Abstract
Abstract. Cluster analysis and the classification tree technique are applied to investigate the relationship between the individual characteristics of Italian temporary help agency (THA) workers and their probability of achieving a temporary job. The application aims to show some advantages of these techniques with respect to traditional econometric tools. Sketches of the most common profiles among Italian THA workers are obtained as a result. Besides the typical THA worker pointed out by previous studies (young male workers, with a medium–high level of education, living in the Northern regions), two new profiles have been identified: the first comprising male manual workers with previous job experience, whose average age is over 30 and whose educational level is low; the second comprising young female workers with a medium–high level of education, working in the service sector or in the public sector. The results are compared with the more usual logit analysis and show their robustness.
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