Robust Approaches to Forecasting
AbstractWe investigate alternative robust approaches to forecasting, using a new class of robust devices, contrasted with equilibrium correction models.� Their forecasting properties are derived facing a range of likely empirical problems at the forecast origin, including measurement errors, implulses, omitted variables, unanticipated location shifts and incorrectly included variables that experience a shift.� We derive the resulting forecast biases and error variances, and indicate when the methods are likely to perform well.� The robust methods are applied to forecasting US GDP using autoregressive models, and also to autoregressive models with factors extracted from a large dataset of macroeconomic variables.� We consider forecasting performance over the Great Recession, and over an earlier more quiescent period.
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Bibliographic InfoPaper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 697.
Date of creation: 30 Jan 2014
Date of revision:
Robust forecasts; Smoothed Forecasting devices; Factor models; GDP forecasts; Location shifts;
Find related papers by JEL classification:
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2014-04-11 (All new papers)
- NEP-ECM-2014-04-11 (Econometrics)
- NEP-FOR-2014-04-11 (Forecasting)
- NEP-GER-2014-04-11 (German Papers)
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- Margaret M. McConnell & Gabriel Perez Quiros, 1998.
"Output fluctuations in the United States: what has changed since the early 1980s?,"
41, Federal Reserve Bank of New York.
- Gabriel Perez-Quiros & Margaret M. McConnell, 2000. "Output Fluctuations in the United States: What Has Changed since the Early 1980's?," American Economic Review, American Economic Association, vol. 90(5), pages 1464-1476, December.
- Margaret McConnell & Gabriel Perez Quiros, 2000. "Output fluctuations in the United States: what has changed since the early 1980s?," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
- Margaret M. McConnell & Gabriel Perez Quiros, 1997. "Output fluctuations in the United States: what has changed since the early 1980s?," Research Paper 9735, Federal Reserve Bank of New York.
- Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2000.
"The use and abuse of "real-time" data in economic forecasting,"
0004, Federal Reserve Bank of Dallas.
- Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2003. "The Use and Abuse of Real-Time Data in Economic Forecasting," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 618-628, August.
- Evan Koenig & Sheila Dolmas & Jeremy M. Piger, 2002. "The use and abuse of 'real-time' data in economic forecasting," Working Papers 2001-015, Federal Reserve Bank of St. Louis.
- Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2000. "The use and abuse of "real-time" data in economic forecasting," International Finance Discussion Papers 684, Board of Governors of the Federal Reserve System (U.S.).
- N. Kundan Kishor & Evan F. Koenig, 2009.
"VAR Estimation and Forecasting When Data Are Subject to Revision,"
Journal of Business & Economic Statistics,
Taylor & Francis Journals, vol. 30(2), pages 181-190, July.
- N. Kundan Kishor & Evan F. Koenig, 2005. "VAR estimation and forecasting when data are subject to revision," Working Papers 0501, Federal Reserve Bank of Dallas.
- Clements, Michael P. & Galvão, Ana Beatriz, 2013. "Forecasting with vector autoregressive models of data vintages: US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 29(4), pages 698-714.
- Castle, Jennifer L. & Fawcett, Nicholas W.P. & Hendry, David F., 2010.
"Forecasting with equilibrium-correction models during structural breaks,"
Journal of Econometrics,
Elsevier, vol. 158(1), pages 25-36, September.
- Jennifer Castle & David Hendry & Nicholas W.P. Fawcett, 2008. "Forecasting with Equilibrium-correction Models during Structural Breaks," Economics Series Working Papers 408, University of Oxford, Department of Economics.
- Pena, Daniel & Poncela, Pilar, 2004. "Forecasting with nonstationary dynamic factor models," Journal of Econometrics, Elsevier, vol. 119(2), pages 291-321, April.
- Ben S. Bernanke & Jean Boivin, 2001.
"Monetary Policy in a Data-Rich Environment,"
NBER Working Papers
8379, National Bureau of Economic Research, Inc.
- Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000.
"The Generalized Dynamic-Factor Model: Identification And Estimation,"
The Review of Economics and Statistics,
MIT Press, vol. 82(4), pages 540-554, November.
- Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 1999. "The Generalized Dynamic Factor Model: Identification and Estimation," CEPR Discussion Papers 2338, C.E.P.R. Discussion Papers.
- Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
- James H. Stock & Mark W. Watson, 1989.
"New Indexes of Coincident and Leading Economic Indicators,"
in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409
National Bureau of Economic Research, Inc.
- Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
- Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2012.
"Model selection when there are multiple breaks,"
Journal of Econometrics,
Elsevier, vol. 169(2), pages 239-246.
- Anthony Garratt & Kevin Lee & Emi Mise & Kalvinder Shields, 2006.
"Real Time Representations of the Output Gap,"
Birkbeck Working Papers in Economics and Finance
0619, Birkbeck, Department of Economics, Mathematics & Statistics.
- Kevin Lee & Emi Mise & Kalvinder Shields & Tony Garratt, 2005. "Real time Representations of the Output Gap," Money Macro and Finance (MMF) Research Group Conference 2005 26, Money Macro and Finance Research Group.
- Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2013. "Forecasting by factors, by variables, by both or neither?," Journal of Econometrics, Elsevier, vol. 177(2), pages 305-319.
- Patterson, K. D., 2003. "Exploiting information in vintages of time-series data," International Journal of Forecasting, Elsevier, vol. 19(2), pages 177-197.
- P. Geoffrey Allen & Robert Fildes, 2005. "Levels, Differences and ECMs - Principles for Improved Econometric Forecasting," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 881-904, December.
- Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
- J. Steven Landefeld & Eugene P. Seskin & Barbara M. Fraumeni, 2008. "Taking the Pulse of the Economy: Measuring GDP," Journal of Economic Perspectives, American Economic Association, vol. 22(2), pages 193-216, Spring.
- Guillaume Chevillon, 2005.
"Direct multi-step estimation and forecasting,"
Documents de Travail de l'OFCE
2005-10, Observatoire Francais des Conjonctures Economiques (OFCE).
- repec:taf:jnlbes:v:30:y:2012:i:2:p:181-190 is not listed on IDEAS
- Michael P. Clements & Ana Beatriz Galvão, 2013. "Real‐Time Forecasting Of Inflation And Output Growth With Autoregressive Models In The Presence Of Data Revisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(3), pages 458-477, 04.
- 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.
- Fildes, Robert & Stekler, Herman, 2002. "Reply to the comments on 'The state of macroeconomic forecasting'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 503-505, December.
Blog mentionsAs found by EconAcademics.org, the blog aggregator for Economics research:
- In all probability, economic forecasts are probably wrong
by David F Hendry, Director, Economic Modelling, The Institute for New Economic Thinking at the Oxford Martin School at University of Oxford in The Conversation on 2014-07-18 12:06:35
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