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Employment and business cycle asymmetries: a data based study

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  • Gerard A. Pfann

Abstract

Does the magnitude of a trough in employment differ from the magnitude of a peak in employment, and is the time employment spends in rising from a trough to a peak longer than the time spends in falling from a peak to a trough? In this paper we measure the asymmetry of magnitudes and the asymmetry of durations of seven US postwar employment series. The series are detrended using the Hodrick-Prescott filter prior to the analysis. Appropriate measurements of the two types of asymmetry are the skewness of the detrended series and the skewness of the first differenced detrended series, respectively. Monte Carlo and bootstrapping procedures are used to evaluate the significance levels. Five out of seven series show negative skewnesses in levels as well as in first differences. The skewnesses of magnitudes and durations of US aggregate employment are significant, and yield 0.50 and 0.60 respectively. ; In the second part of the paper a nonlinear AR model is derived from the theory of Hermitian type polynomials that have the potential to realize stochastic asymmetric self-sustained oscillations. In contrast with the standard linear AR model, the nonlinear AR model, fitted to the employment series, accurately generates the two types of asymmetry.

Suggested Citation

  • Gerard A. Pfann, 1991. "Employment and business cycle asymmetries: a data based study," Discussion Paper / Institute for Empirical Macroeconomics 39, Federal Reserve Bank of Minneapolis.
    • Handle: RePEc:fip:fedmem:39
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    References listed on IDEAS

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    1. Prescott, Edward C., 1986. "Theory ahead of business-cycle measurement," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 25(1), pages 11-44, January.
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    Cited by:

    1. D. Jones & Maurice Peat & Max Stevenson, 1996. "Does the Process of Spatial Aggregation of U.K. Unemplyment Rate Series Serve to Induce or Remove Evidence of Asymmetry in the Business Cycle," Working Paper Series 67, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    2. James H. Stock & Mark W. Watson, 1993. "A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience," NBER Chapters, in: Business Cycles, Indicators, and Forecasting, pages 95-156, National Bureau of Economic Research, Inc.
    3. Canova, Fabio, 1998. "Detrending and business cycle facts," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 475-512, May.

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