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Comparing Forecast Accuracy in Small Samples
Roland Döhrn
出版
Ruhr-Universität Bochum (RUB), Department of Economics
, 2019
ISBN
386788966X
9783867889667
URL
http://books.google.com.hk/books?id=WZGkzQEACAAJ&hl=&source=gbs_api
註釋
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.
