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Title: Income stochastic frontiers: Methodological advances for income inequalities investigations Authors:  Graziella Bonanno - University of Salerno (Italy) [presenting]
Filippo Domma - University of Calabria (Italy)
Camilla Mastromarco - University of Calabria (Italy)
Abstract: The existence of inequalities in income distribution is closely related to the standard conceptualization of efficiency. The idea is to measure the differences between a potential income, obtained for an individual with particular socio-economic characteristics given his investment in human capital, and the income actually received. In particular, we estimate a Mincer equation incorporating human capital variables such as experience, education and occupation. In studies related to earnings frontiers, some scholars use the Stochastic Frontier Approach to get wage efficiency and refer to traditionally approach employing Normally distributed errors. The implicit hypothesis of this specification is that wages follow a log-Normal distribution. However, it has been shown that the latter distribution, particularly in the case of incomes, is not suitable due to the poor ability to describe both the upper and lower tails of the observed distribution of incomes. To overcome this problem, the starting point of our specification is to use the Dagum distribution for the random variable income, for which it has been shown that it fits very well with the entire income distribution. To perform a first empirical analysis in order to test the new SF specification, individuals' data are used derived from IT-SILC (Eurostat), which aims to collect timely and comparable cross-sectional and longitudinal data on income, poverty, social exclusion and living conditions.