IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this article

Combining Survey Forecasts and Time Series Models: The Case of the Euribor

  • Krüger Fabian

    ()

    (Universität Konstanz, Fachbereich Wirtschaftswissenschaften, Universitätsstraße 10, 78464 Konstanz, Germany, and CoFE)

  • Pohlmeier Winfried

    ()

    (Universität Konstanz, Fachbereich Wirtschaftswissenschaften, Universitätsstraße 10, 78464 Konstanz, Germany, and CoFE, ZEW)

  • Mokinski Frieder

    ()

    (Zentrum für Europäische Wirtschaftsforschung (ZEW) Abteilung für Internationale Finanzmärkte und Finanzmanagement L 7, 1, 68161 Mannheim, Germany)

This paper reinterprets Maganelli’s (2009) idea of “Forecasting with Judgment” to obtain a dynamic algorithm for combining survey expectations data and time series models for macroeconomic forecasting. Existing combination approaches typically obtain combined forecasts by linearly weighting individual forecasts. The approach presented here instead uses survey forecasts in the estimation stage of a time series model. Thus an estimate of the model parameters is obtained that reflects two sources of information: a history of realizations of the variables that are involved in the time series model and survey expectations on the future course of the variable that is to be forecast. The idea at the estimation stage is to shrink parameter estimates towards values that are compatible (in an appropriate sense) with the survey forecasts that have been observed. It is exemplified how this approach can be applied to different autoregressive time series models. In an empirical application, the approach is used to forecast the three-month Euribor at a six-month horizon.

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: http://www.degruyter.com/view/j/jbnst.2011.231.issue-1/jbnst-2011-0106/jbnst-2011-0106.xml?format=INT
Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Article provided by De Gruyter in its journal Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik).

Volume (Year): 231 (2011)
Issue (Month): 1 (February)
Pages: 63-81

as
in new window

Handle: RePEc:jns:jbstat:v:231:y:2011:i:1:p:63-81
Contact details of provider: Web page: http://www.degruyter.com

Order Information: Web: http://www.degruyter.com/view/j/jbnst

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. Mario Forni & Domenico Giannone & Marco Lippi & Lucrezia Reichlin, 2007. "Opening the Black Box: Structural Factor Models with Large Cross-Sections," Center for Economic Research (RECent) 008, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
  2. Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010. "Forecast Combinations," Working Papers 2010-04, Banco de México.
  3. Francis X. Diebold & Canlin Li, 2002. "Forecasting the Term Structure of Government Bond Yields," Center for Financial Institutions Working Papers 02-34, Wharton School Center for Financial Institutions, University of Pennsylvania.
  4. 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.
  5. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.
  6. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
  7. Manganelli, Simone, 2009. "Forecasting With Judgment," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 553-563.
  8. Kwiatkowski, D. & Phillips, P.C.B. & Schmidt, P., 1990. "Testing the Null Hypothesis of Stationarity Against the Alternative of Unit Root : How Sure are we that Economic Time Series have a Unit Root?," Papers 8905, Michigan State - Econometrics and Economic Theory.
  9. West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, Elsevier.
  10. Aiolfi, Marco & Timmermann, Allan, 2006. "Persistence in forecasting performance and conditional combination strategies," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 31-53.
  11. González, Andrés & Hubrich, Kirstin & Teräsvirta, Timo, 2011. "Forecasting inflation with gradual regime shifts and exogenous information," Working Paper Series 1363, European Central Bank.
  12. Jose, Victor Richmond R. & Winkler, Robert L., 2008. "Simple robust averages of forecasts: Some empirical results," International Journal of Forecasting, Elsevier, vol. 24(1), pages 163-169.
  13. Inoue, Atsushi & Kilian, Lutz, 2008. "How Useful Is Bagging in Forecasting Economic Time Series? A Case Study of U.S. Consumer Price Inflation," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 511-522, June.
  14. Jeremy Smith & Kenneth F. Wallis, 2009. "A Simple Explanation of the Forecast Combination Puzzle," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 331-355, 06.
  15. Nolte, Ingmar & Pohlmeier, Winfried, 2007. "Using forecasts of forecasters to forecast," International Journal of Forecasting, Elsevier, vol. 23(1), pages 15-28.
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:jns:jbstat:v:231:y:2011:i:1:p:63-81. 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: (Peter Golla)

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.