GDP Trend-cycle Decompositions Using State-level Data

Manuel González-Astudillo

No 2017-051, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

Abstract: 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.

Keywords: unobserved component model; State-level GDP data; Trend-cycle decomposition (search for similar items in EconPapers)
JEL-codes: C13 C32 C52 (search for similar items in EconPapers)
Pages: 34 pages
Date: 2017-05
New Economics Papers: this item is included in nep-ets
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedgfe:2017-51

DOI: 10.17016/FEDS.2017.051

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