Comparing Predictive Accuracy
Francis Diebold () and
Roberto Mariano ()
Journal of Business & Economic Statistics, 1995, vol. 13, issue 3, 253-63
The authors propose and evaluate explicit tests of the null hypothesis of no difference in the accuracy of two competing forecasts. In contrast to previously developed tests, a wide variety of accuracy measures can be used (in particular, the loss function need not be quadratic and need not even be symmetric) and forecast errors can be non-Gaussian, nonzero mean, serially correlated, and contemporaneously correlated. Asymptotic and exact finite sample tests are proposed, evaluated, and illustrated.
References: Add references at CitEc
Citations: View citations in EconPapers (3748) Track citations by RSS feed
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Journal Article: Comparing Predictive Accuracy (2002)
Working Paper: Comparing Predictive Accuracy (1994)
Software Item: DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:bes:jnlbes:v:13:y:1995:i:3:p:253-63
Ordering information: This journal article can be ordered from
Access Statistics for this article
Journal of Business & Economic Statistics is currently edited by Jonathan H. Wright and Keisuke Hirano
More articles in Journal of Business & Economic Statistics from American Statistical Association
Bibliographic data for series maintained by Christopher F. Baum ().