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Studies in Nonlinear Dynamics & Econometrics

Ed. by Mizrach, Bruce

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Volume 24, Issue 1


Volume 24 (2020)

Trimmed Whittle estimation of the SVAR vs. filtering low-frequency fluctuations: applications to technology shocks

Yuliya LovchaORCID iD: https://orcid.org/0000-0002-0481-7785 / Alejandro Perez-Laborda
Published Online: 2019-02-09 | DOI: https://doi.org/10.1515/snde-2018-0030


This paper shows that the trimmed Whittle estimation of the SVAR is superior to filtering (or differencing) undesired, low-frequency fluctuations that may arise in macroeconomic data. Pre-filtering destroys the low-frequency range of the spectrum, thus biasing the estimated parameters and the responses of the variables to shocks. The proposed method, by contrast, accounts for the undesired fluctuations while overcoming these drawbacks. Furthermore, the method remains reliable even when the observed low-frequency variability has been incorrectly considered as external to the SVAR. An empirical application that examines the effect of technology shocks on hours worked is provided to illustrate the results. We find the response of hours positive and similar using both long and short-run identification restrictions, thus providing a solution to a wide debate in the business cycle literature.

This article offers supplementary material which is provided at the end of the article.

Keywords: band-pass; business cycle; frequency domain; Hodrick-Prescott, hours-worked; impulse response

JEL Classification: C32; C51; E32; E37


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About the article

Published Online: 2019-02-09

Funding Source: Ministerio de Economia y Competividad

Award identifier / Grant number: ECO2016-75410-P

Perez-Laborda acknowledges financial support from the Ministerio de Economia y Competividad (Funder Id 10.13039/501100003329, ECO2016-75410-P, Spain).

Citation Information: Studies in Nonlinear Dynamics & Econometrics, Volume 24, Issue 1, 20180030, ISSN (Online) 1558-3708, DOI: https://doi.org/10.1515/snde-2018-0030.

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Yuliya Lovcha and Alejandro Perez-Laborda
Macroeconomic Dynamics, 2020, Page 1

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