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Monitoring Forecasting Combinations with Semiparametric Regression Models

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  • Antonis Michis

    ()
    (Central Bank of Cyprus)

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    Abstract

    In this study, a modelling framework is proposed for evaluating the accuracy of forecasting combinations when the number of available forecasts is large and changes in time. Squared forecast errors are modelled with a semiparametric additive regression model where the linear part involves indicator variables reflecting the time period when the forecast is performed and the nonparametric part involves a smooth function of the number of individual forecasts entering the combinations. The partial regression estimates permit two-dimensional plots of the relationship between squared forecast errors and the number of forecasts entering the combinations and can be used to assess the contribution of additional forecasts in reducing the forecast errors. The method is demonstrated with six empirical applications using macroeconomic forecasts published by Her Majesty’s Treasury.

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    File URL: http://www.centralbank.gov.cy/media/pdf/NPWPE_No2_052012.pdf
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    Bibliographic Info

    Paper provided by Central Bank of Cyprus in its series Working Papers with number 2012-02.

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    Length: 21 pages
    Date of creation: May 2012
    Date of revision:
    Handle: RePEc:cyb:wpaper:2012-02

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    Web page: http://www.centralbank.gov.cy/nqcontent.cfm?a_id=1
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    Related research

    Keywords: Forecasting combinations; semiparametric models; forecast errors.;

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    1. Turgut Kisinbay, 2007. "The Use of Encompassing Tests for Forecast Combinations," IMF Working Papers 07/264, International Monetary Fund.
    2. Swanson, Norman R & Zeng, Tian, 2001. "Choosing among Competing Econometric Forecasts: Regression-Based Forecast Combination Using Model Selection," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(6), pages 425-40, September.
    3. Francis X. Diebold, 1989. "Forecast combination and encompassing: reconciling two divergent literatures," Finance and Economics Discussion Series 80, Board of Governors of the Federal Reserve System (U.S.).
    4. Mauro Costantini & Robert M. Kunst, 2011. "Combining forecasts based on multiple encompassing tests in a macroeconomic core system," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(6), pages 579-596, September.
    5. 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.
    6. 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.
    7. 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.
    8. David Harvey & Paul Newbold, 2000. "Tests for multiple forecast encompassing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 471-482.
    9. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    10. Spyros Makridakis & Robert L. Winkler, 1983. "Averages of Forecasts: Some Empirical Results," Management Science, INFORMS, vol. 29(9), pages 987-996, September.
    11. Fang, Yue, 2003. "Forecasting combination and encompassing tests," International Journal of Forecasting, Elsevier, vol. 19(1), pages 87-94.
    12. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-89, June.
    13. Chong, Yock Y & Hendry, David F, 1986. "Econometric Evaluation of Linear Macro-Economic Models," Review of Economic Studies, Wiley Blackwell, vol. 53(4), pages 671-90, August.
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