When the United Nations Development Programme (UNDP) releases its annual Human Development Report for 2010, there will this time be a new measure of poverty in countries from the trade income based measure of poverty.
The UNDP and Oxford University have launched a new index to measure poverty levels which they said give a “multidimensional” picture of people living in hardship, and could help target development resources more effectively.
The two institutions said in a joint news release that the new measure, the Multidimensional Poverty Index, or MPI, was developed and applied by the Oxford Poverty and Human Development Initiative (OPHI) with UNDP support.
The MPI will be featured in the forthcoming 20th anniversary edition of the UNDP Human Development Report, and replaces the Human Poverty Index, which had been included in these reports since 1997.
“The MPI provides a fuller measure of poverty than the traditional dollar-a-day formulas. It is a valuable addition to the family of instruments we use to examine broader aspects of well-being, including UNDP’s Human Development Index and other measures of inequality across the population and between genders,” says Jeni Klugman, Director of the UNDP Human Development Report Office and the principal author of this year’s report.
This year’s Human Development Report will be published in late October, but research findings from the MPI were made available today at a policy forum in London and on line on the websites of OPHI (http://www.ophi.org.uk) and the UNDP Human Development Report (http://hdr.undp.org/en/).
The MPI assesses a range of critical factors or “deprivations” at the household level: from education to health outcomes to assets and services. “Taken together, these factors provide a fuller portrait of acute poverty than simple income measures,” OPHI and UNDP said in the statement.
The measure reveals the nature and extent of poverty at different levels: from household up to regional, national and international levels. The multidimensional approach to assessing poverty has been adapted for national use in Mexico, and is now being considered by Chile and Colombia.
“The MPI is like a high resolution lens which reveals a vivid spectrum of challenges facing the poorest households,” said OPHI Director Sabina Alkire, who created the MPI with James Foster of George Washington University.
The UNDP Human Development Report Office says they are joining forces with OPHI to promote international discussions on the practical applicability of this multidimensional approach to measuring poverty.
New Multidimensional Poverty Measure Index map
Country | Multidimensional Poverty Index (MPI) (null) (No year) |
Slovenia | 0 |
Slovakia | 0 |
Czech Republic | 0.0000515 |
Belarus | 0.0000804 |
Latvia | 0.0014039 |
United Arab Emirates | 0.0020124 |
Kazakhstan | 0.0021675 |
Palestinian Territories | 0.0026515 |
Georgia | 0.0028182 |
Hungary | 0.0029484 |
Bosnia and Herzegovina | 0.0030181 |
Serbia | 0.0033291 |
Albania | 0.0036619 |
Russian Federation | 0.004914 |
Uruguay | 0.0058453 |
Thailand | 0.0063474 |
Montenegro | 0.0063739 |
Croatia | 0.0066471 |
Ukraine | 0.0078279 |
Macedonia | 0.0078303 |
Armenia | 0.0082274 |
Rep. of Moldova | 0.0082328 |
Uzbekistan | 0.0084111 |
Ecuador | 0.0091946 |
Jordan | 0.0095726 |
Tunisia | 0.010469 |
Argentina | 0.0112819 |
South Africa | 0.0143359 |
Mexico | 0.0154625 |
Kyrgyzstan | 0.0188584 |
Trinidad and Tobago | 0.0197402 |
Sri Lanka | 0.0206195 |
Azerbaijan | 0.0207166 |
Syrian Arab Republic | 0.0207464 |
Belize | 0.0236837 |
Egypt | 0.0258936 |
Estonia | 0.0263797 |
Turkey | 0.0389074 |
Brazil | 0.0391825 |
Colombia | 0.0406378 |
Suriname | 0.0438603 |
Dominican Republic | 0.04783 |
Guyana | 0.0546115 |
China | 0.0559935 |
Iraq | 0.0587957 |
Paraguay | 0.0642984 |
Mongolia | 0.0646115 |
Philippines | 0.0672428 |
Tajikistan | 0.0684319 |
Vietnam | 0.0750767 |
Peru | 0.0853588 |
Myanmar (Burma) | 0.0880144 |
Indonesia | 0.0953236 |
Guatemala | 0.1270255 |
Djibouti | 0.138538 |
Morocco | 0.1391553 |
Ghana | 0.1396917 |
Honduras | 0.1595332 |
Gabon | 0.1608929 |
Zimbabwe | 0.1738981 |
Bolivia | 0.1751358 |
Swaziland | 0.1827849 |
Namibia | 0.1869626 |
Nicaragua | 0.2112119 |
Lesotho | 0.220099 |
São Tomé and Principe | 0.236401 |
Cambodia | 0.2633314 |
Lao People’s Dem. Rep. | 0.2669367 |
Pakistan | 0.2753857 |
Yemen | 0.2832491 |
Togo | 0.2844177 |
Bangladesh | 0.2913768 |
India | 0.2962426 |
Cameroon | 0.2985434 |
Kenya | 0.3020832 |
Haiti | 0.3055187 |
Côte d’Ivoire | 0.3201939 |
Gambia | 0.3236082 |
Zambia | 0.3253048 |
Chad | 0.3441871 |
Nepal | 0.3499077 |
Mauritania | 0.3520175 |
Tanzania | 0.3673323 |
Nigeria | 0.3676438 |
Senegal | 0.3841565 |
Malawi | 0.3843631 |
Congo | 0.3931986 |
Comoros | 0.4084577 |
Benin | 0.412274 |
Madagascar | 0.4127711 |
Rwanda | 0.4425673 |
Angola | 0.4520091 |
Mozambique | 0.4807159 |
Liberia | 0.4839164 |
Sierra Leone | 0.4891497 |
Guinea | 0.5046654 |
Cent African Rep | 0.51229 |
Somalia | 0.5137413 |
Burundi | 0.529762 |
Burkina Faso | 0.5358329 |
Mali | 0.5639204 |
Ethiopia | 0.5823998 |
Niger | 0.6424667 |