Conditional Predictive Density Evaluation in the Presence of Instabilities
AbstractWe propose new methods for evaluating predictive densities. The methods include Kolmogorov-Smirnov and Cramer-von Mises-type tests for the correct specification of predictive densities robust to dynamic mis-specification. The novelty is that the tests can detect mis-specification in the predictive densities even if it appears only over a fraction of the sample, due to the presence of instabilities. Our results indicate that our tests are well sized and have good power in detecting mis-specification in predictive densities, even when it is time-varying. An application to density forecasts of the Survey of Professional Forecasters demonstrates the usefulness of the proposed methodologies.
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Bibliographic InfoPaper provided by Barcelona Graduate School of Economics in its series Working Papers with number 688.
Date of creation: Feb 2013
Date of revision:
predictive density; dynamic mis-specification; instability; structural change; forecast evaluation;
Other versions of this item:
- Rossi, Barbara & Sekhposyan, Tatevik, 2013. "Conditional predictive density evaluation in the presence of instabilities," Journal of Econometrics, Elsevier, vol. 177(2), pages 199-212.
- Barbara Rossi & Tatevik Sekhposyan, 2013. "Conditional predictive density evaluation in the presence of instabilities," Economics Working Papers 1368, Department of Economics and Business, Universitat Pompeu Fabra.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-05-22 (All new papers)
- NEP-ECM-2013-05-22 (Econometrics)
- NEP-FOR-2013-05-22 (Forecasting)
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