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A Benchmarking Approach to Forecast Combination

Author

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  • Trabelsi, Abdelwahed
  • Hillmer, Steven C

Abstract

This article is concerned with the development of a statistical model-based approach to optimally combine forecasts derived from an extrapolative model, such as an autoregressive integrated moving average (ARIMA) time series model, with forecasts of a particular characteristic of the same series obtained from independent sources. The methods derived combine the strengths of all forecasting approaches considered in the combinational scheme. The implications of the general theory are investigated in the context of some commonly encountered seasonal ARIMA models. An empirical example to illustrate the method is included.

Suggested Citation

  • Trabelsi, Abdelwahed & Hillmer, Steven C, 1989. "A Benchmarking Approach to Forecast Combination," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(3), pages 353-362, July.
    • Handle: RePEc:bes:jnlbes:v:7:y:1989:i:3:p:353-62
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    Citations

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    Cited by:

    1. Gomez, Nicolas & Guerrero, Victor M., 2006. "Restricted forecasting with VAR models: An analysis of a test for joint compatibility between restrictions and forecasts," International Journal of Forecasting, Elsevier, vol. 22(4), pages 751-770.
    2. Peter A. Zadrozny, 2016. "Real-Time State Space Method for Computing Smoothed Estimates of Future Revisions of U.S. Monthly Chained CPI," CESifo Working Paper Series 5897, CESifo.
    3. Alvarez, Luis J. & Delrieu, Juan C. & Jareño, Javier, 1997. "Restricted forecasts and economic target monitoring: An application to the Spanish Consumer Price Index," Journal of Policy Modeling, Elsevier, vol. 19(3), pages 333-349, June.
    4. Kourentzes, Nikolaos & Petropoulos, Fotios & Trapero, Juan R., 2014. "Improving forecasting by estimating time series structural components across multiple frequencies," International Journal of Forecasting, Elsevier, vol. 30(2), pages 291-302.
    5. Víctor M. Guerrero & Francisco Corona, 2018. "Retropolating some relevant series of Mexico's System of National Accounts at constant prices: The case of Mexico City's GDP," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 495-519, November.
    6. Victor Guerrero, 2005. "Restricted estimation of an adjusted time series: application to Mexico's industrial production index," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(2), pages 157-177.
    7. Sucharita Ghosh & Donald Lien, 2001. "Forecasting with preliminary data: a comparison of two methods," Applied Economics, Taylor & Francis Journals, vol. 33(6), pages 721-726.
    8. Victor Guerrero & Edmundo Berumen, 1998. "Forecasting electricity consumption with extra-model information provided by consumers," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(2), pages 283-299.
    9. Andrawis, Robert R. & Atiya, Amir F. & El-Shishiny, Hisham, 2011. "Combination of long term and short term forecasts, with application to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 27(3), pages 870-886, July.

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