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The Assessment And Improvement Of The Accuracy For The Forecast Intervals

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  • Bratu, Mihaela

    ()
    (Academy of Economic Studies. Faculty of Cybernetics, Statistics and Economic Informatics.)

Abstract

The objective of this research is to present some accuracy measures associated to forecast intervals, taken into account the fact that in literature some specific accuracy indicators for this type of prediction have not been proposed yet. For the quarterly inflation rate provided by the National Bank of Romania, forecast intervals were built on the horizon 2010-2012. According to the number of intervals that include the real value and to an econometric procedure based on DUMMY variables, the intervals based on historical errors (RMSE- root mean squared errors) are better than those based on BCA bootstrap procedure. However, the new indicator proposed in this paper as a measure of global accuracy, M indicator, the forecast intervals based on BCA bootstraping are more accurate than the intervals based on historical RMSE. Bayesian intervals were constructed for quarterly USA inflation in 2012 using aprioristic information, but the smaller intervals did not imply an increase in the degree of accuracy.

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File URL: ftp://www.ipe.ro/RePEc/WorkingPapers/cs26_2.pdf
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Bibliographic Info

Paper provided by Institute for Economic Forecasting in its series Working Papers of Macroeconomic Modelling Seminar with number 132602.

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Length: 11 pages
Date of creation: Jul 2013
Date of revision:
Handle: RePEc:rjr:wpmems:132602

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Keywords: forecast intervals; accuracy; uncertainty; BCA bootstrap intervals; indicator M;

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  1. Matei Demetrescu, 2007. "Optimal forecast intervals under asymmetric loss," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 227-238.
  2. Jian Wang & Jason J. Wu, 2009. "The Taylor rule and forecast intervals for exchange rates," International Finance Discussion Papers 963, Board of Governors of the Federal Reserve System (U.S.).
  3. Henning Fischer & Marta García-Bárzana & Peter Tillmann & Peter Winker, 2014. "Evaluating FOMC forecast ranges: an interval data approach," Empirical Economics, Springer, vol. 47(1), pages 365-388, August.
  4. Chatfield, Chris, 1993. "Calculating Interval Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 121-35, April.
  5. Chatfield, Chris, 1993. "Calculating Interval Forecasts: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 143-44, April.
  6. Diebold, Francis X & West, Kenneth D, 1998. "Symposium on Forecasting and Empirical Methods in Macroeconomics and Finance: Editors' Introduction," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 811-15, November.
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