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Finite-sample properties of tests for forecast equivalence

Author

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  • Todd E. Clark

Abstract

This paper uses Monte Carlo experiments to examine the small-sample properties of some commonly used tests of equal forecast accuracy. The study pays particular attention to test power, evaluated using both asymptotic and empirical critical values. In addition to evaluating different tests, this paper evaluates the performance of different methods of determining the bandwidth used in computing autocorrelation-consistent test statistics. The simulation results show that tests of equal forecast accuracy have somewhat inflated size and modest or even low power. Moreover, the performances of the different tests and the bandwidth selection criteria are broadly similar.

Suggested Citation

  • Todd E. Clark, 1996. "Finite-sample properties of tests for forecast equivalence," Research Working Paper RWP 96-03, Federal Reserve Bank of Kansas City.
    • Handle: RePEc:fip:fedkrw:96-03
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    Citations

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    Cited by:

    1. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
    2. Helge Berger & Pär Österholm, 2011. "Does Money Growth Granger Cause Inflation in the Euro Area? Evidence from Out‐of‐Sample Forecasts Using Bayesian VARs," The Economic Record, The Economic Society of Australia, vol. 87(276), pages 45-60, March.
    3. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    4. West, Kenneth D & McCracken, Michael W, 1998. "Regression-Based Tests of Predictive Ability," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 817-840, November.
    5. Martin Lettau & Sydney Ludvigson, 2001. "Consumption, Aggregate Wealth, and Expected Stock Returns," Journal of Finance, American Finance Association, vol. 56(3), pages 815-849, June.
    6. Hendry, David & Hubrich, Kirstin, 2006. "Forecasting Economic Aggregates by Disaggregates," CEPR Discussion Papers 5485, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    Forecasting;

    Statistics

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