We develop an ordinal method for making welfare comparisons between populations with multidimensional discrete well-being indicators observed at the micro level. The approach assumes that, for each well-being indicator, the levels can be ranked from worse to better; however, no assumptions are...

We develop an approach for making welfare comparisons between populations with multidimensional discrete well-being indicators observed at the micro level. The approach is rooted in the concept of multidimensional first order dominance. It assumes that, for each indicator, the levels can be...

We develop an approach for making welfare comparisons between populations with multidimensional discrete well-being indicators observed at the micro level. The approach is rooted in the concept of multidimensional first order dominance. It assumes that, for each indicator, the levels can be...

We develop an approach for making welfare comparisons between populations with multidimensional discrete well-being indicators observed at the micro level. The approach is rooted in the concept of multidimensional first order dominance. It assumes that, for each indicator, the levels can be...

We develop an ordinal method for making welfare comparisons between populations with multidimensional discrete well-being indicators observed at the micro level. The approach assumes that, for each well-being indicator, the levels can be ranked from worse to better; however, no assumptions are...