Employment of Disabled People According to Law 68/1999. A Multidimensional Analysis at Regional Level
AbstractLaw 68/1999, whose aim is the regulation and promotion of the employment of persons with disabilities, delegates to regions the management of the labour market. However, its successful implementation does not depend exclusively on the regions’ actions but also on the environmental context. We propose a two-step analysis focusing on Italian regions for the year 2005. In the first phase, we use multidimensional scaling in order to identify different socio-economic contexts. Then, cluster analysis is used in order to test for the presence of subsets among Italian regions. The results show that an environment featuring a large number of profit-making firms, and providing support services for disabled people, provides most opportunities for the employment of disabled people. On the contrary, large public sector organizations and a rather closed social environment do not seem to have a positive impact on the employment process.
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Bibliographic InfoArticle provided by Vita e Pensiero, Pubblicazioni dell'Universita' Cattolica del Sacro Cuore in its journal Rivista Internazionale di Scienze Sociali.
Volume (Year): 120 (2012)
Issue (Month): 1 ()
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Disabled People; Public Policy; Non-Labour Market Discrimination; Multidimensional Scaling; Cluster Analysis;
Find related papers by JEL classification:
- J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination
- J48 - Labor and Demographic Economics - - Particular Labor Markets - - - Particular Labor Markets; Public Policy
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
- C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
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