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Robust Evaluation of Fixed-Event Forecast Rationality

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  • Clements, Michael P
  • Taylor, Nick

Abstract

In this paper we introduce a new testing procedure for evaluating the rationality of fixed-event forecasts based on a pseudo-maximum likelihood estimator. The procedure is designed to be robust to departures in the normality assumption. A model is introduced to show that such departures are likely when forecasters experience a credibility loss when they make large changes to their forecasts. The test is illustrated using monthly fixed-event forecasts produced by four UK institutions. Use of the robust test leads to the conclusion that certain forecasts are rational while use of the Gaussian-based test implies that certain forecasts are irrational. The difference in the results is due to the nature of the underlying data. Copyright © 2001 by John Wiley & Sons, Ltd.

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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 20 (2001)
Issue (Month): 4 (July)
Pages: 285-95

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Handle: RePEc:jof:jforec:v:20:y:2001:i:4:p:285-95

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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Cited by:
  1. Hendry, David F & Michael P. Clements, 2002. "Economic Forecasting: Some Lessons from Recent Research," Royal Economic Society Annual Conference 2002 99, Royal Economic Society.
  2. Rosario Dell'Aquila & Elvezio Ronchetti, 2004. "Robust tests of predictive accuracy," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(2), pages 161-184.
  3. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.

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