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Time scale evaluation of economic forecasts

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  • Michis, Antonis A.

Abstract

A maximal overlap discrete wavelet transform is used to obtain time scale decompositions of economic forecasts and their errors. The generated time scale components can be used in loss measures and tests for comparing forecast accuracy to evaluate whether the forecasts accurately capture the cyclical features of the data.

Suggested Citation

  • Michis, Antonis A., 2014. "Time scale evaluation of economic forecasts," Economics Letters, Elsevier, vol. 123(3), pages 279-281.
    • Handle: RePEc:eee:ecolet:v:123:y:2014:i:3:p:279-281
    DOI: 10.1016/j.econlet.2014.03.002
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    References listed on IDEAS

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    1. Michis Antonis & Sapatinas Theofanis, 2007. "Wavelet Instruments for Efficiency Gains in Generalized Method of Moment Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 11(4), pages 1-25, December.
    2. Yogo, Motohiro, 2008. "Measuring business cycles: A wavelet analysis of economic time series," Economics Letters, Elsevier, vol. 100(2), pages 208-212, August.
    3. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
    4. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    5. Fan, Yanqin & Gençay, Ramazan, 2010. "Unit Root Tests With Wavelets," Econometric Theory, Cambridge University Press, vol. 26(5), pages 1305-1331, October.
    6. Marco Gallegati & Mauro Gallegati & James Bernard Ramsey & Willi Semmler, 2011. "The US Wage Phillips Curve across Frequencies and over Time," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(4), pages 489-508, August.
    7. Jensen, Mark J., 2000. "An alternative maximum likelihood estimator of long-memory processes using compactly supported wavelets," Journal of Economic Dynamics and Control, Elsevier, vol. 24(3), pages 361-387, March.
    8. Yongmiao Hong & Chihwa Kao, 2004. "Wavelet-Based Testing for Serial Correlation of Unknown Form in Panel Models," Econometrica, Econometric Society, vol. 72(5), pages 1519-1563, September.
    9. Faÿ, Gilles & Moulines, Eric & Roueff, François & Taqqu, Murad S., 2009. "Estimators of long-memory: Fourier versus wavelets," Journal of Econometrics, Elsevier, vol. 151(2), pages 159-177, August.
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    Cited by:

    1. Yang, Dazhi & Sharma, Vishal & Ye, Zhen & Lim, Lihong Idris & Zhao, Lu & Aryaputera, Aloysius W., 2015. "Forecasting of global horizontal irradiance by exponential smoothing, using decompositions," Energy, Elsevier, vol. 81(C), pages 111-119.
    2. Martyna Marczak & Thomas Beissinger, 2016. "Bidirectional relationship between investor sentiment and excess returns: new evidence from the wavelet perspective," Applied Economics Letters, Taylor & Francis Journals, vol. 23(18), pages 1305-1311, December.
    3. Antonis A. Michis, 2021. "Wavelet Multidimensional Scaling Analysis of European Economic Sentiment Indicators," Journal of Classification, Springer;The Classification Society, vol. 38(3), pages 443-480, October.
    4. Stelios Bekiros & Jose Arreola Hernandez & Gazi Salah Uddin & Ahmed Taneem Muzaffar, 2020. "On the predictability of crude oil market: A hybrid multiscale wavelet approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 599-614, July.
    5. Nikolaos Mitianoudis & Theologos Dergiades, 2016. "Stock Prices Predictability at Long-horizons: Two Tales from the Time-Frequency Domain," Discussion Paper Series 2016_04, Department of Economics, University of Macedonia, revised Dec 2016.
    6. Ardila, Diego & Sornette, Didier, 2016. "Dating the financial cycle with uncertainty estimates: a wavelet proposition," Finance Research Letters, Elsevier, vol. 19(C), pages 298-304.
    7. Caraiani, Petre, 2017. "Evaluating exchange rate forecasts along time and frequency," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 60-81.
    8. Markidou Anna & Michis Antonis, 2016. "Channel Concentration and Retail Prices: Evidence from the Traditional Cheese Market of Cyprus," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 14(1), pages 109-119, May.

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    More about this item

    Keywords

    Forecast accuracy; Loss measures; Time scales; Wavelets;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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