Title: Dynamic Measurement of Poverty: Modeling and Estimation

Author(s): Guglielmo D’Amico and Philippe Regnault
Issue: Volume 80 Series B Part 2 Year 2018
Pages: 305 -- 340
This study presents a model of income evolution from which dynamic versions of commonly used static poverty measures are derived. The dynamic indexes are calculated both for finite- and infinite-size economic systems. Probabilistic convergence results prove that the infinite-size system can be conveniently used to approximate the finite-size system in an effective way. Secondly, poverty indexes estimation based on micro-data are discussed under different sampling schemes and it is proved that they are strongly consistent. A hypothetical example is used to show the dynamic evolution of the poverty and the estimation methodologies.
AMS (2000) subject classification. Primary 60J25; Secondary 91B82.
Keywords and phrases: Markov process, Population dynamic, Nonparametric estimation, Micro-data