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Tests for multiple forecast encompassing

Author

Listed:
  • David Harvey

    (Department of Economics, Loughborough University, Loughborough, Leicestershire, LE11 3TU, UK)

  • Paul Newbold

    (School of Economics, University of Nottingham, University Park, Nottingham, NG7 2RD, UK)

Abstract

In the evaluation of economic forecasts, it is frequently the case that comparisons are made between a number of competing predictors. A natural question to ask in such contexts is whether one forecast encompasses its competitors, in the sense that they contain no useful information not present in the superior forecast. We develop tests for this notion of multiple forecast encompassing which are robust to properties expected in the forecast errors, and apply the tests to forecasts of UK growth and inflation. Copyright © 2000 John Wiley & Sons, Ltd.

Suggested Citation

  • David Harvey & Paul Newbold, 2000. "Tests for multiple forecast encompassing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 471-482.
    • Handle: RePEc:jae:japmet:v:15:y:2000:i:5:p:471-482
    as

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    References listed on IDEAS

    as
    1. Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(4), pages 671-690.
    2. 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 254-259, April.
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    4. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
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    7. Pesaran, M. Hashem & Timmermann, Allan G., 1994. "A generalization of the non-parametric Henriksson-Merton test of market timing," Economics Letters, Elsevier, vol. 44(1-2), pages 1-7.
    8. 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.
    Full references (including those not matched with items on IDEAS)

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