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Trend-cycle-seasonal interactions: identification and estimation

Vol: 
CAMA Working Paper 57/2017
Author name: 
Irma Hindrayanto
Jan P.A.M. Jacobs
Denise R. Osborn
Jing Tian
Year: 
2017
Month: 
September
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 non-zero 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.

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