Why Are Bayesian Trend-Cycle Decompositions of U.S. Real GDP So Different?

19 Pages Posted: 2 Feb 2017 Last revised: 8 May 2018

See all articles by Jaeho Kim

Jaeho Kim

University of Oklahoma

Sora Chon

Korea Development Institute (KDI)

Date Written: April 1, 2018

Abstract

This paper provides an underlying reason for why recent Bayesian trend-cycle decompositions of U.S. real GDP differ despite using identical unobserved components models. We stress that a pitfall in estimating unobserved components models accounts for the divergence in the empirical conclusions. Our results also show that the decline in the long-run growth rate of real GDP has been slow and gradual rather than abrupt during the post-World War II period.

Keywords: Trend-Cycle Decomposition, Unobserved Components Model, Structural Break, Gibbs Sampling

JEL Classification: C11, E32

Suggested Citation

Kim, Jaeho and Chon, Sora, Why Are Bayesian Trend-Cycle Decompositions of U.S. Real GDP So Different? (April 1, 2018). Available at SSRN: https://ssrn.com/abstract=2908367 or http://dx.doi.org/10.2139/ssrn.2908367

Jaeho Kim (Contact Author)

University of Oklahoma ( email )

729 Elm Avenue
Norman, OK 73019-2103
United States

Sora Chon

Korea Development Institute (KDI) ( email )

263 Namsejong-ro
Sejong-si 30149
Korea, Republic of (South Korea)

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