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

Peter Sephton ()

Computational Economics, 2024, vol. 64, issue 2, No 3, 693-705

Abstract: 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.

Keywords: Integrated processes; Akaike information criterion; Bayesian information criterion; Wavelet; Unit root test (search for similar items in EconPapers)
JEL-codes: C12 C15 C22 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10614-023-10458-4

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