Evaluating long-horizon forecasts

Todd Clark and Michael McCracken

No RWP 01-14, Research Working Paper from Federal Reserve Bank of Kansas City

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 (search for similar items in EconPapers)
Date: 2001
New Economics Papers: this item is included in nep-ets
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Citations: View citations in EconPapers (26)

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