Whatever happened to the business cycle? a Bayesian analysis of jobless recoveries
AbstractDuring the typical recovery from U.S. post-War period economic downturns, employment recovers to its pre-recession level within months of the output trough. However, during the last two recoveries, employment has taken up to two years to achieve its pre-recession benchmark. We propose a formal empirical model of business cycles with recovery periods to demonstrate that the last two recoveries have been statistically different from previous experiences. We find that this difference can be attributed to a shift in the speed of transition between business cycle regimes. Moreover, we find this shift results from both durable and non-durable manufacturing sectors losing their cyclical characteristics. We argue that this finding of acyclicality in post-1980 manufacturing sectors is consistent with previous hypotheses (e.g., improved inventory management) regarding the reduction in macroeconomic volatility over the same period. These results suggest a link between the two phenomena, which have heretofore been studied separately.
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Bibliographic InfoPaper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2007-013.
Date of creation: 2007
Date of revision:
Other versions of this item:
- Engemann, Kristie M. & Owyang, Michael T., 2010. "Whatever Happened To The Business Cycle? A Bayesian Analysis Of Jobless Recoveries," Macroeconomic Dynamics, Cambridge University Press, vol. 14(05), pages 709-726, November.
- NEP-ALL-2007-06-23 (All new papers)
- NEP-BEC-2007-06-23 (Business Economics)
- NEP-MAC-2007-06-23 (Macroeconomics)
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- Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2012. "Forecasting UK GDP growth, inflation and interest rates under structural change: a comparison of models with time-varying parameters," Bank of England working papers 450, Bank of England.
- R. Jason Faberman, 2008. "Job flows, jobless recoveries, and the Great Moderation," Working Papers 08-11, Federal Reserve Bank of Philadelphia.
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