IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper

Forecasting GDP at the regional level with many predictors

  • Lehmann, Robert
  • Wohlrabe, Klaus

In this paper, we assess the accuracy of macroeconomic forecasts at the regional level using a large data set at quarterly frequency. We forecast gross domestic product (GDP) for two German states (Free State of Saxony and Baden- Württemberg) and Eastern Germany. We overcome the problem of a ’data-poor environment’ at the sub-national level by complementing various regional indicators with more than 200 national and international indicators. We calculate single– indicator, multi–indicator, pooled and factor forecasts in a pseudo real–time setting. Our results show that we can significantly increase forecast accuracy compared to an autoregressive benchmark model, both for short and long term predictions. Furthermore, regional indicators play a crucial role for forecasting regional GDP.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: https://epub.ub.uni-muenchen.de/17104/1/Lehmann_Wohlrabe_2013.pdf
Download Restriction: no

Paper provided by University of Munich, Department of Economics in its series Discussion Papers in Economics with number 17104.

as
in new window

Length:
Date of creation: 14 Sep 2013
Date of revision:
Handle: RePEc:lmu:muenec:17104
Contact details of provider: Postal:
Ludwigstr. 28, 80539 Munich, Germany

Phone: +49-(0)89-2180-3405
Fax: +49-(0)89-2180-3510
Web page: http://www.vwl.uni-muenchen.de

More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Konstantin A. Kholodilin & Boriss Siliverstovs, 2006. "On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 226(3), pages 234-259, May.
  2. Christian Schumacher, 2007. "Forecasting German GDP using alternative factor models based on large datasets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 271-302.
  3. Hans-Ulrich Brautzsch & Udo Ludwig, 2002. "Vierteljährliche Entstehungsrechnung des Bruttoinlandsprodukts für Ostdeutschland: Sektorale Bruttowertschöpfung," IWH Discussion Papers 164, Halle Institute for Economic Research.
  4. Giorgio Bodo & Roberto Golinelli & Giuseppe Parigi, 2000. "Forecasting Industrial Production in the Euro Area," Temi di discussione (Economic working papers) 370, Bank of Italy, Economic Research and International Relations Area.
  5. Kai Carstensen & Klaus Wohlrabe & Christina Ziegler, 2010. "Predictive Ability of Business Cycle Indicators under Test: A Case Study for the Euro Area Industrial Production," CESifo Working Paper Series 3158, CESifo Group Munich.
  6. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
  7. Schanne, N. & Wapler, R. & Weyh, A., 2010. "Regional unemployment forecasts with spatial interdependencies," International Journal of Forecasting, Elsevier, vol. 26(4), pages 908-926, October.
  8. Sandra Eickmeier & Christina Ziegler, 2008. "How successful are dynamic factor models at forecasting output and inflation? A meta-analytic approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 237-265.
  9. Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
  10. Katja Drechsel & Laurent Maurin, 2011. "Flow of conjunctural information and forecast of euro area economic activity," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(3), pages 336-354, April.
  11. Katja Drechsel & R. Scheufele, 2013. "Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment," IWH Discussion Papers 7, Halle Institute for Economic Research.
  12. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  13. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
  14. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2007. "A Two-Step Estimator for Large Approximate Dynamic Factor Models Based on Kalman Filtering," CEPR Discussion Papers 6043, C.E.P.R. Discussion Papers.
  15. Joachim Ragnitz, 2009. "East Germany Today: Successes and Failures," CESifo DICE Report, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 7(4), pages 51-58, 01.
  16. Vladimir Kuzin & Massimiliano Marcellino & Christian Schumacher, 2009. "Pooling versus Model Selection for Nowcasting with Many Predictors: An Application to German GDP," Economics Working Papers ECO2009/13, European University Institute.
  17. Costantini, Mauro & Pappalardo, Carmine, 2010. "A hierarchical procedure for the combination of forecasts," International Journal of Forecasting, Elsevier, vol. 26(4), pages 725-743, October.
  18. Konstantin A. Kholodilin & Boriss Siliverstovs & Stefan Kooths, 2007. "A Dynamic Panel Data Approach to the Forecasting of the GDP of German Länder," Discussion Papers of DIW Berlin 664, DIW Berlin, German Institute for Economic Research.
  19. Marc Hallin & Mario Forni & Marco Lippi & Lucrezia Reichlin, 2003. "Do financial variables help forecasting inflation and real activity in the Euro area ?," ULB Institutional Repository 2013/2123, ULB -- Universite Libre de Bruxelles.
  20. Christian Dreger & Konstantin A. Kholodilin, 2006. "Prognosen der regionalen Konjunkturentwicklung," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 73(34), pages 469-474.
  21. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2003. "Leading Indicators for Euro-area Inflation and GDP Growth," Working Papers 235, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  22. Eickmeier, Sandra & Ng, Tim, 2011. "Forecasting national activity using lots of international predictors: An application to New Zealand," International Journal of Forecasting, Elsevier, vol. 27(2), pages 496-511, April.
  23. Beate Schirwitz & Christian Seiler & Klaus Wohlrabe, 2009. "Regionale Konjunkturzyklen in Deutschland – Teil I: Die Datenlage," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(13), pages 18-24, 07.
  24. Schumacher, Christian, 2009. "Factor forecasting using international targeted predictors: the case of German GDP," Discussion Paper Series 1: Economic Studies 2009,10, Deutsche Bundesbank, Research Centre.
  25. Gerit Vogt, 2010. "VAR-Prognose-Pooling : ein Ansatz zur Verbesserung der Informationsgrundlage der ifo Dresden Konjunkturprognosen," ifo Dresden berichtet, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 17(02), pages 32-40, 04.
  26. Beate Schirwitz & Christian Seiler & Klaus Wohlrabe, 2009. "Regionale Konjunkturzyklen in Deutschland – Teil II: Die Zyklendatierung," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(14), pages 24-31, 07.
  27. Gerit Vogt, 2009. "Konjunkturprognose in Deutschland. Ein Beitrag zur Prognose der gesamtwirtschaftlichen Entwicklung auf Bundes- und Länderebene," ifo Beiträge zur Wirtschaftsforschung, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 36, 7.
  28. Wolfgang Nierhaus, 2007. "Vierteljährliche volkswirtschaftliche Gesamtrechnungen für Sachsen mit Hilfe temporaler Disaggregation," ifo Dresden berichtet, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 14(04), pages 24-36, 08.
  29. Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
  30. Chow, Gregory C & Lin, An-loh, 1971. "Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Time Series by Related Series," The Review of Economics and Statistics, MIT Press, vol. 53(4), pages 372-75, November.
  31. Robert Lehmann & Wolf-Dietmar Speich & Roman Straube & Gerit Vogt, 2010. "Funktioniert der ifo Konjunkturtest auch in wirtschaftlichen Krisenzeiten? : eine Analyse der Zusammenhänge zwischen ifo Geschäftsklima und amtlichen Konjunkturdaten für Sachsen," ifo Dresden berichtet, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 17(03), pages 8-14, 06.
  32. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
  33. Wenzel, Lars, 2013. "Forecasting regional growth in Germany: A panel approach using business survey data," HWWI Research Papers 133, Hamburg Institute of International Economics (HWWI).
  34. 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.
  35. Kopoin, Alexandre & Moran, Kevin & Paré, Jean-Pierre, 2013. "Forecasting regional GDP with factor models: How useful are national and international data?," Economics Letters, Elsevier, vol. 121(2), pages 267-270.
  36. Bandholz, Harm & Funke, Michael, 2003. "Die Konstruktion und Schätzung eines Konjunkturfrühindikators für Hamburg," Wirtschaftsdienst – Zeitschrift für Wirtschaftspolitik (1949 - 2007), ZBW – German National Library of Economics / Leibniz Information Centre for Economics, vol. 83(8), pages 540-548.
  37. Klaus Abberger & Klaus Wohlrabe, 2006. "Einige Prognoseeigenschaften des ifo Geschäftsklimas - Ein Überblick über die neuere wissenschaftliche Literatur," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(22), pages 19-26, November.
  38. Michael P. Clements & Ana Beatriz Galvao, 2009. "Forecasting US output growth using leading indicators: an appraisal using MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(7), pages 1187-1206.
  39. Vladimir Kuzin & Massimiliano Marcellino & Christian Schumacher, 2013. "Pooling Versus Model Selection For Nowcasting Gdp With Many Predictors: Empirical Evidence For Six Industrialized Countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(3), pages 392-411, 04.
  40. Simonetta Longhi & Peter Nijkamp, 2007. "Forecasting Regional Labor Market Developments under Spatial Autocorrelation," International Regional Science Review, , vol. 30(2), pages 100-119, April.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:lmu:muenec:17104. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Tamilla Benkelberg)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.