Abstract
The aim of this paper is to analyze how the geospatial distributions of unemployed people and jobcentres affects the probability of finding a job. We estimated a latent class logistic regression to analyze the probability of a transition to employment while controlling for individual and location heterogeneity. We compute the median value of the odds ratios between the area with the highest employment probability and the area with the lowest employment probability when randomly selecting areas. The results support the need to develop employment policies that take into account a place-based environment and to investigate how an institution’s impact can be people- and place-sensitive. An additional objective of this paper is to discuss this issue and suggest the need for the formulation of targets at jobcentres as well as the division of funding according to the targets and results that are to receive welfare advantages
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