Multidimensional poverty index – Wikipedia

L’ Multidimensional poverty index (IPM) ^{[ first ]}, in English Multidimensional Poverty Index (MPI), also translated Multidimensional poverty index , is a statistical index evaluating poverty in developing countries, created by a department of the University of Oxford in 2010 and used by the United Nations Development Program (UNDP) for its human development report October 2010 .

Poverty measurement is most often based on a single essential indicator, income (for example the poverty line: $ 1.25 per day). This approach to poverty provides only partial image of it, hence the work of Sabina Alkire and Maria Emma Santos of Ophi ( Oxford Poverty & Human Development Initiative (in) ) who worked from ten poverty indicators at the same time, hence its “multidimensional” character:

infantile mortality (if a child died in the family);
nutrition (if a family member is in malnutrition);
years of schooling (if no member has been five years in school);
The school exit (if one of the children left school before 8 years old);
electricity (if the home does not have electricity);
drinking water (if there are not less than 30 minutes of walking);
sanitary facilities (if there are none or share with others);
Habitat soil (if the soil is covered by mud, sand or manure);
the fuel used to cook (if it’s wood, charcoal or dung);
movable property (if not more than one of them: radio, television, telephone, bicycle or motorcycle).

The index is interested in households, counting the deprivation which affects them in the fields of health, education and standard of living. The statistics used to calculate the 2010 index are not all of the same year, ranging from 2003 to 2007. The update of the index in 2014 uses data dating back to the worst of 2005, at best from 2012. The index is calculated according to the following formula ^{[ 2 ]}:

after-content-x4

{displaystyle IPM=Htimes A}

${displaystyle IPM=Htimes A}$

“H” designates the percentage of people who are poor according to the definition of the IPM , while “A” means the intensity of this poverty (the percentage of indicators of the IPM which are concerned on average). A person living in multidimensional poverty lives “With at least 33 percent of the indicators reflecting acute deprivation in the fields of health, education and standard of living” ^{[ first ]}.

Statistical work covers 104 developing countries (37 of sub -Saharan Africa, 24 in Europe/CEI, 18 from Latin America/Caribbean, 11 of the Arab world, 9 of East/Pacific Asia and 5 D ‘Southern Asia), populated by 5.2 billion inhabitants in 2007 (78% of the world’s population). Among them: 1 billion 659 million humans are considered by the multidimensional poverty index as poor, the poorest of the poor in the world.

If the countries of sub -Saharan Africa are very numerous in the bottom of the ranking (27% of the poor on the planet within the meaning of the MPI), South Asia concentrates 51% of the poor in the world (for 29.5% of the population developing countries). The distribution of the poor is done as follows:

The index of multidimensional poverty is therefore added to other tools for measuring the inequalities used by the UN to meet the millennium objectives: the gross domestic product per capita (GDP/Hab.), The Human Development Index (IDH ) and the index of human poverty (IPH).

Classification of countries according to the IPM
Pays	IPM 2007 ^{[ 3 ]}	Names of Poor 2007	Share of the poor in The 2007 population	IPM 2014 ^{[ 4 ]}	Names of poor (year)	Share of the poor in the population (year)
Niger	0.64	6 600 000	84.5%	0.605	15 416 000 (2012)	89.3% (2012)
Ethiopia	0.58	70 700 000	90%	0.564	78 070 000 (2011)	87.3% (2011)
Had to	0.56	10 800 000	87.1%	0.457	11 883 000 (2012)	77.7% (2012)
Burkina Faso	0.54	12 100 000	82.6%	0.535	13 054 000 (2010)	84% (2010)
Burundi	0.53	6 600 000	84.5%	0.454	7 458 000 (2010)	80.8% (2010)
Somalia	0.51	7 100 000	81.2%	0.514	7 051 000 (2006)	81.2% (2006)
Central African Republic	0.51	3 700 000	86.4%	0.430	3 374 000 (2010)	77.6% (2010)
Guinea	0.5	7 900 000	82.4%	0.459	8 602 000 (2012)	75.1% (2012)
Sierra Leone	0.49	4 400 000	81.5%	0.464	4 935 000 (2013)	81.0% (2013)
Guinea-Bissau	?	?	?	0.462	1 126 000 (2006)	77.5% (2006)
Mozambique	0.48	17 500 000	79.8%	0.389	17 109 000 (2011)	69.6% (2011)
Liberia	0.48	3 000 000	83.9%	0.374	3 059 000 (2013)	71.2% (2013)
Uganda	?	?	?	0.367	24 576 000 (2011)	69.9% (2011)
Timor oriental	?	?	?	0.360	735 000 (2009)	68.1% (2009)
Afghanistan	?	?	?	0.353	19 256 000 (2010)	66.2% (2010)
Maurice	?	?	?	0.352	2 054 000 (2007)	61.7% (2007)
Angola	0.45	13 600 000	77.4%	?	?	?
Rwanda	0.44	7 700 000	81.4%	0.350	7 472 000 (2010)	69.0% (2010)
Madagascar	0.41	13 100 000	70.5%	0.357	13 707 000 (2008)	66.9% (2008)
Benign	0.41	6 000 000	72%	0.307	6 253 000 (2011)	62.2% (2011)
Comoros	0.41	440 000	73.9%
Democratic Republic of Congo	0.39	45 700 000	73.2%	0.401	50 696 000 (2013)	75.1% (2013)
Flame	0.38	10 400 000	72.3%	0.334	10 008 000 (2010)	66.7% (2010)
Senegal	0.38	8 000 000	66.9%	0.332	8 455 000 (2012)	59.8% (2012)
Nigeria	0.37	93 800 000	63.5%	0.303	92 448 000 (2013)	53.2% (2013)
Tanzania	0.37	27 000 000	65.3%	0.332	29 484 000 (2010)	65.6% (2010)
Mauritania	0.35	1 900 000	61.7%
Nepal	0.35	18 300 000	64.7%	0.217	12 003 000 (2011)	44.2% (2011)
Chad	0.34	6 700 000	62.9%	0.554	10 223 000 (2010)	87.2% (2010)
Zambia	0.33	7 800 000	63.7%	0.328	7 770 000 (2007)	64.2% (2007)
Gambia	0.32	970 000	60.4%	0.324	896 000 (2005)	60.4% (2005)
Ivory Coast	0.32	10 500 000	52.2%	0.310	11 655 000 (2011)	58.7% (2011)
Haiti	0.31	5 600 000	57.3%	0.248	5 026 000 (2012)	49.4% (2012)
Kenya	0.3	22 800 000	60.4%	0.229	19 040 000 (2008)	47.8% (2008)
Cameroon	0.3	10 200 000	54.6%	0.248	9 736 000 (2011)	46.0% (2011)
Inside	0.3	645 000 000	55.4%	0.283	614 489 000 (2005)	53.7% (2005)
Bangladesh	0.29	91 200 000	57.8%	0.253	78 385 000 (2011)	51.3% (2011)
Togo	0.28	3 400 000	54.3%	0.250	3 139 000 (2010)	49.8% (2010)
Yemen	0.28	11 700 000	52.5%	0.283	10 850 000 (2006)	52.5% (2006)
Pakistan	0.28	88 300 000	51%	0.230	80 461 000 (2012)	44.2% (2012)
Laos	0.27	2 900 000	47.2%
Cambodia	0.26	7 700 000	53.9%	0.212	6 593 000 (2010)	45.9% (2010)
Sao Tome and Principe	0.24	100 000	51.6%
Lesotho	0.22	960 000	48.1%
Nicaragua	0.21	2 300 000	40.7%
Republic of Congo	0.21	1 600 000	40.6%	0.181	1 722 000 (2011)	39.7% (2011)
Namibia	0.19	830 000	39.8%	0.187	823 000 (2006)	39.6% (2006)
In the tattoo / Swaziland	0.18	490 000	41.1%
Bolivia	0.18	3 400 000	36.3%
Zimbabwe	0.17	4 800 000	38.5%
Gabon	0.16	500 000	35.4%
Honduras	0.16	2 300 000	32.8%
Ghana	0.14	6 900 000	30.1%
Morocco	0.14	8 900 000	28.5%
Djibouti	0.14	230 000	47.3%
Guatemala	0.13	3 500 000	25.9%
Indonesia	0.1	46 700 000	20.8%
Burma	0.09	7 000 000	14.2%
Peru	0.09	5 600 000	19.8%
Vietnam	0.08	12 300 000	14.3%
Tadjikistan	0.07	1 100 000	17.1%
Philippines	0.07	11 200 000	12.6%
Mongolia	0.06	410 000	15.8%
Paraguay	0.06	810 000	13.3%
Iraq	0.06	4 200 000	14.2%
China	0.06	165 800 000	12.5%	0.056	161 573 000 (2002)	12.5% (2002)
Guyana	0.05	110 000	13.8%
Dominican Republic	0.05	1 100 000	11.1%
Suriname	0.04	40 000	7.5%
Colombia	0.04	4 100 000	9.2%
Brazil	0.04	16 200 000	8.5%
Türkiye	0.04	6 200 000	8.5%
Estonia	0.03	90 000	7.2%
Egypt	0.03	5 100 000	6.4%
Belize	0.02	20 000	5.6%
Syria	0.02	1 100 000	5.5%
Azerbaijan	0.02	460 000	5.4%
Sri Lanka	0.02	1 100 000	5.3%
Trinity and Tobago	0.02	70 000	5.6%
Kyrgyzstan	0.02	260 000	4.9%
Mexico	0.02	4 300 000	4%
South Africa	0.01	1 500 000	3.1%
Argentine	0.01	1 200 000	3%
Tunisia	0.01	280 000	2.8%
Jordan	0.01	160 000	2.7%
Equator	0.01	290 000	2.2%
Uzbekistan	0.01	620 000	2.3%
Moldova	0.01	80 000	2.2%
Armenia	0.01	70 000	2.3%
Fruit salad	0.01	40 000	1.9%
Ukraine	0.01	10 100 000	2.2%
Croatia	0.01	70 000	1.6%
Montenegro	0.01	10 000	1.5%
Thailand	0.01	1 100 000	1.6%
Uruguay	0.01	60 000	1.7%
Russia	0.005	1 800 000	1.3%
Albania	0.004	30 000	0.96%
Serbia	0.003	80 000	0.83%
Bosnia and Herzegovina	0.003	30 000	0.81%
Hungary	0.003	80 000	0.76%
Georgia	0.003	40 000	0.8%
Palestinian territories	0.003	30 000	0.69%
Kazakhstan	0.002	90 000	0.59%
United Arab Emirates	0.002	30 000	0.57%
Latvia	0.001	10 000	0.3%