Multidimensional Poverty Index

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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 MPI is an index of acute multidimensional poverty. It shows the number of people who are multidimensionally poor (suffering deprivations in 33.33% of weighted indicators) and the number of deprivations with which poor households typically contend. It reflects deprivations in very rudimentary services and core human functioning for people across 104 countries. Although deeply constrained by data limitations, MPI reveals a different pattern of poverty than income poverty, as it illuminates a different set of deprivations.

Indicators[edit]

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 school
  • Children enrolled
Living Standards
  • Cooking fuel
  • Toilet
  • Water
  • Electricity
  • Floor
  • Assets

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

Calculation of the index[edit]

Formula[edit]

The MPI is calculated as follows:[2]

MPI = H \times A

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

Indicators used[edit]

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

  • Education (each indicator is weighted equally at 1/6)
  1. Years of schooling: deprived if no household member has completed five years of schooling
  2. Child school attendance: deprived if any school-aged child is not attending school up to class 8
  • Health (each indicator is weighted equally at 1/6)
  1. Child mortality: deprived if any child has died in the family
  2. Nutrition: deprived if any adult or child for whom there is nutritional information is malnourished
  • Standard of Living (each indicator is weighted equally at 1/18)
  1. Electricity: deprived if the household has no electricity
  2. Sanitation: deprived if the household’s sanitation facility is not improved (according to MDG guidelines), or it is improved but shared with other households
  3. Drinking water: deprived if the household does not have access to safe drinking water (according to MDG guidelines) or safe drinking water is more than a 30-minute walk from home roundtrip
  4. Floor: deprived if the household has a dirt, sand or dung floor
  5. Cooking fuel: deprived if the household cooks with dung, wood or charcoal
  6. Assets ownership: deprived if the household does not own more than one radio, TV, telephone, bike, motorbike or refrigerator and does not own a car or truck

A person is considered poor if they are deprived in at least 33.33% of the weighted indicators. The intensity of poverty denotes the proportion of indicators in which they are deprived.

Real example[edit]

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[edit]

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:

\frac {1 + 1 + 0}{3} = 0.667

Factor A for country X is:

\frac {33.33\% + 50.00\%} {2} = 0.417

Thus, the MPI for country X is:

0.667 \times 0.417 = 0.278

Evaluation of MPI as a poverty Indicator[edit]

It is a sincere effort towards expansion as well as simplification of poverty estimation.

Comparison with HDI HDI was developed by Mahbub ul Haq and Amartya Sen, in 1990, and was also developed by UNDP. The UNDP is trying to improve on the HDI formula by introducing the IHDI (Inequality affected HDI).

Similarities with HDI Both HDI and MPI use the 3 broad dimensions 1. Health 2. Education 3. Standard of living

Differences with HDI HDI uses only single indicators for each dimension of Poverty while MPI uses more than 1 indicator for each dimension of poverty.

HDI = Geometric mean of (Normalized Indices of 3 dimensions)

HDI is calculated for almost all the countries, while MPI is calculated for only 104 countries.

HDI is somewhat biased towards the GDP per capita, as has been demonstrated by some studies which found high correlation between HDI and log of GDP per capita. Hence, HDI has been criticized as the other development parameters were being ignored.

Both HDI and MPI has been criticized by economist such as Ratan Lal Basu for lack of "Moral/Emotional/Spiritual Dimensions" of poverty. The same has been captured by "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[edit]

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[edit]

References[edit]

  1. ^ "A wealth of data. A useful new way to capture the many aspects of poverty". The Economist. July 29, 2010. Retrieved 2010-08-04. "Aided by the improved availability of survey data about living conditions for households in over 100 developing countries, the researchers have come up with a new index, called the Multidimensional Poverty Index (MPI), which the United Nations Development Programme (UNDP) will use in its next “Human Development Report” in October." 
  2. ^ http://www.ophi.org.uk/wp-content/uploads/Argentina.pdf
  3. ^ Alkire Roche Santos Seth. "Multidimensional Poverty Index 2011: Brief Methodological Note". Oxford Poverty & Human Development Initiative (OPHI). 
  4. ^ http://www.ophi.org.uk/wp-content/uploads/Niger.pdf