Comparing forecast accuracy in small samples

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The Diebold-Mariano-Test has become a common tool to compare the accuracy of macroeconomic forecasts. Since these are typically model-free forecasts, distribution free tests might be a good alternative to the Diebold-Mariano-Test. This paper suggests a permutation test. Stochastic simulations show that permutation tests outperform the Diebold-Mariano-Test. Furthermore, a test statistic based on absolute errors seems to be more sensitive to differences in forecast accuracy than a statistic based on squared errors