Exact Tests of Equal Forecast Accuracy with an Application to the Term Structure of Interest Rates
Abstract
The author proposes a class of exact tests of the null hypothesis of exchangeable forecast errors and, hence, of the hypothesis of no difference in the unconditional accuracy of two competing forecasts. The class includes analogues of the well-known Diebold and Mariano (1995) parametric and non-parametric test statistics. The forecast errors can be non-normal and contemporaneously correlated, and general forms of the loss function are admitted. The nonparametric distribution-free property of these new tests makes them robust to the presence of conditional heteroscedasticity, heavy tails, and outliers in the loss-differential series. These tests are used with a randomization or “Monte Carlo” resampling technique, which yields an exact and computationally inexpensive inference procedure. Simulations confirm the reliability of the new test procedure, and its power is found to be comparable with that of the size-corrected parametric Diebold-Mariano test. The test procedure is illustrated with an application to the term structure of interest rates. The application shows that exchangeable forecast errors can be found empirically even when comparing forecasts from estimated models.Download Info
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Paper provided by Bank of Canada in its series Working Papers with number 04-2.Length: 36 pages
Date of creation: 2004
Date of revision:
Handle: RePEc:bca:bocawp:04-2
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Related research
Keywords: Econometric and statistical methods;Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- 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-2004-01-18 (All new papers)
- NEP-CMP-2004-01-18 (Computational Economics)
- NEP-ECM-2004-01-25 (Econometrics)
- NEP-ETS-2004-01-18 (Econometric Time Series)
- NEP-RMG-2004-01-18 (Risk Management)
References
References listed on IDEASPlease report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Jean-Marie Dufour, 2003.
"Identification, weak instruments, and statistical inference in econometrics,"
Canadian Journal of Economics,
Canadian Economics Association, vol. 36(4), pages 767-808, November.
- Jean-Marie Dufour, 2003. "Identification, Weak Instruments and Statistical Inference in Econometrics," CIRANO Working Papers 2003s-49, CIRANO.
- DUFOUR, Jean-Marie, 2003. "Identification, Weak Instruments and Statistical Inference in Econometrics," Cahiers de recherche 2003-12, Universite de Montreal, Departement de sciences economiques.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Ryan Ratcliff, 2010. "Predicting nominal exchange rate movements using skewness information from options prices," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(1), pages 75-92.
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