Robust critical values for unit root tests for series with conditional heteroscedasticity errors: An application of the simple NoVaS transformation
In this paper, we introduce a set of critical values for unit root tests that are robust in the presence of conditional heteroscedasticity errors using the normalizing and variance-stabilizing transformation (NoVaS) and examine their properties using Monte Carlo methods. In terms of the size of the...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2017-01-01
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| Series: | Cogent Economics & Finance |
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| Online Access: | http://dx.doi.org/10.1080/23322039.2016.1274282 |
| Summary: | In this paper, we introduce a set of critical values for unit root tests that are robust in the presence of conditional heteroscedasticity errors using the normalizing and variance-stabilizing transformation (NoVaS) and examine their properties using Monte Carlo methods. In terms of the size of the test, our analysis reveals that unit root tests with NoVaS-modified critical values have actual sizes close to the nominal size. For the power of the test, we find that unit root tests with NoVaS-modified critical values either have the same power as, or slightly better than, tests using conventional Dickey–Fuller critical values across the sample range considered. |
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| ISSN: | 2332-2039 |