Issues in Measuring and Modeling Poverty

Economists have relied heavily on household incomes or expenditures normalized for differences in household specific prices and demographics in their research and policy advice related to poverty and inequality. Recognizing the conceptual and empirical problems that confound such measures does not mean that they should be ignored. Instead, it indicates the need for supplementary measures to capture the missing items. Implementing a genuinely multidimensional approach will often make the welfare rankings of social states more difficult, but that fact points to the nonrobustness of low-dimensional rankings. This may have its own policy ramifications, with the possibility of correspondence between policy instruments and welfare objectives. The model types used to understand the poverty and inequity determination processes will be affected. Not only will there be more dependent variables to consider, but variables will have potentially complex relationships. These relationships will often be hard to empirically disentangle, despite richer integrated and longitudinal data sets. Such data open rich and relevant agenda for research into the dynamics of poverty along multiple dimensions. A simultaneous attack on these issues from all three fronts - measurement, modeling, and data - offers hope of establishing a credible empirical foundation for public action in fighting poverty