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Regression-Based Tests of Predictive Ability
Open accessAbstract
We develop regression-based tests of hypotheses about out of sample prediction errors.Representative tests include ones for zero mean and zero correlation between a prediction error and a vector of predictors.The relevant environments are ones in which predictions depend on estimated parameters.We show that standard regression statistics generally fail to account for error introduced by estimation of these parameters.We propose computationally convenient test statistics that properly account for such error.Simulations indicate that the procedures can work well in samples of size typically available, although there sometimes are substantial size distortions.
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Citations
Cited by
(2011) · Econometrica · doi:10.3982/ecta5771 · Cited by 2,096
Tests of Conditional Predictive Ability
Giacomini, R., & White, H. (2006) · Econometrica · doi:10.1111/j.1468-0262.2006.00718.x · Cited by 1,646
Evaluating Density Forecasts with Applications to Financial Risk Management
Diebold, F. X., Gunther, T. A., & Tay, A. S. (1998) · International Economic Review · doi:10.2307/2527342 · Cited by 1,452
Forecasting Volatility in Financial Markets: A Review
Poon, S., & Granger, C. W. J. (2003) · Journal of Economic Literature · doi:10.1257/002205103765762743 · Cited by 1,315
A Test for Superior Predictive Ability
Hansen, P. R. (2005) · Journal of Business & Economic Statistics · doi:10.1198/073500105000000063 · Cited by 1,230
Metadata
- Authors
- West, K. D., & McCracken, M. W.
- Venue
- International Economic Review
- Publisher
- JSTOR
- Published
- 1998-11
- Volume
- 39
- Issue
- 4
- Pages
- 817
- ISSN
- 0020-6598 (ISSN-L)
- OpenAlex
- W1575811129
- Cited by
- 285
- References
- 0
- FWCI
- 14.94
- Type
- journal article
- Language
- en
- Open access
- green
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- West, K. D., & McCracken, M. W. (1998). Regression-Based Tests of Predictive Ability. International Economic Review. https://doi.org/10.2307/2527340
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
