Data

Intensity of multidimensional poverty

Harmonized over time
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What you should know about this indicator

  • Being in multidimensional poverty means that a person lives in a household deprived in a third or more of ten indicators, grouped into three dimensions of well-being: health (using two indicators: nutrition, child mortality), education (using two indicators: years of schooling, school attendance), and living standards (using six indicators: cooking fuel, sanitation, drinking water, electricity, housing, assets).
  • Each household is assessed against specific thresholds for these indicators. For example, a household is considered deprived in the electricity indicator if it does not have access to it. This article discusses specific thresholds in more detail.
  • The intensity of multidimensional poverty is calculated as the average share of indicators in which those counted as MPI poor are deprived.
  • Each indicator contributes to one of the three dimensions of well-being. Health and education indicators are weighted more (1/6 each) than living standards indicators (1/18 each) so that all three dimensions contribute equally to the overall measure.
  • This indicator is a harmonized over time (HOT) estimate. This harmonization seeks to make two or more MPI estimates comparable by aligning the indicator definitions in each survey. Look for the current margin estimate (CME) to see the most recent survey data.
Learn more in the FAQs

The global MPI is a measure of acute poverty covering over 100 countries in the developing regions of the world. This measure is based on the dual-cutoff counting approach to poverty developed by Alkire and Foster (2011). The global MPI was developed in 2010 by Alkire and Santos (2014, 2010) in collaboration with the UNDP’s Human Development Report Office (HDRO). Since its inception, the global MPI has used information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. These dimensions are the same as those used in the UNDP’s Human Development Index.

In 2018, the first major revision of the global MPI was undertaken, considering improvements in survey microdata and better align to the 2030 development agenda insofar as possible (Alkire and Jahan, 2018; OPHI, 2018). The revision consisted of adjustments in the definition of five out of the ten indicators, namely child mortality, nutrition, years of schooling, housing and assets. Alkire, Kanagaratnam, Nogales and Suppa (2022) provide a comprehensive analysis of the consequences of the 2018 revision. The normative and empirical decisions that underlie the revision of the global MPI, and adjustments related to the child mortality, nutrition, years of schooling and housing indicators are discussed in Alkire and Kanagaratnam (2021). The revision of assets indicator is detailed in Vollmer and Alkire (2022).

The global MPI begins by establishing a deprivation profile for each person, showing which of the 10 indicators they are deprived in. Each person is identified as deprived or non-deprived in each indicator based on a deprivation cutoff. In the case of health and education, each household member may be identified as deprived or not deprived according to available information for other household members. For example, if any household member for whom data exist is undernourished, each person in that household is considered deprived in nutrition. Taking this approach – which was required by the data – does not reveal intrahousehold disparities, but is intuitive and assumes shared positive (or negative) effects of achieving (or not achieving) certain outcomes. Next, looking across indicators, each person’s deprivation score is constructed by adding up the weights of the indicators in which they are deprived. The indicators use a nested weight structure: equal weights across dimensions and an equal weight for each indicator within a dimension. The normalised indicator weight structure of the global MPI means that the living standard indicators receive lower weight than health and education related indicators because from a policy perspective, each of the three dimensions is of roughly equal normative importance.

In the global MPI, a person is identified as multidimensionally poor or MPI poor if they are deprived in at least one-third of the weighted MPI indicators. In other words, a person is MPI poor if the person’s deprivation score is equal to or higher than the poverty cutoff of 33.33 percent. After the poverty identification step, we aggregate across individuals to obtain the incidence of poverty or headcount ratio (H) which represents the percentage of poor people in the population. We then compute the intensity of poverty (A), representing the average percentage of weighted deprivations experienced by the poor. We then compute the adjusted poverty headcount ratio (M0) or MPI by combining H and A in a multiplicative form (MPI = H x A).

Both the incidence and the intensity of these deprivations are highly relevant pieces of information for poverty measurement. The incidence of poverty is intuitive and understandable by anyone. People always want to know how many poor people there are in a society as a proportion of the whole population. Media tend to pick up on the incidence of poverty easily. Yet, the proportion of poor people as the headline figure is not enough (Alkire, Oldiges and Kanagaratnam, 2021).

A headcount ratio is also estimated using two other poverty cutoffs. The global MPI identifies individuals as vulnerable to poverty if they are close to the one-third threshold, that is, if they are deprived in 20 to 33.32 percent of weighted indicators. The tables also apply a higher poverty cutoff to identify those in severe poverty, meaning those deprived in 50 percent or more of the dimensions.

The AF methodology has a property that makes the global MPI even more useful—dimensional breakdown. This property makes it possible to consistently compute the percentage of the population who are multidimensionally poor and simultaneously deprived in each indicator. This is known as the censored headcount ratio of an indicator. The weighted sum of censored headcount ratios of all MPI indicators is equal to the MPI value.

The censored headcount ratio shows the extent of deprivations among the poor but does not reflect the weights or relative values of the indicators. Two indicators may have the same censored headcount ratios but different contributions to overall poverty, because the contribution depends both on the censored headcount ratio and on the weight assigned to each indicator. As such, a complementary analysis to the censored headcount ratio is the percentage contribution of each indicator to overall multidimensional poverty.

Intensity of multidimensional poverty
Harmonized over time
Multidimensional poverty is defined as being deprived in a range of health, education and living standards indicators. The intensity is the share of indicators in which people in multidimensional poverty are deprived on average.
Source
Alkire, Kanagaratnam and Suppa (2024) - The Global Multidimensional Poverty Index (MPI) 2024 – with minor processing by Our World in Data
Last updated
October 28, 2024
Next expected update
October 2025
Date range
2001–2023
Unit
%

Frequently Asked Questions

How is multidimensional poverty defined in the MPI?

Multidimensional poverty refers to a way of understanding and measuring poverty that goes beyond income or consumption levels. It captures the many ways in which people experience deprivation.

The Oxford Poverty and Human Development Initiative (OPHI) defines multidimensional poverty through the Multidimensional Poverty Index (MPI). The MPI uses 10 indicators grouped into three dimensions: health, education, and living standards. A person is considered to be living in multidimensional poverty (MPI poor) if they are deprived in at least one-third of these weighted indicators.

The indicators are not equally weighted. “Health” and “education” indicators each contribute 1/6 to the total, while “living standards” indicators contribute 1/18 each. This ensures the three dimensions are equally represented in the overall measure.

Which sources does OPHI use to produce global estimates of multidimensional poverty?

OPHI calculates the Multidimensional Poverty Index (MPI) using data from large-scale household surveys, primarily the Demographic and Health Survey (DHS), the Multiple Indicators Cluster Survey (MICS), and other national surveys when recent data from these two sources is not available.

These surveys include detailed information about households, covering questions about nutrition, school attendance, sanitation, and access to clean drinking water. Each household is assessed against specific deprivation thresholds for all 10 indicators. If a household falls short in a third or more of the weighted indicators, it is classified as multidimensionally poor, and all its members are also considered poor.

What if not all indicators are available for a country?

Not all countries have recent and comparable data for all ten indicators. When data for some indicators is missing from the survey data, those indicators are excluded from the calculation of the MPI, and the weights of remaining indicators are proportionally adjusted to maintain equal weights across the three dimensions (health, education, living standards).

MPI estimates are only calculated for a country where:

  • at least one “health” and one “education” indicator is available
  • at least four indicators in “living standards” are available

How comparable is the MPI data across time or between countries?

MPI data can be compared by using harmonized indicators across countries and time. However, challenges arise due to variations in survey designs, timing, and indicator availability.

For international comparisons using the latest available survey data, OPHI provides current margin estimates (CME), which apply consistent definitions and thresholds across all countries. This means that only one figure is given per country, based on the most recent information available.

To compare data across time within a country, OPHI provides harmonized over time (HOT) estimates that focus only on indicators consistently available in all surveyed years.

Are there other sources of multidimensional poverty data?

Yes, there are other sources of multidimensional poverty data besides OPHI’s global MPI. The World Bank produces the Multidimensional Poverty Measure (MPM), which incorporates extreme poverty as one of its dimensions, combining monetary and non-monetary indicators into a single measure. In addition, many countries have developed their own national multidimensional poverty indices, tailored to their specific contexts and priorities, often as part of their regular poverty monitoring systems.

Sources and processing

This data is based on the following sources

The global Multidimensional Poverty Index (MPI) is an international measure of acute multidimensional poverty covering over 100 developing countries. It complements traditional monetary poverty measures by capturing the acute deprivations in health, education, and living standards that a person faces simultaneously.

The MPI assesses poverty at the individual level. If a person is deprived in a third or more of ten (weighted) indicators, the global MPI identifies them as ‘MPI poor’. The extent – or intensity – of their poverty is also measured through the percentage of deprivations they are experiencing.

The global MPI shows who is poor and how they are poor and can be used to create a comprehensive picture of people living in poverty. It permits comparisons both across countries and world regions, and within countries by ethnic group, urban/rural area, subnational region, and age group, as well as other key household and community characteristics. For each group and for countries as a whole, the composition of MPI by each of the ten indicators shows how people are poor.

This makes the MPI and its linked information platform 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.

The global MPI was developed by OPHI with the UN Development Programme (UNDP) for inclusion in UNDP’s flagship Human Development Report in 2010. It has been published annually by OPHI and in the HDRs ever since.

Retrieved on
October 28, 2024
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
  • Alkire, S., Kanagaratnam, U., and Suppa, N. (2024). The Global Multidimensional Poverty Index (MPI) 2024. Country Results and Methodological Note. OPHI MPI Methodological Note 58, Oxford Poverty and Human Development Initiative, University of Oxford.
  • Alkire, S., Kanagaratnam, U., and Suppa, N. (2024). The Global Multidimensional Poverty Index (MPI) 2024. Disaggregation Results and Methodological Note. OPHI MPI Methodological Note 59, Oxford Poverty and Human Development Initiative, University of Oxford.

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“Data Page: Intensity of multidimensional poverty”, part of the following publication: Joe Hasell, Max Roser, Esteban Ortiz-Ospina and Pablo Arriagada (2022) - “Poverty”. Data adapted from Alkire, Kanagaratnam and Suppa. Retrieved from https://ourworldindata.org/grapher/intensity-of-multidimensional-poverty-hot [online resource]
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Alkire, Kanagaratnam and Suppa (2024) - The Global Multidimensional Poverty Index (MPI) 2024 – with minor processing by Our World in Data

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Alkire, Kanagaratnam and Suppa (2024) - The Global Multidimensional Poverty Index (MPI) 2024 – with minor processing by Our World in Data. “Intensity of multidimensional poverty – Harmonized over time” [dataset]. Alkire, Kanagaratnam and Suppa, “Global Multidimensional Poverty Index (MPI) 2024” [original data]. Retrieved December 6, 2024 from https://ourworldindata.org/grapher/intensity-of-multidimensional-poverty-hot