Reconciling Output Gaps: Unobserved Components Model and Hodrick-Prescott Filter

24 Pages Posted: 20 Jul 2016

See all articles by Joshua C. C. Chan

Joshua C. C. Chan

University of Technology Sydney (UTS) - UTS Business School; Purdue University

Angelia Grant

Australian National University (ANU) - Centre for Applied Macroeconomic Analysis (CAMA)

Date Written: June 2016

Abstract

This paper reconciles two widely used trend-cycle decompositions of GDP that give markedly different estimates: the correlated unobserved components model yields output gaps that are small in amplitude, whereas the Hodrick-Prescott (HP) filter generates large and persistent cycles. By embedding the HP filter in an unobserved components model, we show that this difference arises due to differences in the way the stochastic trend is modeled. Moreover, the HP filter implies that the cyclical components are serially independent — an assumption that is decidedly rejected by the data. By relaxing this restrictive assumption, the new model provides comparable model fit relative to the standard correlated unobserved components model.

Keywords: trend-cycle decomposition, HP filter, structural break

JEL Classification: C11, C52, E32

Suggested Citation

Chan, Joshua C. C. and Chan, Joshua C. C. and Grant, Angelia, Reconciling Output Gaps: Unobserved Components Model and Hodrick-Prescott Filter (June 2016). CAMA Working Paper No. 44/2016 , Available at SSRN: https://ssrn.com/abstract=2811452 or http://dx.doi.org/10.2139/ssrn.2811452

Joshua C. C. Chan (Contact Author)

University of Technology Sydney (UTS) - UTS Business School ( email )

Sydney
Australia

Purdue University

West Lafayette, IN 47907-1310
United States

Angelia Grant

Australian National University (ANU) - Centre for Applied Macroeconomic Analysis (CAMA) ( email )

ANU College of Business and Economics
Canberra, Australian Capital Territory 0200
Australia

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