Tests of Equal Forecast Accuracy and Encompassing for Nested Models

Federal Reserve Bank of Kansas City, Research Working Paper No. 99-11

54 Pages Posted: 9 Nov 1999

See all articles by Todd E. Clark

Todd E. Clark

Federal Reserve Bank of Cleveland

Michael W. McCracken

Federal Reserve Banks - Federal Reserve Bank of St. Louis

Date Written: October 1999

Abstract

We examine the asymptotic and finite-sample properties of tests for equal forecast accuracy and encompassing applied to 1-step ahead forecasts from nested parametric models. We first derive the asymptotic distributions of two standard tests and one new test of encompassing. Tables of asymptotically valid critical values are provided. Monte Carlo methods are then used to evaluate the size and power of the tests of equal forecast accuracy and encompassing. The simulations indicate that post-sample tests can be reasonably well sized. Of the post-sample tests considered, the encompassing test proposed in this paper is the most powerful. We conclude with an empirical application regarding the predictive content of unemployment for inflation.

JEL Classification: C53, C12, C52

Suggested Citation

Clark, Todd E. and McCracken, Michael W., Tests of Equal Forecast Accuracy and Encompassing for Nested Models (October 1999). Federal Reserve Bank of Kansas City, Research Working Paper No. 99-11. Available at SSRN: https://ssrn.com/abstract=191028 or http://dx.doi.org/10.2139/ssrn.191028

Todd E. Clark (Contact Author)

Federal Reserve Bank of Cleveland ( email )

P.O. Box 6387
Cleveland, OH 44101
United States
216-579-2015 (Phone)

Michael W. McCracken

Federal Reserve Banks - Federal Reserve Bank of St. Louis ( email )

411 Locust St
Saint Louis, MO 63011
United States

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