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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