Multidimensional Poverty Index

The Multidimensional Poverty Index (MPI) was developed in 2010 by Oxford Poverty & Human Development Initiative and the United Nations Development Programme^[1] and uses different factors to determine poverty beyond income-based lists. It replaced the previous Human Poverty Index. The global MPI is released annually by OPHI and the results published on its website.

The global Multidimensional Poverty Index (MPI) is an international measure of acute poverty covering over 100 developing countries. It complements traditional income-based poverty measures by capturing the severe deprivations that each person faces at the same time with respect to education, health and living standards. The MPI assesses poverty at the individual level. If someone is deprived in a third or more of ten (weighted) indicators, the global index identifies them as ‘MPI poor’, and the extent – or intensity – of their poverty is measured by the number of deprivations they are experiencing. The MPI can be used to create a comprehensive picture of people living in poverty, and permits comparisons both across countries, regions and the world and within countries by ethnic group, urban/rural location, as well as other key household and community characteristics.

This makes it invaluable as an analytical tool to identify the most vulnerable people - the poorest among the poor, revealing poverty patterns within countries and over time, enabling policy makers to target resources and design policies more effectively.

Indicators

The index uses the same three dimensions as the Human Development Index: health, education, and standard of living. These are measured using ten indicators.

Dimension	Indicators
Health	Child Mortality Nutrition
Education	Years of schooling School attendance
Living Standards	Cooking fuel Toilet Water Electricity Floor Assets

Each dimension and each indicator within a dimension is equally weighted.

Calculation of the index

Formula

The MPI is calculated as follows:^[2]

H: Percentage of people who are MPI poor (incidence of poverty)
A: Average intensity of MPI poverty across the poor (%)

Indicators used

The following ten indicators are used to calculate the MPI:^[3]

• Education (each indicator is weighted equally at 1/6)

• Health (each indicator is weighted equally at 1/6)

• Standard of Living (each indicator is weighted equally at 1/18)

A person is considered poor if they are deprived in at least a third of the weighted indicators. The intensity of poverty denotes the proportion of indicators in which they are deprived.

Real example

Niger:^[4]

• MPI = 0.642
• H = 0.927
• A = 0.693

In Niger, 92.7% of the country's population is MPI poor (they are deprived in at least 33.33% of the weighted indicators, by definition). Those who are MPI poor suffer from deprivation in 69.3% of indicators, on average.

Fictional example

Country X consists of persons A, B and C. The following table shows the deprivation on each of the 10 indicators for persons A, B and C.

"0%" indicates no deprivation in that indicator, while "100%" indicates deprivation in that indicator.

Indicator	Weight	Person A	Person B	Person C
1	1/6	0%	0%	0%
2	1/6	0%	0%	0%
3	1/6	100%	100%	0%
4	1/6	0%	100%	0%
5	1/18	0%	100%	100%
6	1/18	0%	100%	100%
7	1/18	0%	0%	100%
8	1/18	100%	100%	100%
9	1/18	100%	0%	100%
10	1/18	100%	0%	0%
Weighted score		33.33%	50.00%	27.78%
Status		MPI poor (≥ 33%)	MPI poor (≥ 33%)	Not MPI poor (< 33%)

Factor H for country X is:

Factor A for country X is:

Thus, the MPI for country X is:

Evaluation of MPI as a poverty Indicator

The MPI constitutes a sincere effort towards expansion as well as simplification of poverty estimation.

Comparison with HDI

HDI, the Human Development Index, was developed by Mahbub ul Haq and Amartya Sen, in 1990, and was also developed by the UNDP. It is calculated as the geometric mean of the normalized indices of the three dimensions of human development it takes into account: health, education and standard of living. The UNDP is trying to improve on the HDI formula by introducing the IHDI (Inequality affected HDI).

While both HDI and MPI use the 3 broad dimensions health, education and standard of living, HDI uses only single indicators for each dimension of poverty while MPI uses more than one indicator for each one. This, amongst other reasons, has led to the MPI only being calculated for 104 countries, where data is available for all these diverse indicators, while HDI is calculated for almost all countries.

However, though HDI is thus more universally applicable, its relative sparsity of indicators also makes it more susceptible to bias. Indeed some studies have found it to be somewhat biased towards GDP per capita, as demonstrated by a high correlation between HDI and the log of GDPpc. Hence, HDI has been criticized for ignoring other development parameters.

Comparison with other indicators

Both HDI and MPI have been criticized by economists such as Ratan Lal Basu for not taking "moral/emotional/spiritual dimensions" of poverty into consideration. It has been attempted to capture these additional factors by the "Global Happiness Index" in which a country like Bhutan (which has dismal performance on other indicators) has been ranked no. 1.

MPI in some developing countries

Country	MPI	% of People who are MPI Poor	Average Intensity of MPI Poverty	Number of MPI Poor People (thousands)	Year	% of People who are Income Poor ($1.25/day)	% of People who are Income Poor ($2.00/day)	Year
Albania	0.005	1.4	37.7	45	2009	0.6	4.3	2008
Angola	0.452	77.4	58.4	11,136	2001	54.3	70.2	2000
Argentina	0.011	3.0	37.7	1,160	2005	0.9	2.4	2009
Armenia	0.004	1.1	36.2	34	2005	1.3	12.4	2008
Azerbaijan	0.021	5.3	39.4	461	2006	1.0	7.8	2008
Bangladesh	0.292	57.8	50.4	83,207	2007	49.6	81.3	2005
Belarus	0.000	0.0	35.1	0	2005	0.1	0.2	2008
Belize	0.024	5.6	42.6	16	2006	12.4	24.5	1999
Benin	0.412	71.8	57.4	5,652	2006	47.3	75.3	2003
Bhutan	0.119	27.2	43.9	197	2010	26.2	49.5	2003
Bolivia	0.089	20.5	43.7	1,972	2008	13.6	25.1	2007
Bosnia and Herzegovina	0.003	0.8	37.2	30	2006	0.0	0.2	2007
Brazil	0.011	2.7	39.3	5,075	2006	3.8	9.9	2009
Burkina Faso	0.536	82.6	64.9	12,078	2006	56.5	81.2	2003
Burundi	0.530	84.5	62.7	6,127	2005	81.3	93.5	2006
Cambodia	0.251	52.0	48.4	6,946	2005	28.3	56.5	2007
Cameroon	0.287	53.3	53.9	9,149	2004	9.6	30.4	2007
Central African Republic	0.512	86.4	59.3	3,199	2000	62.8	80.1	2008
Chad	0.344	62.9	54.7	5,758	2003	61.9	83.3	2003
China	0.056	12.5	44.9	161,675	2003	15.9	36.3	2005
Colombia	0.022	5.4	40.9	2,500	2010	16.0	27.9	2006
Comoros	0.408	73.9	55.2	415	2000	46.1	65.0	2004
Cote d'Ivoire	0.353	61.5	57.4	11,083	2005	23.8	46.3	2008
Croatia	0.016	4.4	36.3	196	2003	0.1	0.1	2008
Czech Republic	0.010	3.1	33.4	316	2003	0.1	0.2	1996
Djibouti	0.139	29.3	47.3	241	2006	18.8	41.2	2002
Dominican Republic	0.018	4.6	39.4	438	2007	4.3	13.6	2007
Congo, Democratic Republic of the	0.393	73.2	53.7	44,485	2007	59.2	79.6	2006
Ecuador	0.009	2.2	41.6	286	2003	4.4	13.6	2009
Egypt	0.024	6.0	40.7	4,699	2008	2.0	18.5	2005
Estonia	0.026	7.2	36.5	97	2003	0.5	1.5	2004
Ethiopia	0.562	88.6	63.5	65,798	2005	39.0	77.6	2005
Gabon	0.161	35.4	45.5	437	2000	4.8	19.6	2005
Gambia	0.324	60.4	53.6	934	2006	34.3	56.7	2003
Georgia	0.003	0.8	35.2	36	2005	15.3	32.2	2008
Ghana	0.144	31.2	46.2	7,258	2008	30.0	53.6	2006
Guatemala	0.127	25.9	49.1	3,134	2003	11.7	24.3	2006
Guinea	0.506	82.5	61.3	7,459	2005	43.3	69.6	2007
Guyana	0.053	13.4	39.5	100	2005	8.7	18.0	1998
Haiti	0.299	56.4	53.0	5,346	2006	54.9	72.2	2001
Honduras	0.159	32.5	48.9	2,281	2006	23.3	35.4	2007
Hungary	0.016	4.6	34.3	466	2003	0.2	0.4	2007
India	0.283	53.7	52.7	612,203	2005	41.6	75.6	2005
Indonesia	0.095	20.8	45.9	48,352	2007	18.7	50.6	2009
Iraq	0.059	14.2	41.3	3,996	2006	4.0	25.3	2007
Jordan	0.008	2.4	34.4	145	2009	0.4	3.5	2006
Kazakhstan	0.002	0.6	36.9	92	2006	0.2	1.5	2007
Kenya	0.229	47.8	48.0	18,863	2009	19.7	39.9	2005
Kyrgyzstan	0.019	4.9	38.8	249	2006	1.9	29.4	2007
Laos	0.267	47.2	56.5	2,757	2006	33.9	66.0	2008
Latvia	0.006	1.6	37.9	37	2003	0.3	1.0	2004
Lesotho	0.156	35.3	44.1	759	2009	43.4	62.3	2003
Liberia	0.485	83.9	57.7	2,917	2007	83.7	94.8	2007
Macedonia	0.008	1.9	40.9	39	2005	0.3	4.3	2008
Madagascar	0.357	66.9	53.3	13,463	2009	67.8	89.6	2005
Malawi	0.381	72.1	52.8	8,993	2004	73.9	90.5	2004
Maldives	0.018	5.2	35.6	16	2009	1.5	12.2	2004
Mali	0.558	86.6	64.4	11,772	2006	51.4	77.1	2006
Mauritania	0.352	61.7	57.1	1,982	2007	21.2	44.1	2000
Mexico	0.015	4.0	38.9	4,313	2006	1.8	8.6	2008
Moldova	0.007	1.9	36.7	72	2005	1.9	12.5	2008
Mongolia	0.065	15.8	41.0	402	2005	22.4	49.1	2005
Montenegro	0.006	1.5	41.6	9	2005	0.1	0.2	2008
Morocco	0.048	10.6	45.3	3,287	2007	2.5	14.0	2007
Mozambique	0.512	79.3	64.6	18,127	2009	59.6	81.8	2008
Burma	0.154	31.8	48.3	14,297	2000
Namibia	0.187	39.6	47.2	855	2007	49.1	62.2	1993
Nepal	0.350	64.7	54.0	18,009	2006	24.82	57.25	2010
Nicaragua	0.128	28.0	45.7	1,538	2006	15.8	31.9	2005
Niger	0.642	92.4	69.4	12,437	2006	43.1	75.9	2007
Nigeria	0.310	54.1	57.3	81,510	2008	64.4	83.9	2004
Occupied Palestinian Territories	0.005	1.4	37.3	52	2007
Pakistan	0.264	49.4	53.4	81,236	2007	22.6	61.0	2006
Paraguay	0.064	13.3	48.5	755	2003	5.1	13.2	2008
Peru	0.086	19.9	43.2	5,421	2004	5.9	14.7	2009
Philippines	0.064	13.4	47.4	12,083	2008	22.6	45.0	2006
Congo, Republic of the	0.208	40.6	51.2	1,600	2009	54.1	74.4	2005
Russia	0.005	1.3	38.9	1,883	2003	0.0	0.1	2008
Rwanda	0.426	80.2	53.2	7,380	2005	76.8	89.6	2005
São Tomé and Príncipe	0.154	34.5	44.7	56	2009	29.7	55.9	2001
Senegal	0.384	66.9	57.4	7,273	2005	33.5	60.4	2005
Serbia	0.003	0.8	40.0	79	2005	0.1	0.7	2008
Sierra Leone	0.439	77.0	57.0	4,321	2008	53.4	76.1	2003
Slovakia	0.000	0.0	0.0	0	2003	0.3	1.4	1996
Somalia	0.514	81.2	63.3	6,940	2006
South Africa	0.057	13.4	42.3	6,609	2008	17.4	35.7	2006
Sri Lanka	0.021	5.3	38.7	1,027	2003	7.0	29.1	2007
Suriname	0.039	8.2	47.2	41	2006	15.5	27.2	1999
Swaziland	0.184	41.4	44.5	469	2007	62.9	81.0	2001
Syria	0.021	5.5	37.5	1,041	2006	1.7	16.9	2004
Tajikistan	0.068	17.1	40.0	1,103	2005	21.5	50.9	2004
Tanzania	0.367	65.2	56.3	27,559	2008	67.9	87.9	2007
Thailand	0.006	1.6	38.5	1,067	2005	0.4	11.5	2004
East Timor	0.360	68.1	52.9	749	2009	37.4	72.8	2007
Togo	0.284	54.3	52.4	3,003	2006	38.7	69.3	2006
Trinidad and Tobago	0.020	5.6	35.1	74	2006	4.2	13.5	1992
Tunisia	0.010	2.8	37.1	272	2003	2.6	12.8	2000
Turkey	0.028	6.6	42.0	4,378	2003	2.7	9.1	2005
Uganda	0.367	72.3	50.7	21,235	2006	37.7	64.5	2009
Ukraine	0.008	2.2	35.5	1,018	2007	0.0	0.1	2008
United Arab Emirates	0.002	0.6	35.3	20	2003
Uruguay	0.006	1.7	34.7	56	2003	0.0	0.2	2009
Uzbekistan	0.008	2.3	36.2	603	2006	46.3	76.7	2003
Vanuatu	0.129	30.1	42.7	67	2007
Vietnam	0.084	17.7	47.2	14,249	2002	13.1	38.5	2008
Yemen	0.283	52.5	53.9	11,176	2006	17.5	46.6	2005
Zambia	0.328	64.2	51.2	7,739	2007	64.3	81.5	2004
Zimbabwe	0.180	39.7	45.3	4,974	2006

Source: Alkire, S. Roche, JM. Santos, ME. and Seth, S (November 2011) http://ophi.qeh.ox.ac.uk . Multidimensional Poverty Index: 2011 Data. Oxford Poverty and Human Development Initiative. Available at: www.ophi.org.uk/policy/multidimensional-poverty-index/.

See also

• Human Development Index

References