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On winning forecasting competitions in economics

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Author Info

  • Michael P. Clements

    (Economics Department, Warwick University, Coventry, CV4 7AL, UK Nuffield College, Oxford, OX1 1NF, UK)

  • David F. Hendry

    (Economics Department, Warwick University, Coventry, CV4 7AL, UK Nuffield College, Oxford, OX1 1NF, UK)

Abstract

To explain which methods might win forecasting competitions on economic time series, we consider forecasting in an evolving economy subject to structural breaks, using mis-specified, data-based models. `Causal' models need not win when facing deterministic shifts, a primary factor underlying systematic forecast failure. We derive conditional forecast biases and unconditional (asymptotic) variances to show that when the forecast evaluation sample includes sub-periods following breaks, non-causal models will outperform at short horizons. This suggests using techniques which avoid systematic forecasting errors, including improved intercept corrections. An application to a small monetary model of the UK illustrates the theory.

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File URL: http://link.springer.de/link/service/journals/10108/papers/9001002/90010123.pdf
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Bibliographic Info

Article provided by Springer in its journal Spanish Economic Review.

Volume (Year): 1 (1999)
Issue (Month): 2 ()
Pages: 123-160

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Handle: RePEc:spr:specre:v:1:y:1999:i:2:p:123-160

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Related research

Keywords: Forecasting; structural breaks; differencing; intercept corrections;

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Citations

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Cited by:
  1. Corradi, V. & Swanson, N.R., 2000. "A Consistent Test for Nonlinear Out of Sample Predictive Accuracy," Discussion Papers 0012, Exeter University, Department of Economics.
  2. Hendry, David F. & Clements, Michael P., 2001. "Economic forecasting: some lessons from recent research," Working Paper Series 0082, European Central Bank.
  3. David Hendry, 2000. "Forecast Failure, Expectations Formation, and the Lucas Critique," Economics Series Working Papers 2002-W08, University of Oxford, Department of Economics.
  4. Francis X. Diebold & Lutz Kilian, 1999. "Unit Root Tests are Useful for Selecting Forecasting Models," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-063, New York University, Leonard N. Stern School of Business-.
  5. Cook, S., 1996. "Econometric methodology II: the role of the philosophy of science," Discussion Paper Series In Economics And Econometrics 9619, Economics Division, School of Social Sciences, University of Southampton.
  6. David Hendry, 2000. "A General Forecast-error Taxonomy," Econometric Society World Congress 2000 Contributed Papers 0608, Econometric Society.
  7. Qizilbash, M., 1994. "Corruption, temptation and guilt: moral character in economic theory," Discussion Paper Series In Economics And Econometrics 9419, Economics Division, School of Social Sciences, University of Southampton.
  8. Mukerji, S., 1995. "A theory of play for games in strategic form when rationality is not common knowledge," Discussion Paper Series In Economics And Econometrics 9519, Economics Division, School of Social Sciences, University of Southampton.
  9. Corradi, Valentina & Swanson, Norman R. & Olivetti, Claudia, 2001. "Predictive ability with cointegrated variables," Journal of Econometrics, Elsevier, vol. 104(2), pages 315-358, September.
  10. Valentina Corradi & Norman Swanson, 2003. "Some Recent Developments in Predictive Accuracy Testing With Nested Models and (Generic) Nonlinear Alternatives," Departmental Working Papers 200316, Rutgers University, Department of Economics.
  11. Dungey, Mardi & Fry, Renee, 2000. "A Multi-Country Structural VAR Model," Departmental Working Papers 2001-04, The Australian National University, Arndt-Corden Department of Economics.
  12. Hendry, David F. & Mizon, Grayham E., 2001. "Reformulating empirical macro-econometric modelling," Discussion Paper Series In Economics And Econometrics 0104, Economics Division, School of Social Sciences, University of Southampton.
  13. Valentina Corradi & Norman R. Swanson, 2003. "The Effect of Data Transformation on Common Cycle, Cointegration and Unit Root Tests: Monte Carlo Results and a Simple Test," Departmental Working Papers 200322, Rutgers University, Department of Economics.
  14. Chien-Chung Nieh & Hwey-Yun Yau & Ken Hung & Hong-Kou Ou & Shine Hung, 2013. "Cointegration and causal relationships among steel prices of Mainland China, Taiwan, and USA in the presence of multiple structural changes," Empirical Economics, Springer, vol. 44(2), pages 545-561, April.

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