Abstract
In this paper one of the challenges of multidimensional poverty measurement is addressed, i.e. the dependence between well-being dimensions. To measure this dependence, copula-based correlation coefficients are employed. This methodology is applied to EU-SILC data for the year 2015. The results of estimation suggest that individual performances in different dimensions correlate, but its magnitude varies across countries. The highest dependence is observed between educational and income dimensions. The results of the pairwise estimation of correlation coefficients are then used for developing a weighting scheme in the multidimensional poverty index. This approach allows, in particular, to incorporate this inter-dimensional dependence into a multidimensional poverty measure.