Robust critical values for unit root tests for series with conditional heteroscedasticity errors: An application of the simple NoVaS transformation

• Main Author: Panagiotis Mantalos
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2017-01-01
• Series: Cogent Economics & Finance
• Subjects: critical values; normalizing and variance-stabilizing transformation; unit root tests
• Online Access: http://dx.doi.org/10.1080/23322039.2016.1274282

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.