1. Multidimensional Poverty Index Human Development Report Office
Multidimensional Poverty Index
Milorad Kovacevic
Human Development Report Office

2. Multidimensional Poverty Index
The dimensions of poverty go far beyond inadequate income—to
poor health and nutrition,
low education and skills,
inadequate livelihoods,
bad housing conditions,
social exclusion and lack of participation
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

3. Multidimensional Poverty Index
HDR 2010, in collaboration with Oxford University’s Poverty and Human Development Initiative, introduced a new Multidimensional Poverty Index (MPI)
only for 104 developing countries (due to lack of comparable data)
The 104 countries include 92% of the population in 98 developing countries
in 2011 – at most 120
The MPI is an index of acute multidimensional poverty and is meant to complement monetary based measures
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

4. Dimensions of the Multidimensional Poverty Index
MPI identifies overlapping deprivations at the household level
Composed of 10 indicators corresponding to the same 3 dimensions as the HDI: Health, Education and Living Standards
- Each dimension is equally weighted
- Each indicator has equal weight within its dimension

5. Dimensions of the Multidimensional Poverty Index
The MPI shows the average number of poor people and the average number of deprivations with which poor households contend
A household is multidimensionally poor if it is deprived in at least 30% of the weighted indicators (2 to 6 indicators)
The MPI reveals a different pattern of poverty than income poverty
it illuminates a different set of deprivations
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

6. Data Sources Demographic & Health Surveys (DHS – 48 countries)
Data: Household Surveys
Demographic & Health Surveys (DHS – 48 countries)
Multiple Indicator Cluster Surveys (MICS – 35 countries)
World Health Survey (WHS – 19 countries)
Additionally used 2 special surveys covering Mexico and urban Argentina
WHS 2003 for United Arab Emirates
MPI is deeply affected by lack of comparable data
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

7. Methodology
MPI corresponds to the first measure of the Alkire & Foster (2007) family of multidimensional poverty measures, called M0
It is constructed using the AF method:
H is the percentage of people who are poor - shows the incidence of multidimensional poverty: (H=q/n)
A is the average proportion of weighted deprivations people suffer at the same time - shows the intensity of multidimensional poverty: 𝑨=[ 𝟏 𝒒 𝑪 𝒊 /𝟏𝟎]/𝒒
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

8. Methodology
Two step procedure applied to identify who is multidimensionally poor, uses dual cutoff method:
Identify all individuals deprived in any dimension
Within dimension cutoff
Identify who is multidimensionally poor
Cross dimensional cutoff
Deprived in at least 30% of the weighted indicators
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

9. Measurement Indicators and Cutoffs
Health (each indicator weighted equally at 1/6 )
Child Mortality: If any child has died in the family
Malnutrition: If any interviewed adult in the family has low Body Mass Index; if any child is more than 2 standard deviations below the reference normal weight for age, (WHO standards)
[WHS has male data but no child data; MICS has child data but no adult data]
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

10. Measurement Indicators and Cutoffs
Education (each indicator weighted equally at 1/6 )
- Years of Schooling: if no person in the household has completed 5 years of schooling
- Child Enrolment: if any school-aged child is out of school, where school-aged is an 8 year period from the national starting age
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

11. Measurement Indicators and Cutoffs
Standard of Living (each indicator weighted equally at 1/18)
- Electricity (no electricity is poor)
- Drinking water (MDG definitions)
- Sanitation (MDG definitions + not shared)
- Flooring (dirt/sand/dung are poor)
- Cooking Fuel (wood/charcoal/dung are poor)
- Assets (poor if do not own a car/truck and do not own more than one of these: radio, tv, telephone, bike, motorbike, or refrigerator)
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

12. Illustration
Ali’s household is deprived in nutrition and child enrolment. Is Ali’s household multidimensionally poor?
10(1/6)+10(1/6) = 3.34 (> 3) Yes
Maira’s household is deprived in electricity, water, sanitation, and has a dirt floor. Is Ali’s household multidimensionally poor?
10(1/18)+10(1/18) + 10(1/18)+10(1/18) = 2.20 (<3) No
Tom’s household is deprived in years schooling, sanitation, assets, and cooking fuel. Is Tom’s household multidimensionally poor?
10(1/6)+ 10(1/18)+10(1/18) + 10(1/18)= 3.33 (>3) Yes
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

13. Missing Dimensions Missing dimensions include: Work Empowerment
Safety from Violence (crime, conflict)
Political Freedom
Relationships (social capital, inclusion, dignity)
(Cultural/Spiritual/Subjective Well-being)
Data are not available to incorporate any of these into the MPI for 100+ countries
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

14. Patterns of Multidimensional Poverty
32% the population in 104 developing countries, about 1.75 billion people, are MPI poor
The 104 countries includes 92% of the population in 98 developing countries
Regional rates vary from 3% in Europe and Central Asia to 65% in sub-Saharan Africa
South Asia is home to the largest number of MPI poor, followed by sub-Saharan Africa
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

15. Patterns of Multidimensional Poverty
Half the world’s MPI poor live in South Asia, but the intensity of MPI poor is highest in sub-Saharan Africa
Eight Indian states are home to 421 million MPI poor people - more than the 410 million poor living in the 26 poorest African countries combined
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

16. Patterns of Multidimensional Poverty
Countries with higher multidimensional poverty headcounts tend to have more deprivations
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

17. Patterns of Multidimensional Poverty
South Asia has highest incidence of multidimensional poverty in the world-ranging from 38.7% in Sri Lanka to 54.1% in Nepal
Sub-Saharan Africa has significant variation–ranging from 3% in South Africa to 93% in Niger
East Asia and the Pacific has relatively low rates of multidimensional
poverty– but over half of Cambodians are MPI poor
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

18. Patterns of Multidimensional Poverty
Europe and Central Asia’s incidence of Multidimensional poverty is lowest of the developing country regions – close to zero in several countries, while Tajikistan is the highest with 17%
Arab states MPI values are generally below 7%, but as high as 52% in Yemen and 81% in Somalia
Latin America and Caribbean MPI values range from 2% (Uruguay) to 57% (Haiti)
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

19. Patterns of Multidimensional Poverty
United Arab Emirates (WHS 2003)
MPI H A
@ Risk (1)
At least one severe deprivation
Education
Health
Living Standard
0.002
0.6%
35.3%
2.0%
5.4%
0.0%
(1) Suffering in 20% of weighted indicators
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

20. Patterns of Multidimensional Poverty
The MPI highlights significant variations:
Within-countries
Nairobi is similar to Dominican Republic, rural northeast is worse than Niger
Among ethnicities, religions and castes
MPI headcount in Kenya ranged from 29% for the Embu to 96% for the Turkana and Masai
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

21. Changes Over Time
MPI at two points in time in Bangladesh, Ethiopia and Ghana
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

22. Relevance to Country Level Work
Can be adapted using indicators and weights that make sense for the region or the country
Can be adopted for national poverty eradication programs
It can be used to study changes over time
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

23. Policy Applications Allocate resources effectively Show impacts
Target those with the greatest intensity of poverty
Identify interconnections among deprivations
Helps in addressing MDGs strategically
Design policy
Show which deprivations are most common in different groups so that policies can be tailored to particular needs
Show impacts
Reflects results of policy interventions quickly
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

24. Limitations of the Multidimensional Poverty Index
Drawbacks mainly due to data constraints
Indicators include inputs, outputs and one stock indicator because flow data unavailable in some instances
Health data relatively weak
Judgments necessary where data is missing
Intrahousehold inequality is not captured
Does not measure inequality amongst the poor
Cross-country comparability limited
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011

25. Criticism of the Multidimensional Poverty Index
Martin Ravallion’s recent criticism:
Arbitrariness of components and weights.
Income based measures aggregate consumption across a large number of goods.
Limited information about trade-offs.
Uncertainty about robustness of resulting rankings.
Responses
Giving income weight of one is no less arbitrary.
Prices reflect scarcities and current distribution.
Indices can and should enable reasoned public debate about the implicit weights and trade-offs.
Contention of HDR approach is that since education and health are public goods, current prices underestimate their social value.
MPI background research exhaustively evaluated robustness
Workshop on HD Approach and Measurement for the GCC States, Doha, 9-11 May, 2011