"The MPI uses 10 indicators to measure three critical dimensions of poverty at the household level: education, health and living standard in 104 developing countries. These directly measured deprivations in health and educational outcomes as well as key services such as water, sanitation, and electricity reveal not only how many people are poor but also the composition of their poverty.
"The MPI also reflects the intensity of poverty -- the sum of weighted deprivations that each household faces at the same time. A person who is deprived in 70% of the indicators is clearly worse off than someone who is deprived in 40% of the indicators."
This isn’t just about variables, but also about normalization, weights and aggregate. I fear the average "policy-maker" will simply be lost. Using MPI, we have been told poverty in India is concentrated in Bihar, Chhattisgarh, Jharkhand, MP, Orissa, Rajasthan, UP and West Bengal. At the risk of being deliberately unfair to MPI, did we need MPI to tell us that?2010 will mark 20 years of UNDP’s Human Development Reports (HDRs). Consequently, UNDP wants to do something new. There cannot be any dispute that HDRs have been phenomenally successful in focusing attention on human development aspects, and the MDGs (Millennium Development Goals) may not have evolved without HDRs. There have been regional and sub-regional HDRs too, such as state-level ones in India.
Among several development-cum-deprivation measures used in HDRs, HDI (human development index) based on education (literacy, enrolment rate), health (life expectancy) and PPP per capita income are the most commonly cited. Since 1990 and even earlier, we have known poverty is multi-dimensional. It cannot be captured through simple measures, it is also a process. However, several poverty-related variables are correlated with one another. Therefore, even simple measures based on a few variables can provide a good enough picture.
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