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Business cycles, trend elimination and the HP filter

Business cycles, trend elimination and the HP filter
Business cycles, trend elimination and the HP filter
Trend elimination and business cycle estimation are analyzed by finite sample and asymptotic methods. An overview history is provided, operator theory is developed, limit theory as the sample size n → ∞ is derived, and filtered series properties are studied relative to smoothing parameter (λ) behavior. Simulations reveal that limit theory with λ =O(n4) delivers excellent approximations to the HP filter for common sample sizes but fails to remove stochastic trends, contrary to standard thinking in macroeconomics and thereby explaining ‘spurious cycle’ effects of the HP filter. The findings are related to the long run effects of the GFC.
0020-6598
1-52
Phillips, Peter C.B.
f67573a4-fc30-484c-ad74-4bbc797d7243
Jin, Sainan
faa63244-5d92-4f1b-9851-c113cc61c0ea
Phillips, Peter C.B.
f67573a4-fc30-484c-ad74-4bbc797d7243
Jin, Sainan
faa63244-5d92-4f1b-9851-c113cc61c0ea

Phillips, Peter C.B. and Jin, Sainan (2020) Business cycles, trend elimination and the HP filter. International Economic Review, 0, 1-52. (doi:10.1111/iere.12494).

Record type: Article

Abstract

Trend elimination and business cycle estimation are analyzed by finite sample and asymptotic methods. An overview history is provided, operator theory is developed, limit theory as the sample size n → ∞ is derived, and filtered series properties are studied relative to smoothing parameter (λ) behavior. Simulations reveal that limit theory with λ =O(n4) delivers excellent approximations to the HP filter for common sample sizes but fails to remove stochastic trends, contrary to standard thinking in macroeconomics and thereby explaining ‘spurious cycle’ effects of the HP filter. The findings are related to the long run effects of the GFC.

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WHP_filter_2020_June_A8_pcb - Accepted Manuscript
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More information

Accepted/In Press date: 9 September 2020
e-pub ahead of print date: 2 December 2020

Identifiers

Local EPrints ID: 445515
URI: http://eprints.soton.ac.uk/id/eprint/445515
DOI: doi:10.1111/iere.12494
ISSN: 0020-6598
PURE UUID: 1cb16507-c7ea-4413-a7de-713d3aa09b01
ORCID for Peter C.B. Phillips: ORCID iD orcid.org/0000-0003-2341-0451

Catalogue record

Date deposited: 14 Dec 2020 17:31
Last modified: 17 Mar 2024 06:08

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Contributors

Author: Peter C.B. Phillips ORCID iD
Author: Sainan Jin

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