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Markov switching in disaggregate unemployment rates

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Author Info

  • Chinhui Juhn

    ()
    (Department of Economics, Univesity of Houston, Houston, TX 77204, cjuhn@uh.edu.)

  • Simon Potter

    ()
    (Domestic Research, Federal Reserve Bank of New York, New York, NY 10045, simon.potter@ny.frb.org.)

  • Marcelle Chauvet

    ()
    (Department of Economics University of California, Riverside, CA 92521, chauvet@mail.ucr.edu.)

Abstract

We develop a dynamic factor model with Markov switching to examine secular and business cycle fluctuations in the U.S. unemployment rates. We extract the common dynamics amongst unemployment rates disaggregated for 7 age groups. The framework allows analysis of the contribution of demographic factors to secular changes in unemployment rates. In addition, it allows examination of the separate contribution of changes due to asymmetric business cycle fluctuations. We find strong evidence in favor of the common factor and of the switching between high and low unemployment rate regimes. We also find that demographic adjustments can account for a great deal of secular changes in the unemployment rates, particularly the abrupt increase in the 1970s and 1980s and the subsequent decrease in the last 18 years.

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Bibliographic Info

Article provided by Springer in its journal Empirical Economics.

Volume (Year): 27 (2002)
Issue (Month): 2 ()
Pages: 205-232

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Handle: RePEc:spr:empeco:v:27:y:2002:i:2:p:205-232

Note: Received: December 2000/Final Version Received: June 2001
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Related research

Keywords: Markov switching; unemployment; common factor; asymmetries; business cycle; baby boom; Bayesian methods;

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References

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  1. Jaap H. Abbring & Gerard J. van den Berg & Jan C. van Ours, 1997. "Business Cycles and Compositional Variation in U.S. Unemployment," Tinbergen Institute Discussion Papers 97-050/3, Tinbergen Institute.
  2. Chib, Siddhartha, 2001. "Markov chain Monte Carlo methods: computation and inference," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 57, pages 3569-3649 Elsevier.
  3. Chauvet, Marcelle, 1998. "An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 969-96, November.
  4. Kim, C-J., 1991. "Dynamic Linear Models with Markov-Switching," Papers 91-8, York (Canada) - Department of Economics.
  5. John Geweke, 1998. "Using simulation methods for Bayesian econometric models: inference, development, and communication," Staff Report 249, Federal Reserve Bank of Minneapolis.
  6. Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November.
  7. Diebold, Francis X & Rudebusch, Glenn D, 1996. "Measuring Business Cycles: A Modern Perspective," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 67-77, February.
  8. Skalin, Joakim & Teräsvirta, Timo, 1998. "Modelling asymmetries and moving equilibria in unemployment rates," Working Paper Series in Economics and Finance 262, Stockholm School of Economics, revised 05 Oct 1998.
  9. Koop, Gary & Potter, Simon M., 1998. "Bayes factors and nonlinearity: Evidence from economic time series1," Journal of Econometrics, Elsevier, vol. 88(2), pages 251-281, November.
  10. Geweke, John, 1986. "Exact Inference in the Inequality Constrained Normal Linear Regression Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(2), pages 127-41, April.
  11. Vredin, Anders & Warne, Anders, 2000. "Unemployment and Inflation Regimes," Working Paper Series 107, Sveriges Riksbank (Central Bank of Sweden).
  12. Robert J. Gordon, 1981. "Inflation, Flexible Exchange Rates, and the Natural Rate of Unemployment," NBER Working Papers 0708, National Bureau of Economic Research, Inc.
  13. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
  14. Chinhui Juhn & Kevin M. Murphy & Robert H. Topel, 1991. "Why Has the Natural Rate of Unemployment Increased over Time?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 22(2), pages 75-142.
  15. Neftci, Salih N, 1984. "Are Economic Time Series Asymmetric over the Business Cycle?," Journal of Political Economy, University of Chicago Press, vol. 92(2), pages 307-28, April.
  16. Boldin, Michael D, 1994. "Dating Turning Points in the Business Cycle," The Journal of Business, University of Chicago Press, vol. 67(1), pages 97-131, January.
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Cited by:
  1. Jean-michel Sahut & Medhi Mili & Frédéric Teulon, 2012. "What is the linkage between real growth in the Euro area and global financial market conditions?," Economics Bulletin, AccessEcon, vol. 32(3), pages 2464-2480.
  2. Mili, Mehdi & Sahut, Jean-Michel & Teulon, Frédéric, 2012. "Non linear and asymmetric linkages between real growth in the Euro area and global financial market conditions: New evidence," Economic Modelling, Elsevier, vol. 29(3), pages 734-741.
  3. Michael J. Dueker & Michael T. Owyang & Martin Sola, 2010. "A time-varying threshold STAR model of unemployment and the natural rate," Working Papers 2010-029, Federal Reserve Bank of St. Louis.
  4. Hamilton, James D., 2003. "Comment on "A comparison of two business cycle dating methods"," Journal of Economic Dynamics and Control, Elsevier, vol. 27(9), pages 1691-1693, July.
  5. José Cancelo, 2007. "Cyclical Asymmetries in Unemployment Rates: International Evidence," International Advances in Economic Research, Springer, vol. 13(3), pages 334-346, August.

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