Prague Economic Papers 2015, 24(3):274-286 | DOI: 10.18267/j.pep.519
The Improvement of Unemployment Rate Predictions Accuracy
- Romanian Academy, Bucharest, Romania (mihaela_mb1@yahoo.com).
This research is related to the assessment of alternative unemployment rate predictions for the Romanian economy, the forecasts being provided by three anonymous forecasters: F1, F2 and F3. F3 provided the most accurate forecasts for the horizon 2001-2014, while F2 predictions are the less accurate according to U1 Theil's statistic and according to a new method that has not been used before in literature in this context. The multi-criteria ranking was applied to make a hierarchy of the forecasters regarding the accuracy and five important accuracy measures were taken into account at the same time: mean errors, mean squared error, root mean squared error, U1 and U2 statistics of Theil. The combined forecasts of forecasters' predictions are the best strategy to improve the forecasts accuracy. The filtered and smoothed original predictions based on Hodrick-Prescott filter, respectively Holt-Winters technique, are a good strategy of improving the accuracy only for F2 expectations. The assessment and improvement of forecasts accuracy have an important contribution in growing the quality of decision-making process.
Klíčová slova: forecasts, accuracy, multi-criteria ranking, combined forecasts, Hodrick-Prescott filter, Holt-Winters smoothing exponential technique
JEL classification: C51, C53, E21, E27
Zveřejněno: 1. leden 2015 Zobrazit citaci
Reference
- Abreu, I. (2011), "International Organizations' vs. Private Analysts' Forecasts: An Evaluation." Bank of Portugal Review, Vol. 4, No. 2, pp. 4-13.
- Allan, G. (2012), "Evaluating the Usefulness of Forecasts of Relative Growth." Strathclyde, Discussion Papers in Economics, Vol. 1, No. 12-14, pp. 6-12.
- Armstrong, J. S., Fildes, R. (1995), "On the Selection of Error Measures for Comparisons among Forecasting Methods." Journal of Forecasting, Vol. 14, No. 1, pp. 67-71.
Přejít k původnímu zdroji...
- Bates, J., Granger, C. W. J. (1969), "The Combination of Forecasts." Operations Research Quarterly, Vol. 20, No. 4, pp. 451-468.
Přejít k původnímu zdroji...
- Bilan, Y. (2012), "Specificity of Border Labour Migration." Transformations in Business & Economics, Vol. 11, No. 2, pp. 82-97.
- Bratu, M. (2012), Strategies to Improve the Accuracy of Macroeconomic Forecasts in USA. Munich: Lap Lambert Academic Publishing.
- Bratu Simionescu, M. (2013), "Filters or Holt Winters Technique to Improve the Forecasts for USA Inflation Rate?" Acta Universitatis Danubius. Economica, Vol. 9, No. 1, pp. 56-68.
- Chen Z, Yang Y. (2004), "Assessing Forecast Accuracy Measures." Annals of Statistics, Vol. 28, No. 1, pp. 75-87.
- Diebold, F. X., Mariano, R. (1995), "Comparing Predictive Accuracy." Journal of Business and Economic Statistics, Vol. 13, No. 1, pp. 253-265.
Přejít k původnímu zdroji...
- Dovern, J., Weisser J. (2011), "Accuracy, Unbiasedness and Efficiency of Professional Macroeconomic Forecasts: An Empirical Comparison for the G7." International Journal of Forecasting, Vol. 27, No. 2, pp. 452-465.
Přejít k původnímu zdroji...
- Franses, P. H., McAleer, M., Legerstee, R. (2012), "Evaluating Macroeconomic Forecasts: A Concise Review of Some Recent Developments." Working Paper/Department of Economics and Finance, University of Cantenbury, Vol. 2, No.1, pp. 13-26.
Přejít k původnímu zdroji...
- Gorr, W. L. (2009), "Forecast Accuracy Measures for Exception Reporting Using Receiver Operating Characteristic Curves." International Journal of Forecasting, Vol. 25, No. 1, pp. 48-61.
Přejít k původnímu zdroji...
- Gürkaynak, R. S., Kisacikoglu, B., Rossi, B. (2013), "Do DSGE Models Forecast More Accurately out-of-Sample than VAR Models?" CEPR Discussion Papers 9576, C.E.P.R. Discussion Papers.
Přejít k původnímu zdroji...
- Heilemann, U., Stekler, H. (2007), "Introduction to the Future of Macroeconomic Forecasting" International Journal of Forecasting, Vol. 23, No. 2, pp. 159-165.
Přejít k původnímu zdroji...
- Liu, D., Smith, J. K. (2014), "Inflation Forecasts and Core Inflation Measures: Where Is the Information on Future Inflation?" The Quarterly Review of Economics and Finance, Vol. 54, No. 1, pp. 133-137.
Přejít k původnímu zdroji...
- Kucur, H., Shinji T. (2006), "Testing the Accuracy of IMF Macroeconomic Forecasts, 1994-2003." IEO Background Paper Number BP/06/01. Available at http://www.ieo-imf.org/ieo/pages/CompletedEvaluation114.aspx
- Müller-Dröge, C., Sinclair, T., Steckler, H. O. (2014), "Evaluating Forecasts of a Vector of Variables: A German Forecasting Competition." Cama Working Paper, Vol. 1, No. 55, pp. 1-23.
Přejít k původnímu zdroji...
- Ruth, K. (2008), "Macroeconomic Forecasting in the EMU: Does Disaggregate Modeling Improve Forecast Accuracy?" Journal of Policy Modeling, Vol. 30, No. 3, pp. 417-429.
Přejít k původnímu zdroji...
- Simionescu, M. (2013), "Methods for Assessing the Uncertainty in Forecasts Based on Opinion Survey." International Journal of Academic Research, Vol. 5, No. 6, pp. 56-67.
Přejít k původnímu zdroji...
- Simionescu, M. (2014), "The Performance of Predictions Based on the Dobrescu Macromodel for the Romanian Economy." Journal for Economic Forecasting, Vol. 3, pp. 179-195.
- Smith, J., Wallis, K. F. (2009), "A Simple Explanation of the Forecast Combination Puzzle." Oxford Bulletin of Economics and Statistics, Vol. 71, No. 3, pp. 331-355.
Přejít k původnímu zdroji...
- Stekler H. O., Zhang H. (2013), "An Evaluation of Chinese Economic Forecasts." Journal of Chinese Economic and Business Studies, Vol. 11, No. 4, pp. 251-259.
Přejít k původnímu zdroji...
- Timmermann, A. (2007), "An Evaluation of the WEO Forecasts." IMF Staff Papers, Vol. 54, No. 1, pp. 2-34.
Přejít k původnímu zdroji...
- Todd E. C., McCracken, M. W. (2013), "Evaluating the Accuracy of Forecasts from Vector Autoregressions." Working Paper 2013-010A.
- Yang, Y. (2004), "Combining Forecasting Procedures: Some Theoretical Results." Econometric Theory, Vol. 20, No. 1, pp. 176-222.
Přejít k původnímu zdroji...
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