This chapter proposes an original methodology to measure social exclusion and applies it to the UNDP/UNICEF 2010 survey dataset on social exclusion in FYR Macedonia. Following a brief presentation of some general features of the economic and social situation in FYR Macedonia, this chapter explains first that the multivariate technique called correspondence analysis allows one to aggregate in one factor, separately for each domain of social exclusion, the variables that are available to characterize this domain. Then an approach commonly used in productivity analysis and called stochastic production frontier is presented. This technique allowed us to derive a latent vector assumed to represent the level of overall social exclusion of each of the individuals in the survey. In the last section of this chapter, an attempt is made to find out what the determinants of social exclusion are by regressing the latent variable assumed to describe social exclusion on a certain number of explanatory variables such as the level of education, the marital status, and the age of the individual.
Deutsch J., Silber J., Verme P. (2013). On measuring social exclusion: A new approach with an application to FYR Macedonia. New York : Springer [10.1007/978-1-4614-4945-4_7].
On measuring social exclusion: A new approach with an application to FYR Macedonia
Verme P.
2013
Abstract
This chapter proposes an original methodology to measure social exclusion and applies it to the UNDP/UNICEF 2010 survey dataset on social exclusion in FYR Macedonia. Following a brief presentation of some general features of the economic and social situation in FYR Macedonia, this chapter explains first that the multivariate technique called correspondence analysis allows one to aggregate in one factor, separately for each domain of social exclusion, the variables that are available to characterize this domain. Then an approach commonly used in productivity analysis and called stochastic production frontier is presented. This technique allowed us to derive a latent vector assumed to represent the level of overall social exclusion of each of the individuals in the survey. In the last section of this chapter, an attempt is made to find out what the determinants of social exclusion are by regressing the latent variable assumed to describe social exclusion on a certain number of explanatory variables such as the level of education, the marital status, and the age of the individual.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
