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Forecast evaluation of small nested model sets

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  • Hubrich, Kirstin
  • West, Kenneth D.

Abstract

We propose two new procedures for comparing the mean squared prediction error (MSPE) of a benchmark model to the MSPEs of a small set of alternative models that nest the benchmark. Our procedures compare the bench-mark to all the alternative models simultaneously rather than sequentially, and do not require re-estimation of models as part of a bootstrap procedure. Both procedures adjust MSPE differences in accordance with Clark and West (2007); one procedure then examines the maximum t-statistic, the other computes a chi-squared statistic. Our simulations examine the proposed procedures and two existing procedures that do not adjust the MSPE differences: a chi-squared statistic, and White’s (2000) reality check. In these simulations, the two statistics that adjust MSPE differences have most accurate size, and the procedure that looks at the maximum t-statistic has best power. We illustrate, our procedures by comparing forecasts of different models for U.S. inflation. JEL Classification: C32, C53, E37

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Bibliographic Info

Paper provided by European Central Bank in its series Working Paper Series with number 1030.

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Date of creation: Mar 2009
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Handle: RePEc:ecb:ecbwps:20091030

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Keywords: Inflation forecasting; multiple model comparisons; Out-of-Sample; prediction; testing;

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References

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  1. Inoue, Atsushi & Kilian, Lutz, 2003. "On the selection of forecasting models," Working Paper Series 0214, European Central Bank.
  2. Clark, Todd E. & West, Kenneth D., 2006. "Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 155-186.
  3. Rapach, David E. & Wohar, Mark E., 2006. "In-sample vs. out-of-sample tests of stock return predictability in the context of data mining," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 231-247, March.
  4. Todd E. Clark & Michael W. McCracken, 2010. "Reality checks and nested forecast model comparisons," Working Papers 2010-032, Federal Reserve Bank of St. Louis.
  5. Kenneth D. West & Dongchul Cho, 1994. "The Predictive Ability of Several Models of Exchange Rate Volatility," NBER Technical Working Papers 0152, National Bureau of Economic Research, Inc.
  6. Lucio Sarno & Daniel L. Thornton & Giorgio Valente, 2004. "Federal funds rate prediction," Working Papers 2002-005, Federal Reserve Bank of St. Louis.
  7. Kirstin Hubrich & David F. Hendry, 2005. "Forecasting Aggregates by Disaggregates," Computing in Economics and Finance 2005 270, Society for Computational Economics.
  8. Hubrich, Kirstin, 2003. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," Working Paper Series 0247, European Central Bank.
  9. James H. Stock & Mark W. Watson, 2006. "Why Has U.S. Inflation Become Harder to Forecast?," NBER Working Papers 12324, National Bureau of Economic Research, Inc.
  10. Giacomini, Raffaella & White, Halbert, 2003. "Tests of Conditional Predictive Ability," University of California at San Diego, Economics Working Paper Series qt5jk0j5jh, Department of Economics, UC San Diego.
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  12. Hendry, David F. & Hubrich, Kirstin, 2011. "Combining Disaggregate Forecasts or Combining Disaggregate Information to Forecast an Aggregate," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(2), pages 216-227.
  13. Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 583-601, June.
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  24. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
  25. West, Kenneth D, 2001. "Tests for Forecast Encompassing When Forecasts Depend on Estimated Regression Parameters," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(1), pages 29-33, January.
  26. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
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Citations

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Cited by:
  1. Aron, Janine & Muellbauer, John, 2012. "Improving forecasting in an emerging economy, South Africa: Changing trends, long run restrictions and disaggregation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 456-476.
  2. Molodtsova, Tanya & Papell, David H., 2009. "Out-of-sample exchange rate predictability with Taylor rule fundamentals," Journal of International Economics, Elsevier, vol. 77(2), pages 167-180, April.
  3. Kollmann, Robert & Zeugner, Stefan, 2011. "Leverage as a Predictor for Real Activity and Volatility," CEPR Discussion Papers 8327, C.E.P.R. Discussion Papers.
  4. Francesco Ravazzolo & Philip Rothman, 2011. "Oil and US GDP: A Real-Time out-of Sample Examination," Working Papers 0004, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  5. Francesco D’Amuri & Juri Marcucci, 2010. "“Google it!”Forecasting the US Unemployment Rate with a Google Job Search index," Working Papers 2010.31, Fondazione Eni Enrico Mattei.
  6. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.
  7. Hendry, David F. & Hubrich, Kirstin, 2011. "Combining Disaggregate Forecasts or Combining Disaggregate Information to Forecast an Aggregate," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(2), pages 216-227.
  8. Fabio Busetti & Juri Marcucci & Giovanni Veronese, 2009. "Comparing forecast accuracy: A Monte Carlo investigation," Temi di discussione (Economic working papers) 723, Bank of Italy, Economic Research and International Relations Area.
  9. Todd E. Clark & Michael W. McCracken, 2010. "Reality checks and nested forecast model comparisons," Working Papers 2010-032, Federal Reserve Bank of St. Louis.
  10. Mariano, Roberto S. & Preve, Daniel, 2012. "Statistical tests for multiple forecast comparison," Journal of Econometrics, Elsevier, vol. 169(1), pages 123-130.
  11. Daniel Andrés Jaimes Cárdenas & Jair Ojeda Joya, . "Reglas de Taylor y previsibilidad fuera de muestra de la tasa de cambio en Latinoamérica," Borradores de Economia 619, Banco de la Republica de Colombia.

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