May 2017

GDP Trend-cycle Decompositions Using State-level Data

Manuel Gonzalez-Astudillo


This paper develops a method for decomposing GDP into trend and cycle exploiting the cross-sectional variation of state-level real GDP and unemployment rate data. The model assumes that there are common output and unemployment rate trend and cycle components, and that each state's output and unemployment rate are subject to idiosyncratic trend and cycle perturbations. The model is estimated with Bayesian methods using quarterly data from 2005:Q1 to 2016:Q1 for the 50 states and the District of Columbia. Results show that the U.S. output gap reached about -8% during the Great Recession and is about 0.6% in 2016:Q1.

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Keywords: Unobserved components model, state-level GDP data, trend-cycle decomposition


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Last Update: January 09, 2020