What exactly does it mean to be poor? Is it strictly a matter of income, or do other factors count as well, like education and health?
Oxford's new look at poverty may be able to help us better understand which hardships challenge the world's poor. The Multidimensional Poverty Index, or MPI, takes a more holistic approach to measuring poverty than previous poverty indexes, which have focused mainly on income, reports Planet Money. It was designed by the Oxford Poverty and Human Development Initiative (OPHI) in partnership with the United Nations.
The MPI examines three major aspects of poverty: education, health and living standard. More specifically, it considers 10 indicators that affect well-being on a household level, like quality of nutrition, type of cooking fuel, and if a family has a latrine. Ideally, the result is a detailed portrait of the nature and intensity of poverty.
So far the MPI has been applied to populations in 104 developing countries, which are home to nearly 80 percent of the world's poor. Check out OPHI's cool interactive world map to explore the poverty indicators for these countries.
Economists like the World Bank's Martin Ravillion question the MPI's methodology, claiming that it's a mistake to combine so many disparate factors into a single index as though they are equal in value. Ravillion describes the MPI's weakness like comparing "apples and oranges" here on Oxfam's From Poverty to Power blog.
But Sabina Alkire, co-creator of the MPI, insists on the importance of considering multiple aspects so we can understand not just who is poor but "how they are poor." Multidimensional models like the MPI could potentially teach us about correlations between various factors -- for example, does the fact that a child is malnourished relate to whether he or she is educated? OPHI explains how economists, governments and NGOs can apply the new index to their endeavors:
The MPI can be used as an analytical tool to identify the most vulnerable people, show aspects in which they are deprived and help to reveal the interconnections among deprivations. This enables policy makers to target resources and design policies more effectively.