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Pooling of Forecasts

We consider forecasting using a combination, when no model coincides with a non-constant data generation process (DGP). Practical experience suggests that combining forecasts adds value, and can even dominate the best individual device. We show why this can occur when forecasting models are differentially mis-specified, and is likely to occur when the DGP is subject to deterministic shifts. Moreover, averaging may then dominate over estimated weights in the combination. Finally, it cannot be proved that only non-encompassed devices should be retained in the combination. Empirical and Monte Carlo illustrations confirm the analysis.

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Paper provided by Economics Group, Nuffield College, University of Oxford in its series Economics Papers with number 2002-W9.

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Length: 26 pages
Date of creation: 01 Oct 2001
Date of revision:
Handle: RePEc:nuf:econwp:0209
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  1. Ericsson, Neil R., 1992. "Parameter constancy, mean square forecast errors, and measuring forecast performance: An exposition, extensions, and illustration," Journal of Policy Modeling, Elsevier, vol. 14(4), pages 465-495, August.
  2. Ericsson, Neil R & Marquez, Jaime, 1993. "Encompassing the Forecasts of U.S. Trade Balance Models," The Review of Economics and Statistics, MIT Press, vol. 75(1), pages 19-31, February.
  3. 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.
  4. David Hendry & Michael P. Clements, 2001. "Economic Forecasting: Some Lessons from Recent Research," Economics Series Working Papers 78, University of Oxford, Department of Economics.
  5. Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," Review of Economic Studies, Oxford University Press, vol. 53(4), pages 671-690.
  6. Clements, M.P. & Hendry, D., 1992. "On the Limitations of Comparing Mean Square Forecast Errors," Economics Series Working Papers 99138, University of Oxford, Department of Economics.
  7. Hendry, David F., 2000. "On detectable and non-detectable structural change," Structural Change and Economic Dynamics, Elsevier, vol. 11(1-2), pages 45-65, July.
  8. Diebold, Francis X., 1989. "Forecast combination and encompassing: Reconciling two divergent literatures," International Journal of Forecasting, Elsevier, vol. 5(4), pages 589-592.
  9. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
  10. Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper 9525, Federal Reserve Bank of New York.
  11. Hendry, David F & Doornik, Jurgen A, 1997. "The Implications for Econometric Modelling of Forecast Failure," Scottish Journal of Political Economy, Scottish Economic Society, vol. 44(4), pages 437-61, September.
  12. Coulson, N.E. & Robins, R.P., 1989. "Forecast Combination In A Dynamic Setting," Papers 8-88-4, Pennsylvania State - Department of Economics.
  13. 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.
  14. Diebold, Francis X, 1988. "Serial Correlation and the Combination of Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(1), pages 105-11, January.
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