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A Hybrid Forecasting Approach

Author

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  • Emilian Dobrescu

    (Center of Macroeconomic Modelling, Romanian Academy)

Abstract

The objective of the paper is to establish the appropriateness of integrating in predictive simulation an econometric estimation of a given variable into a standard moving average process (a linear algorithm with constant positive weights of distributed lags). The empirical search relates to the Romanian input-output tables collapsed into ten sectors. The database concerning the final output during 1989-2009 years is herein analyzed

Suggested Citation

  • Emilian Dobrescu, 2014. "A Hybrid Forecasting Approach," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 16(35), pages 390-390, February.
    • Handle: RePEc:aes:amfeco:v:1:y:2014:i:35:p:390
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    References listed on IDEAS

    as
    1. Dobrescu, Emilian, 2013. "Modelling the Sectoral Structure of the Final Output," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 59-89, October.
    2. Mariola Pilatowska, 2009. "The Combined Forecasts Using the Akaike Weights," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 9, pages 5-16.
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    4. Ravazzolo, F. & van Dijk, H.K. & Verbeek, M.J.C.M., 2007. "Predictive gains from forecast combinations using time-varying model weights," Econometric Institute Research Papers EI 2007-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Rodrigues, Bruno Dore & Stevenson, Maxwell J., 2013. "Takeover prediction using forecast combinations," International Journal of Forecasting, Elsevier, vol. 29(4), pages 628-641.
    6. Gregory, Allan W. & Yetman, James, 2004. "The evolution of consensus in macroeconomic forecasting," International Journal of Forecasting, Elsevier, vol. 20(3), pages 461-473.
    7. Gregory, Allan W & Smith, Gregor W & Yetman, James, 2001. "Testing for Forecast Consensus," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(1), pages 34-43, January.
    8. David C. Schirm, 2003. "A Comparative Analysis of the Rationality of Consensus Forecasts of U.S. Economic Indicators," The Journal of Business, University of Chicago Press, vol. 76(4), pages 547-562, October.
    9. Miller,Ronald E. & Blair,Peter D., 2009. "Input-Output Analysis," Cambridge Books, Cambridge University Press, number 9780521517133.
    10. Ager, P. & Kappler, M. & Osterloh, S., 2009. "The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach," International Journal of Forecasting, Elsevier, vol. 25(1), pages 167-181.
    11. Robert L. Winkler & Robert T. Clemen, 1992. "Sensitivity of Weights in Combining Forecasts," Operations Research, INFORMS, vol. 40(3), pages 609-614, June.
    12. Miller,Ronald E. & Blair,Peter D., 2009. "Input-Output Analysis," Cambridge Books, Cambridge University Press, number 9780521739023.
    13. Emilian Dobrescu & Viorel Gaftea, 2012. "On the Accuracy of RAS Method in an Emergent Economy," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 14(32), pages 502-521, June.
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    More about this item

    Keywords

    final output extrapolation; hybrid approach.;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models

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