On some measures of poverty dynamics

Poverty measurement is an old research problem that is again of wide interest and has many open problems to be solved. Traditionally, several measures have been proposed to quantify different aspects of poverty. Recently, a stochastic approach to the problem has emerged and led to new results. Basically, it consists of modeling the income evolution of the economic agents according to a continuous-time Markov chain, extending the classical poverty measures into this dynamic framework, and deriving approximate computations of the poverty measures based on probabilistic arguments. The paper reviews such an approach, focusing on the generalization of classical poverty measures into a dynamic setting, and also presents some new measures of interest.