Evaluating Long–Horizon Forecasts
نویسندگان
چکیده
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 model–based 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 (2001) having superior power. The paper concludes with a reexamination of the predictive content of capacity utilization for core inflation. JEL Nos.: C53, C12, C52
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