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On the Performance of Wavelet Based Unit Root Tests

Author

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  • Burak Alparslan Eroğlu

    (Department of Economics, Istanbul Bilgi University, Istanbul 34060, Turkey)

  • Barış Soybilgen

    (Institute of Graduate Programs, Istanbul Bilgi University, Istanbul 34060, Turkey)

Abstract

In this paper, we apply the wavelet methods in the popular Augmented Dickey-Fuller and M types of unit root tests. Moreover, we provide an extensive comparison of the wavelet based unit root tests which also includes the recent contributions in the literature. Moreover, we derive the asymptotic properties of the wavelet based unit root tests under generalized least squares detrending mechanism. We demonstrate that the wavelet based M tests exhibit better size performance even in problematic cases such as the presence of negative moving average innovations. However, the power performances of the wavelet based unit root tests are quite similar to each other.

Suggested Citation

  • Burak Alparslan Eroğlu & Barış Soybilgen, 2018. "On the Performance of Wavelet Based Unit Root Tests," JRFM, MDPI, vol. 11(3), pages 1-22, August.
    • Handle: RePEc:gam:jjrfmx:v:11:y:2018:i:3:p:47-:d:163515
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    References listed on IDEAS

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    1. Nielsen, Morten Ørregaard, 2010. "Nonparametric cointegration analysis of fractional systems with unknown integration orders," Journal of Econometrics, Elsevier, vol. 155(2), pages 170-187, April.
    2. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    3. Fan, Yanqin & Gençay, Ramazan, 2010. "Unit Root Tests With Wavelets," Econometric Theory, Cambridge University Press, vol. 26(5), pages 1305-1331, October.
    4. Nielsen, Morten Ørregaard, 2009. "A Powerful Test Of The Autoregressive Unit Root Hypothesis Based On A Tuning Parameter Free Statistic," Econometric Theory, Cambridge University Press, vol. 25(6), pages 1515-1544, December.
    5. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    6. Perron, Pierre & Qu, Zhongjun, 2007. "A simple modification to improve the finite sample properties of Ng and Perron's unit root tests," Economics Letters, Elsevier, vol. 94(1), pages 12-19, January.
    7. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
    8. Yoosoon Chang & Joon Park, 2002. "On The Asymptotics Of Adf Tests For Unit Roots," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 431-447.
    9. Gençay, Ramazan & Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon J., 2001. "An Introduction to Wavelets and Other Filtering Methods in Finance and Economics," Elsevier Monographs, Elsevier, edition 1, number 9780122796708.
    10. Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November.
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    Cited by:

    1. Aydin, Mucahit, 2019. "A New Nonlinear Wavelet-Based Unit Root Test with Structural Breaks," MPRA Paper 98693, University Library of Munich, Germany.
    2. Thanasis Stengos, 2019. "Nonparametric Econometric Methods and Applications," JRFM, MDPI, vol. 12(4), pages 1-3, November.
    3. Peter S. Sephton, 2024. "Finite Sample Lag Adjusted Critical Values and Probability Values for the Fourier Wavelet Unit Root Test," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 693-705, August.

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