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Finite Sample Lag Adjusted Critical Values and Probability Values for the Fourier Wavelet Unit Root Test

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  • Peter S. Sephton

    (Queen’s University)

Abstract

Inferences from tests for non-stationarity depend critically on whether and how breaks and/or non-linearities are specified. Recent work has shown that wavelet transformations that separate a variable’s high and low frequency components can enhance the performance of unit root and stationarity tests. This note provides response surface estimates of finite sample, lag-adjusted critical values and approximate probability values for an Augmented Dickey–Fuller type wavelet test that includes a Fourier term allowing for smooth breaks in the series. Applications highlight the practical benefits.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:compec:v:64:y:2024:i:2:d:10.1007_s10614-023-10458-4
    DOI: 10.1007/s10614-023-10458-4
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    More about this item

    Keywords

    Integrated processes; Akaike information criterion; Bayesian information criterion; Wavelet; Unit root test;
    All these keywords.

    JEL classification:

    • 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
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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