TREND–CYCLE–SEASONAL INTERACTIONS: IDENTIFICATION AND ESTIMATION
Irma Hindrayanto (),
Jan Jacobs,
Denise Osborn and
Jing Tian
Macroeconomic Dynamics, 2019, vol. 23, issue 8, 3163-3188
Abstract:
Economists typically use seasonally adjusted data in which the assumption is imposed that seasonality is uncorrelated with trend and cycle. The importance of this assumption has been highlighted by the Great Recession. The paper examines an unobserved components model that permits nonzero correlations between seasonal and nonseasonal shocks. Identification conditions for estimation of the parameters are discussed from the perspectives of both analytical and simulation results. Applications to UK household consumption expenditures and US employment reject the zero correlation restrictions and also show that the correlation assumptions imposed have important implications about the evolution of the trend and cycle in the post-Great Recession period.
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
https://www.cambridge.org/core/product/identifier/ ... type/journal_article link to article abstract page (text/html)
Related works:
Working Paper: Trend-cycle-seasonal interactions: identification and estimation (2017) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:cup:macdyn:v:23:y:2019:i:8:p:3163-3188_5
Access Statistics for this article
More articles in Macroeconomic Dynamics from Cambridge University Press Cambridge University Press, UPH, Shaftesbury Road, Cambridge CB2 8BS UK.
Bibliographic data for series maintained by Kirk Stebbing ().