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Labour Market Dynamics in EU: a Bayesian Markov Chain Approach

This paper focuses on labour market dynamics in the EU 15 using Markov Chains for proportions of aggregate data for the first time in this literature. We apply a Bayesian approach, which employs a Monte Carlo Integration procedure that uncovers the entire empirical posterior distribution of transition probabilities from full employment to part employment, temporary employment and unemployment and vice a versa. Thus, statistical inferences are readily available. Our results show that there are substantial variations in the transition probabilities across countries, implying that the convergence of the EU-15 labour markets is far from completed. However, some common patterns are observed as countries with flexible labour markets exhibit similar transition probabilities between different states of the labour market.

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Paper provided by Department of Economics, University of Macedonia in its series Discussion Paper Series with number 2009_07.

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Date of creation: Apr 2009
Date of revision: Apr 2009
Handle: RePEc:mcd:mcddps:2009_07
Contact details of provider: Web page: http://www.uom.gr/index.php?tmima=3

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  1. Jordi Gali, 1996. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations," NBER Working Papers 5721, National Bureau of Economic Research, Inc.
  2. Lawrence J. Christiano & Martin Eichenbaum & Robert J. Vigfusson, 2003. "The response of hours to a technology shock: evidence based on direct measures of technology," International Finance Discussion Papers 790, Board of Governors of the Federal Reserve System (U.S.).
  3. van Dijk, H. K. & Kloek, T., 1980. "Further experience in Bayesian analysis using Monte Carlo integration," Journal of Econometrics, Elsevier, vol. 14(3), pages 307-328, December.
  4. Kloek, Tuen & van Dijk, Herman K, 1978. "Bayesian Estimates of Equation System Parameters: An Application of Integration by Monte Carlo," Econometrica, Econometric Society, vol. 46(1), pages 1-19, January.
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