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Forecast Encompassing Tests and Probability Forecasts

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  • Clements, Michael P

    (Department of Economics, University of Warwick)

  • Harvey, David I

    (School of Economics, University of Nottingham)

Abstract

We consider tests of forecast encompassing for probability forecasts, for both quadratic and logarithmic scoring rules. We propose test statistics for the null of forecast encompassing, present the limiting distributions of the test statistics, and investigate the impact of estimating the forecasting models’ parameters on these distributions. The small-sample performance of the various statistics is investigated, both in terms of small numbers of forecasts and model estimation sample sizes. Two empirical applications show the usefulness of the tests for the evaluation of recession probability forecasts from logit models with different leading indicators as explanatory variables, and for evaluating survey-based probability forecasts. Probability forecasts ; encompassing tests ; recession probabilities

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Paper provided by University of Warwick, Department of Economics in its series The Warwick Economics Research Paper Series (TWERPS) with number 774.

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Length: 37 pages
Date of creation: 2006
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Handle: RePEc:wrk:warwec:774

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Cited by:
  1. Rodrigues, Bruno Dore & Stevenson, Maxwell J., 2013. "Takeover prediction using forecast combinations," International Journal of Forecasting, Elsevier, Elsevier, vol. 29(4), pages 628-641.
  2. Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010. "Forecast Combinations," Working Papers, Banco de México 2010-04, Banco de México.
  3. Clements, Michael P., 2010. "Explanations of the inconsistencies in survey respondents' forecasts," European Economic Review, Elsevier, Elsevier, vol. 54(4), pages 536-549, May.
  4. Jonas Dovern & Christina Ziegler, 2008. "Predicting Growth Rates and Recessions. Assessing U.S. Leading Indicators under Real-Time Condition," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, Duncker & Humblot, Berlin, vol. 54(4), pages 293-318.
  5. David G. McMillan & Mark E. Wohar, 2010. "Stock return predictability and dividend-price ratio: a nonlinear approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 15(4), pages 351-365.
  6. Clements, Michael P., 2008. "Consensus and uncertainty: Using forecast probabilities of output declines," International Journal of Forecasting, Elsevier, Elsevier, vol. 24(1), pages 76-86.
  7. Oliver Hülsewig & Johannes Mayr & Stéphane Sorbe, 2007. "Assessing the Forecast Properties of the CESifo World Economic Climate Indicator: Evidence for the Euro Area," Ifo Working Paper Series Ifo Working Paper No. 46, Ifo Institute for Economic Research at the University of Munich.
  8. Tsyplakov, Alexander, 2014. "Theoretical guidelines for a partially informed forecast examiner," MPRA Paper 55017, University Library of Munich, Germany.
  9. Lahiri, Kajal & Wang, J. George, 2013. "Evaluating probability forecasts for GDP declines using alternative methodologies," International Journal of Forecasting, Elsevier, Elsevier, vol. 29(1), pages 175-190.

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