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Adaptive permutation tests for serial independence |
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| Authors: | Lanh Tran Ba Chu Chunfeng Huang Kim P. Huynh |
| Affiliation: | 1. Department of Statistics, Indiana University, , Bloomington, IN, 47408 USA;2. Department of Economics, Carleton University, , Ottawa, ON, K1S 5B6 Canada;3. Bank of Canada, , Ottawa, ON, K1A 0G9 Canada |
| Abstract: | Permutation tests for serial independence using three different statistics based on empirical distributions are proposed. These tests are shown to be consistent under the alternative of m‐dependence and are all simple to perform in practice. A small simulation study demonstrates that the proposed tests have good power in small samples. The tests are then applied to Canadian gross domestic product (GDP data), corroborating the random‐walk hypothesis of GDP growth. |
| Keywords: | permutation test m‐dependence serial independence the Kolmogorov– Smirnov statistic the Cramer– von Mises statistic the Blum– Kiefer– Rosenblatt statistic |