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SPECTRAL FINANCIAL ECONOMETRICS

Published online by Cambridge University Press:  06 April 2022

Federico M. Bandi*
Affiliation:
Carey Business School, Johns Hopkins University
Andrea Tamoni
Affiliation:
Rutgers Business School, Rutgers University
*
Address correspondence to Federico M. Bandi, Carey Business School, Johns Hopkins University, Baltimore, MD, USA; e-mail: fbandi1@jhu.edu.

Abstract

We survey the literature on spectral regression estimation. We present a cohesive framework designed to model dependence on frequency in the response of economic time series to changes in the explanatory variables. Our emphasis is on the statistical structure and on the economic interpretation of time-domain specifications needed to obtain horizon effects over frequencies, over scales, or upon aggregation. To this end, we articulate our discussion around the role played by lead-lag effects in the explanatory variables as drivers of differential information across horizons. We provide perspectives for future work throughout.

Type
ARTICLES
Copyright
© The Author(s), 2022. Published by Cambridge University Press

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Footnotes

We dedicate this article to Peter C.B. Phillips on the occasion of the conference “A Celebration of Peter Phillips’ 40 Years at Yale,” New Haven, October 19–20, 2018. We thank Peter and conference participants for their useful comments. We are especially grateful to the Editor, Guido Kuersteiner, and two anonymous reviewers for their careful reading and many helpful suggestions.

References

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