Jobless Recovery: A Time Series Look at the United States
James DeNicco () and
Christopher A. Laincz
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James DeNicco: Rice University
Christopher A. Laincz: Drexel University
Atlantic Economic Journal, 2018, vol. 46, issue 1, 3-25
Abstract We use vector auto regression models controlling for log differences in gross domestic product (GDP), the unemployment rate, and changes in the unemployment rate to show that following a recession, the rate of decrease in the unemployment rate significantly slowed over time. Controlling for GDP growth rates, we find two structural breaks indicating weaker recoveries in the unemployment rate over time, i.e. recoveries that are increasingly jobless. The first break is in 1959, and the second is in 1984 coinciding with the usual timing of the Great Moderation. Using the 7.85% unemployment rate at the end of 2012 and assuming average annual recovery growth of 2%, the structural breaks imply an additional two full years are necessary to return to a historical long-run average of 5.5%. We empirically explore possible causes proposed in the literature including industry composition, participation rates and social benefits. Demographic shifts in the labor force and changing industry composition appear to be the strongest contributors to jobless recovery.
Keywords: Unemployment rates; Business cycles; Multivariate analysis and structural breaks; E24; E32; C32 (search for similar items in EconPapers)
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