Forecast Evaluation of Small Nested Model Sets

46 Pages Posted: 19 Mar 2009

See all articles by Kirstin Hubrich

Kirstin Hubrich

Board of Governors of the Federal Reserve System

Kenneth D. West

University of Wisconsin - Madison - Department of Economics; National Bureau of Economic Research (NBER)

Multiple version iconThere are 2 versions of this paper

Date Written: March 18, 2009

Abstract

We propose two new procedures for comparing the mean squared prediction error (MSPE) of a benchmark model to the MSPEs of a small set of alternative models that nest the benchmark. Our procedures compare the benchmark to all the alternative models simultaneously rather than sequentially, and do not require reestimation of models as part of a bootstrap procedure. Both procedures adjust MSPE differences in accordance with Clark and West (2007); one procedure then examines the maximum t-statistic, the other computes a chi-squared statistic. Our simulations examine the proposed procedures and two existing procedures that do not adjust the MSPE differences: a chi-squared statistic, and White's (2000) reality check. In these simulations, the two statistics that adjust MSPE differences have most accurate size, and the procedure that looks at the maximum t-statistic has best power. We illustrate, our procedures by comparing forecasts of different models for U.S. inflation.

Keywords: Out-of-sample, prediction, testing, multiple model comparisons, inflation forecasting

JEL Classification: C32, C53, E37

Suggested Citation

Hubrich, Kirstin and West, Kenneth D., Forecast Evaluation of Small Nested Model Sets (March 18, 2009). ECB Working Paper No. 1030. Available at SSRN: https://ssrn.com/abstract=1349094

Kirstin Hubrich (Contact Author)

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

Kenneth D. West

University of Wisconsin - Madison - Department of Economics ( email )

1180 Observatory Drive
Madison, WI 53706
United States
608-262-0033 (Phone)
608-262-2033 (Fax)

National Bureau of Economic Research (NBER) ( email )

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Cambridge, MA 02138
United States

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