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Trend–Cycle–Seasonal Interactions: Identification And Estimation

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  • Hindrayanto, Irma
  • Jacobs, Jan P.A.M.
  • Osborn, Denise R.
  • Tian, Jing

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.

Suggested Citation

  • Hindrayanto, Irma & Jacobs, Jan P.A.M. & Osborn, Denise R. & Tian, Jing, 2019. "Trend–Cycle–Seasonal Interactions: Identification And Estimation," Macroeconomic Dynamics, Cambridge University Press, vol. 23(8), pages 3163-3188, December.
  • Handle: RePEc:cup:macdyn:v:23:y:2019:i:8:p:3163-3188_5
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