Robust critical values for unit root tests for series with conditional heteroscedasticity errors: An application of the simple NoVaS transformation
AbstractIn 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) in Politis (2007) 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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Bibliographic InfoPaper provided by Örebro University, School of Business in its series Working Papers with number 2012:2.
Length: 24 pages
Date of creation: 02 Feb 2012
Date of revision:
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Postal: Örebro University School of Business, SE - 701 82 ÖREBRO, Sweden
Phone: 019-30 30 00
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Web page: http://www.oru.se/Institutioner/Handelshogskolan-vid-Orebro-universitet/
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Critical values; normalizing and variance-stabilizing transformation; unit root tests;
Find related papers by JEL classification:
- C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-03-08 (All new papers)
- NEP-ECM-2012-03-08 (Econometrics)
- NEP-ETS-2012-03-08 (Econometric Time Series)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- MacKinnon, James G, 1992. "Model Specification Tests and Artificial Regressions," Journal of Economic Literature, American Economic Association, vol. 30(1), pages 102-46, March.
- Kim, Kiwhan & Schmidt, Peter, 1993. "Unit root tests with conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 59(3), pages 287-300, October.
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