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Data revisions and forecasting

Author

Listed:
  • Frederick Joutz
  • H. O. Stekler

Abstract

The relationship between two sets of GNP data, the earliest and the first revisions, is examined. This comparison enables us to determine whether the early numbers are valuable to forecasters. The analysis uses two methods. The first is based on a technique which has been used to evaluate whether financial and economic forecasts are valuable to the users. The second approach uses time series techniques. We conclude that revisions to the 15-day estimates that occur when the 45-day numbers are released are successful and that the 15-day numbers are useful to forecasters.

Suggested Citation

  • Frederick Joutz & H. O. Stekler, 1998. "Data revisions and forecasting," Applied Economics, Taylor & Francis Journals, vol. 30(8), pages 1011-1016.
    • Handle: RePEc:taf:applec:v:30:y:1998:i:8:p:1011-1016
    DOI: 10.1080/000368498325183
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    Citations

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    Cited by:

    1. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
    2. Sinclair, Tara M. & Stekler, H.O., 2013. "Examining the quality of early GDP component estimates," International Journal of Forecasting, Elsevier, vol. 29(4), pages 736-750.
    3. Christis Tombazos, 2003. "New light on the 'impressionistic view' of the balancing item in Australia's balance of payments accounts," Applied Economics, Taylor & Francis Journals, vol. 35(12), pages 1369-1378.
    4. Jordi Pons-Novell, 2006. "An analysis of a panel of Spanish GDP forecasts," Applied Economics, Taylor & Francis Journals, vol. 38(11), pages 1287-1292.
    5. H. Bakhshi & G. Kapetanios & T. Yates, 2005. "Rational expectations and fixed-event forecasts: An application to UK inflation," Empirical Economics, Springer, vol. 30(3), pages 539-553, October.
    6. Sinclair, Tara M., 2019. "Characteristics and implications of Chinese macroeconomic data revisions," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1108-1117.
    7. Harvey, David I. & Newbold, Paul, 2003. "The non-normality of some macroeconomic forecast errors," International Journal of Forecasting, Elsevier, vol. 19(4), pages 635-653.
    8. Mihaela Simionescu, 2014. "Directional accuracy for inflation and unemployment rate predictions in Romania," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 7(2), pages 129-138, September.
    9. Blaskowitz, Oliver J. & Herwartz, Helmut, 2008. "Testing directional forecast value in the presence of serial correlation," SFB 649 Discussion Papers 2008-073, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. repec:hum:wpaper:sfb649dp2008-073 is not listed on IDEAS
    11. Eicher, Theo S. & Kuenzel, David J. & Papageorgiou, Chris & Christofides, Charis, 2019. "Forecasts in times of crises," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1143-1159.
    12. Jordi Pons, 2001. "The rationality of price forecasts: a directional analysis," Applied Financial Economics, Taylor & Francis Journals, vol. 11(3), pages 287-290.

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