Working Paper
Evaluating long-horizon forecasts
Abstract: This paper examines the asymptotic and finite-sample properties of tests of equal forecast accuracy and encompassing applied to predictions from nested long-horizon regression models. We first derive the asymptotic distributions of a set of tests of equal forecast accuracy and encompassing, showing that the tests have non-standard distributions that depend on the parameters of the data-generating process. Using a simple parametric bootstrap for inference, we then conduct Monte Carlo simulations of a range of data-generating processes to examine the finite-sample size and power of the tests. In these simulations, the bootstrap yields tests with good finite-sample size and power properties, with the encompassing test proposed by Clark and McCracken (2001a) having superior power. The paper concludes with a reexamination of the predictive content of capacity utilization for core inflation.
Keywords: Forecasting;
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File(s): File format is application/pdf https://www.kansascityfed.org/documents/5407/pdf-RWP01-14.pdf
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Bibliographic Information
Provider: Federal Reserve Bank of Kansas City
Part of Series: Research Working Paper
Publication Date: 2001
Number: RWP 01-14