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Why are Bayesian trend-cycle decompositions of US real GDP so different?

Authors
Kim, JaehoChon, Sora
Issue Date
Mar-2020
Publisher
Springer Verlag
Keywords
Gibbs sampling; Structural break; Trend-cycle decomposition; Unobserved components model
Citation
Empirical Economics, v.58, no.3, pp 1339 - 1354
Pages
16
Indexed
SSCI
SCOPUS
Journal Title
Empirical Economics
Volume
58
Number
3
Start Page
1339
End Page
1354
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/114236
DOI
10.1007/s00181-018-1554-0
ISSN
0377-7332
1435-8921
Abstract
This paper provides an underlying reason for why recent Bayesian trend-cycle decompositions of US 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. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
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