Time–Frequency Regression

Funashima Yoshito ()
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Funashima Yoshito: Faculty of Economics, Tohoku Gakuin University, 1-3-1 Tsuchitoi, Aoba-ku, Sendai, Miyagi 980-8511, Japan

Journal of Econometric Methods, 2021, vol. 10, issue 1, 21-32

Abstract: Wavelet analysis is widely used to trace macroeconomic and financial phenomena in time–frequency domains. However, existing wavelet measures diverge from conventional regression estimators. Furthermore, a direct comparison between wavelet and traditional regression analyses is difficult. In this study, we modify the partial wavelet gain to provide an estimator that corresponds to the ordinary least squares estimator at each point of the time–frequency space. We argue that from the viewpoint of practical applications, the modified partial wavelet gain is suitable for contemporary regressions across time and frequencies, whereas the original partial wavelet gain is suitable for evaluating an aggregate relationship of contemporaneous and lead-lag relationships.

Keywords: ordinary least squares; time–frequency regression; wavelet gain (search for similar items in EconPapers)
JEL-codes: C49 (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1515/jem-2019-0025

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