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Multidimensional Poverty Index (MPI) Disparity and Dynamics Sabina Alkire, José Manuel Roche, and Suman Seth Rome, 22 May 2012. OPHI – MPI Team.
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José Manuel Roche,
and Suman Seth
Rome, 22 May 2012
OPHI Research Team: Sabina Alkire (Director), James Foster (Research Fellow), John Hammock (Co-Founder and Research Associate), José Manuel Roche (coordination MPI 2011), Maria Emma Santos (coordination MPI 2010), Suman Seth, Paola Ballon, Gaston Yalonetzky, Diego Zavaleta.
Data analysts and MPI calculation since 2011: Mauricio Apablaza, Adriana Conconi, Ivan Gonzalez DeAlba, Gisela Robles Aguilar, Juan Pablo Ocampo Sheen, Sebastian Silva Leander, Christian Oldiges, Nicole Rippin, and Ana Vaz.
Special contributions:Mauricio Apablaza (analysis of family planning), Yadira Diaz (preparation of the maps), Maja Jakobsen (research assistance and preparation of graphs), Nicole Rippin (methodological inputs) Christian Oldiges (research assistance for regional decomposition), Gisela Robles Aguilar (tables, data compilation and preparation of the maps), John Hammock, Sabina Alkire and James Jewell (new Ground Reality Check field material), Maria Emma Santos (methodological inputs and adjustments of MPI methodology), Gaston Yalonetzky (design and programming for standard error calculation).
Communication Team:Paddy Coulter (Director of Communications), Joanne Tomkinson (Research Communications Officer), Heidi Fletcher (Web Manager), Moizza B Sarwar (Research Communications Assistant), and Sarah Valenti (Research Communications Consultant) and Cameron Thibos (Design Assistant).
Administrative Support: Tery van Taack (OPHI Project coordinator), Laura O'Mahony (OPHI Project Assistant)
OPHI prepare the MPI for publication in the UNDP Human Development Report and we are grateful to our colleagues in HDRO for their support.
What is new?
MPI in Middle Income Countries
MPI over Time
A person is multidimensionally poor if they are deprived in 33% of the dimensions.
(censor the deprivations of the non-poor)
The MPI isappropriate for ordinal data, and satisfiespropertieslikesubgroupconsistency, dimensional monotonicity, poverty & deprivationfocus. MPI islikethepoverty gap measure – but looks at breadthinstead – whatbatters a person at thesame time.
Formula: MPI = M0 = H × A
The MPI starts with each person, and constructs a deprivation profile for each person.
Some people are identified as poor based on their joint deprivations. The others are identified as non-poor.
Deprived in 67% of dimensions.
It doesn’t tell the full story
But it gives some idea.
These results are for 109 developing countries, selected because they have DHS, MICS or WHS data since 2000. Special surveys were used for Argentina, Brazil, Mexico, Morocco, Occupied Palestinian Territory, and South Africa
They cover 5.3 billion people - 78.6% of the world’s population
Of these 5.3 billion people, 31% of people are poor.
That is 1.65 billion people.
(2008 population figures taken from Population Prospects 2011; 2010 Revision).
Total Population in 109 MPI countries
MPI poor people by region
103 of our 109 Countries have income; only 71 have income poverty data within 3 years of MPI. Income data ranges from 1992-2008; MPI from 2000-2010.
~ 31 Low Income Countries,(700.9M), 92%
~ 70 Middle Income Countries, (1189.2M), 94%:
~ 42 Lower Middle Income (2378.9M) 97%
~ 28 Upper Middle Income (2178.9M) 90%
~ 8 High Income Countries (41.2M), of which:
~ 5 OECD (29.2M)
~ 2 non-OECD (12M)
Total Population: 5.3 Billion people
(population figures from 2008; data from 2000-2010).
Total Population by Income Category (2008)
MPI Poor Population (2008)
There are more than twice as many ‘severely poor’ people in MICS as in LICS.
And 50% of the world’s 869M severely poor also live in South Asia
26 poorest regions of South Asia
Data for 49 countries and 497 sub-national regions with 10 indicators were used
Whose Deprivation Score exceeds 50? 70%?
(Look at the poorest of the poor)
MPI = 0.283
A = 52.7%
Lao and India have more severe poor. Lao has the most deprived in over 70%
Multidimensional Poverty Index (MPI)
Ecological Diversity and Resilience
Time - Use
Cultural Diversity and Resilience