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

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

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Year of publication:	2018
Authors:	Kim, Jaeho
Other Persons:	Chon, Sora (contributor)
Publisher:	[2018]: [S.l.] : SSRN
Subject:	USA \| United States \| Nationaleinkommen \| National income \| Dekompositionsverfahren \| Decomposition method \| Bayes-Statistik \| Bayesian inference \| Zeitreihenanalyse \| Time series analysis \| Konjunktur \| Business cycle \| Bruttoinlandsprodukt \| Gross domestic product

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Extent:	1 Online-Ressource (19 p)
Type of publication:	Book / Working Paper
Language:	English
Notes:	Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments April 1, 2018 erstellt
Other identifiers:	10.2139/ssrn.2908367 [DOI]
Classification:	C11 - Bayesian Analysis ; E32 - Business Fluctuations; Cycles
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012934793