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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.

Suggested Citation

  • George A. Christodoulakis & Emmanuel C. Mamatzakis, 2009. "Labour Market Dynamics in EU: a Bayesian Markov Chain Approach," Discussion Paper Series 2009_07, Department of Economics, University of Macedonia, revised Apr 2009.
  • Handle: RePEc:mcd:mcddps:2009_07

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    References listed on IDEAS

    1. Jordi Gali, 1999. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," American Economic Review, American Economic Association, vol. 89(1), pages 249-271, March.
    2. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2004. "The Response of Hours to a Technology Shock: Evidence Based on Direct Measures of Technology," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 381-395, 04/05.
    3. 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.
    4. 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.
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    More about this item


    Employment; Unemployment; Markov Chains.;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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