A Dynamic Panel Data Approach to the Forecasting of the GDP of German Lander

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Author Info
Konstantin Arkadievich Kholodilin
Boriss Siliverstovs
Stefan Kooths

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Abstract

In this paper, we make multi-step forecasts of the annual growth rates of the real GDP for each of the 16 German Lander simultaneously. We apply dynamic panel models accounting for spatial dependence between regional GDP. We find that both pooling and accounting for spatial effects help to improve the forecast performance substantially. We demonstrate that the effect of accounting for spatial dependence is more pronounced for longer forecasting horizons (the forecast accuracy gain is about 9% for a 1-year horizon and exceeds 40% for a 5-year horizon). We recommend incorporating a spatial dependence structure into regional forecasting models, especially when long-term forecasts are made.

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File URL: http://www.informaworld.com/openurl?genre=article&doi=10.1080/17421770801996656&magic=repec&7C&7C8674ECAB8BB840C6AD35DC6213A474B5
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Publisher Info
Article provided by Taylor and Francis Journals in its journal Spatial Economic Analysis.

Volume (Year): 3 (2008)
Issue (Month): 2 ()
Pages: 195-207
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Handle: RePEc:taf:specan:v:3:y:2008:i:2:p:195-207

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Related research
Keywords: German Lander; forecasting; dynamic panel model; spatial autocorrelation;

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References listed on IDEAS
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  1. Stefan Bach & Dieter Vesper, 2000. "Finanzpolitik und Wiedervereinigung: Bilanz nach 10 Jahren," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 69(2), pages 194-224.
  2. Longhi, Simonetta & Nijkamp, Peter, 2006. "Forecasting regional labor market developments under spatial heterogeneity and spatial correlation," Serie Research Memoranda 0015, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics. [Downloadable!]
  3. Roberto Patuelli & Daniel A. Griffith & Michael Tiefelsdorf & Peter Nijkamp, 2006. "The Use of Spatial Filtering Techniques: The Spatial and Space-time Structure of German Unemployment Data," Tinbergen Institute Discussion Papers 06-049/3, Tinbergen Institute. [Downloadable!]
  4. Herbert Brücker & Boriss Siliverstovs, 2006. "On the estimation and forecasting of international migration: how relevant is heterogeneity across countries?," Empirical Economics, Springer, vol. 31(3), pages 735-754, September. [Downloadable!] (restricted)
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  5. Badi H. Baltagi & Georges Bresson & Alain Pirotte, 2004. "Tobin q: Forecast performance for hierarchical Bayes, shrinkage, heterogeneous and homogeneous panel data estimators," Empirical Economics, Springer, vol. 29(1), pages 107-113, January. [Downloadable!] (restricted)
  6. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June. [Downloadable!] (restricted)
  7. Badi H. Baltagi & James M. Griffin & Weiwen Xiong, 2000. "To Pool Or Not To Pool: Homogeneous Versus Hetergeneous Estimations Applied to Cigarette Demand," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 117-126, February. [Downloadable!] (restricted)
  8. Erich Langmantel, 1999. "Das ifo Geschäftsklima als Indikator für die Prognose des Bruttoinlandsprodukts," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 52(16-17), pages 16-21, October.
  9. Konstantin A. Kholodilin & Boriss Siliverstovs, 2005. "On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence," Discussion Papers of DIW Berlin 522, DIW Berlin, German Institute for Economic Research. [Downloadable!]
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  10. Christian Dreger & Konstantin A. Kholodilin, 2006. "Prognosen der regionalen Konjunkturentwicklung," Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 73(34), pages 469-474. [Downloadable!]
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  11. Badi H. Baltagi & Georges Bresson & James M. Griffin & Alain Pirotte, 2002. "Homogeneous, heterogeneous or shrinkage estimators? Some empirical evidence from French regional gasoline consumption," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 A6-4, International Conferences on Panel Data. [Downloadable!]
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  12. Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2002. "Comparison of forecast performance for homogeneous, heterogeneous and shrinkage estimators: Some empirical evidence from US electricity and natural-gas consumption," Economics Letters, Elsevier, vol. 76(3), pages 375-382, August. [Downloadable!] (restricted)
  13. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-59, April.
  14. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  15. Stefan Mittnik & Peter Zadrozny, 2004. "Forecasting Quarterly German GDP at Monthly Intervals Using Monthly IFO Business Conditions Data," CESifo Working Paper Series CESifo Working Paper No. , CESifo Group Munich. [Downloadable!]
  16. Schumacher, Christian, 2005. "Forecasting German GDP using alternative factor models based on large datasets," Discussion Paper Series 1: Economic Studies 2005,24, Deutsche Bundesbank, Research Centre. [Downloadable!]
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  17. Dreger, Christian & Schumacher, Christian, 2002. "Estimating Large-Scale Factor Models for Economic Activity in Germany: Do They Outperform Simpler Models?," Discussion Paper Series 26321, Hamburg Institute of International Economics. [Downloadable!]
  18. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
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