The Boosted HP Filter Is More General Than You Might Think

41 Pages Posted: 28 Sep 2022

See all articles by Ziwei Mei

Ziwei Mei

The Chinese University of Hong Kong (CUHK) - Department of Economics

Peter C. B. Phillips

University of Auckland Business School; Yale University - Cowles Foundation; Singapore Management University - School of Economics

Zhentao Shi

Department of Economics, the Chinese University of Hong Kong

Multiple version iconThere are 2 versions of this paper

Date Written: September 20, 2022

Abstract

The global financial crisis and Covid recession have renewed discussion concerning trend-cycle discovery in macroeconomic data, and boosting has recently upgraded the popular HP filter to a modern machine learning device suited to data-rich and rapid computational environments. This paper sheds light on its versatility in trend-cycle determination, explaining in a simple manner both HP filter smoothing and the consistency delivered by boosting for general trend detection. Applied to a universe of time series in FRED databases, boosting outperforms other methods in timely capturing downturns at crises and recoveries that follow. With its wide applicability the boosted HP filter is a useful automated machine learning addition to the macroeconometric toolkit.

Keywords: Boosting, Business cycle, Machine learning, Macroeconomics, Recession

JEL Classification: C22, C55, C43

Suggested Citation

Mei, Ziwei and Phillips, Peter C. B. and Shi, Zhentao, The Boosted HP Filter Is More General Than You Might Think (September 20, 2022). Available at SSRN: https://ssrn.com/abstract=4224809 or http://dx.doi.org/10.2139/ssrn.4224809

Ziwei Mei (Contact Author)

The Chinese University of Hong Kong (CUHK) - Department of Economics ( email )

Shatin, N.T.
Hong Kong

Peter C. B. Phillips

University of Auckland Business School ( email )

12 Grafton Rd
Private Bag 92019
Auckland, 1010
New Zealand
+64 9 373 7599 x7596 (Phone)

Yale University - Cowles Foundation ( email )

Box 208281
New Haven, CT 06520-8281
United States
203-432-3695 (Phone)
203-432-5429 (Fax)

Singapore Management University - School of Economics

90 Stamford Road
178903
Singapore

Zhentao Shi

Department of Economics, the Chinese University of Hong Kong ( email )

Shatin, N.T.
Hong Kong

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