When are trend–cycle decompositions of GDP reliable?

Manuel González-Astudillo and John Roberts

Empirical Economics, 2022, vol. 62, issue 5, No 13, 2417-2460

Abstract: Abstract In this paper, we examine the results of GDP trend–cycle decompositions from the estimation of bivariate unobserved components models that allow for correlated trend and cycle innovations. Three competing variables are considered in the bivariate setup along with GDP: the unemployment rate, the inflation rate, and gross domestic income. We find that the unemployment rate is the preferred variable to accompany GDP in the bivariate setup to obtain accurate estimates of its trend–cycle correlation coefficient and the cycle. We show that the key feature of the unemployment rate that allows for reliable estimates of the cycle of GDP is that its nonstationary component is small relative to its cyclical component. Using quarterly GDP and unemployment rate data from 1948:Q1 to 2019:Q1, we obtain a trend–cycle decomposition of GDP that resembles the conventional CBO estimates; we find positively correlated trend and cycle components.

Keywords: Unobserved components model; Trend–cycle decomposition; Trend–cycle correlation; Bayesian estimation (search for similar items in EconPapers)
JEL-codes: C13 C32 C52 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s00181-021-02105-4

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