Unemployment insurance and training in an equilibrium matching model with heterogeneous agents

Bruno Van der Linden

No 2003001, LIDAM Discussion Papers IRES from Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES)

Abstract: This paper develops a joint evaluation of vocational training and unemployment insurance. This allows to analyze how these schemes complment each other from the viewpoints of labor market indicators and of welfare. For this purpose, a general equilibrium matching model is built where workers are heterogeneous and risk averse. Heterogeneity allows to look at the distribution of the effects. Job search effort and wages are endogenous in order to deal with the induced effects of these schemes. The net effect of these training programs appears to be gloomy. However, their impact on employment can be deeply affected by the design of passive policies. A declining time profile of benefit payments dominates a scheme with a constant replacement ratio. However, the optimal expected length of payment of ‘high’ benefits can vary a lot in the population. A reform that would relate this expected duration to search effort does not appear to produce substantial effects on any of the evaluation crieria. Performance indicators of the labor market and welfare criteria often vary in opposite directions after a reform. This questions the widespread focus on labor market indicators to guide the design of institutional reforms.

Keywords: training; unemployment insurance; sanctions; policy complementaries; wage bargaining; equilibrium unemployment; equilibrium search (search for similar items in EconPapers)
JEL-codes: J63 J64 J65 J68 (search for similar items in EconPapers)
Pages: 45
Date: 2003-01-01
New Economics Papers: this item is included in nep-ias and nep-lab
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Related works:
Working Paper: Unemployment Insurance and Training in an Equilibrium Matching Model with Heterogeneous Agents (2003)
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