Global MPI 2018 Frequently Asked Questions
- What is new in the MPI 2018? Why have some of the indicators been changed?
- What are the new thresholds for each indicator?
- Why was the original MPI modified?
- Do the new methodological changes affect the ranking of countries?
- Are the changes in India’s poverty rate due to methodological modifications?
- What are the data sources used in the MPI2018?
- Is it possible to compare the MPI2018 to the original MPI?
- How often will the MPI2018 be updated?
- Will the original MPI continue to be published?
- How is the global MPI2018 aligned with the Sustainable Development Goals?
- Why is this better than the Human Poverty Index (HPI) previously used in the HDR?
- What does the MPI measure?
- Why is income not included?
- How was the MPI created?
- The MPI is described as a measure of acute poverty. How does this differ from extreme poverty?
- How do I interpret the various values presented with the MPI results?
- What do your figures for ‘population vulnerable to poverty’ and ‘population in severe poverty’ mean?
- How does the MPI respond to changes over time?
- Where can I find out more about how to apply the MPI approach?
Income vs MPI
- Why are there such wide discrepancies between MPI poverty estimates and $1.90/day poverty estimates in so many countries?
- Why is the MPI headcount (much) higher than national poverty estimates in some countries?
- Is the MPI intended to replace the standard $1.90 a day measure of poverty used for the MDGs and other international purposes?
Policy & international adoption
- What are the policy implications?
- How does the MPI relate to the Sustainable Development Goals (SDGs)?
- How is the MPI approach useful at the country level?
- Can the indicators be adapted at the country level?
- Can the MPI be adopted for national poverty eradication programs?
- How does the MPI respond to the effects of shocks?
- The MPI only covers 102 developing countries. Will an MPI be created for developed nations?
- What are the main limitations of the MPI?
- Why is empowerment not included?
- Why are summer 2016 estimates only available for 102 countries?
- Why does national data for the MPI date from so many different years?
The new global MPI has changes in five of the ten indicators from the original MPI: nutrition, child mortality, years of schooling, housing and assets. These changes reflect an extensive public and high-level consultation about ideal adjustments and analysis of feasibility based on currently available data. More info here.
The new threshold for nutrition includes BMI (Body Mass Index)-for-age, and stunting as well as underweight for children. For child mortality, it considers whether a child has, sadly, perished in the household in the last five years preceding the interview date. For years of schooling, the new threshold requires six years, rather than five years, of schooling. A household is deprived in the housing indicator if the floor is made of natural materials; or the roof or walls are made of natural or rudimentary materials. Finally, the assets indicator now includes ownership of computers and animal carts. More info here.
The global MPI was originally created in 2010 and much has changed in the past eight years! Most notably, the new global MPI takes into consideration the Sustainable Development Goals, which were agreed upon in 2015. The new version also builds on an innovative MPI, trialed since 2014, and newly available data to include cut-offs that were not possible in 2010.
The global MPI is much more than a ranking! A simple ranking does not consider confidence intervals and statistically significant differences in MPI values which are available for every country in Table 1. Furthermore, alongside the national MPI, data are provided on headcount ratios, intensity, and deprivations in each one of the 10 indicators of the MPI. Another reason we do not stress rankings is that only some countries’ data are updated every year, so ranking may change only because one country update its data, not because poverty on the ground changed.
Comparisons between the old and new versions of the global MPI are available from data table 7. As can be seen there, there are some countries for which the MPI values shifted quite a bit, but for the vast majority the changes were minor. Overall, by MPI 2018, 1.34 billion people are MPI poor; by the Original MPI it would have been 1.39 billion.
No. The changes to India’s poverty figures are due to the newly available data from 2015-2016. The global MPI was previously using data from 2005-06 (and 2011, but the 2011 survey is not comparable to 2015/16). To calculate the change in poverty over time, we used strict harmonization of the two datasets – meaning that all indicators are computed in the exact same way – to ensure that what we were measuring was due to real changes in poverty and not just a change in the structure of the measure. The same patterns were computed for the ‘old MPI’ and are roughly the same although poverty reduction was actually a bit bigger: according to the Original MPI, 286 million people would have left poverty.
The 2018 global MPI relies on Demographic and Health Surveys (DHS) for 51 countries, Multiple Indicator Cluster Surveys (MICS) for 43 countries, two combined DHS-MICS surveys, three Pan Arab Project for Family Health (PAPFAM) surveys, plus national surveys for Brazil, China, Ecuador, Jamaica, Mexico and South Africa.
Surveys used for the 2018 MPI computation are from various years, depending on the most recent available data for each country, ranging from 2006 to 2016/17.
Numbers of people living in multidimensional poverty have been computed using UNDESA/Population Division data for year 2016 for all countries.
Table 7 online publishes and make publicly available both sets of numbers for the current 105 countries, so it is possible to compare them. The differences, of course, will be due to changes in methodology rather than changes in levels of poverty. Full details about the specific changes that were made for each country can be found in that countries’ entry in Appendix 1 of the methodological note.
As with the earlier version of the global MPI, the new version will be updated once or twice a year to include newly available datasets.
The original MPI will be published alongside the revised MPI for this year. In 2019, we will only publish the MPI following the 2018 revisions.
Rather than viewing challenges one by one, in silos, the MPI shows how deprivations related to SDGs 1,2,3,4,6,7, and 11 are concretely interlinked in poor people’s lives. Rather than providing only national headlines, the global MPI is disaggregated by subnational region, area, ethnicity, or age cohort. The indicators underlying the global MPI 2018 have been revised to better align with the SDGs. So how does the global MPI 2018 support the SDG agenda?
SDG GOAL 1 OF 17. End Poverty in All Its Forms Everywhere. The preamble to the 2030 Agenda for Sustainable Development which defined the SDGs states that “eradicating poverty in all its forms and dimensions… is the greatest global challenge and an indispensable requirement for sustainable development.” The global MPI addresses multidimensional poverty, focusing on the critical dimensions of health, education, and living standards.
SDG TARGET 1.2. Poverty in all its dimensions. The second out of 169 Targets in the SDGs calls for countries to halve the proportion of men, women, and children living in poverty in all its dimensions. Poverty is understood to be both multidimensional and measurable. The official national MPIs developed by countries to reflect their particular context and the global MPI, like national income poverty measures and $1.90/day, both assess progress in poverty reduction: one with respect to national priorities and the other in a comparative perspective.
LEAVE NO ONE BEHIND. The 2030 Agenda for Sustainable Development pledges that “no one will be left behind”. Putting this idea into practice, the global MPI considers the depth or intensity of an individual’s poverty, going beyond the overall number of poor people (headcount ratio) and providing measurement incentives to reduce the deprivations of the poorest – even if they don’t yet exit poverty. This promotes policies that “leave no one behind”. Disaggregation of the MPI by region, age, and urban/rural area identifes specifc pockets of poverty. This enables more targeted policies and actions, and helps ensure that particular areas and groups are not left behind.
INTERLINKAGES ACROSS SDGS. The global MPI reflects deprivations each person faces in multiple SDG areas – education, water and sanitation, health, housing, etc. Connecting to at least seven SDGs, the MPI brings many concerns together into one headline measure. And, since people are MPI poor if they are deprived in one-third of the weighted indicators, the MPI focuses on people who are being left behind in multiple SDGs at the same time.
The MPI replaced the HPI, which appeared in the HDR from 1997-2009. Pioneering in its day, the HPI used country averages to reflect aggregate deprivations in health, education, and standards of living. It could not identify which specific individuals, households or larger groups of people were poor. The Global MPI addresses this shortcoming by identifying each person as poor-or non-poor based on how many deprivations they face, then aggregates this information into an overall set of intuitive statistics such as the percentage of people who are MPI poor. The MPI can be broken down by indicator to show how the composition of multidimensional poverty differs across regions, ethnic groups and so on—with useful implications for policy.
The MPI identifies overlapping deprivations at the household level across the same three dimensions as the Human Development Index (living standards, health, and education). It shows the incidence of poor people in a population and the intensity of deprivations with which poor households contend. For details see Alkire and Santos 2010, 2014. Read more about the MPI methodology here.
One deprivation alone may not represent poverty. The MPI requires a household to be deprived in multiple indicators at the same time. A person is multidimensionally poor if he or she is deprived in at least one third of the weighted indicators (see below for definitions of ‘severe’ poverty and ‘vulnerable’ to poverty).
We could not include income due to data constraints. Income poverty data come from different surveys, and these surveys often do not have information on health and nutrition. For most countries we are not able to identify whether the same people are income poor and also deprived in all the MPI indicators. Therefore, we could not include income.
How was the MPI created?
The MPI was created by Alkire and Santos and other researchers at OPHI, who applied a new technique developed by Sabina Alkire and James Foster to over 100 developing countries. Read more about the Alkire Foster method for multidimensional measurement.
The MPI reflects the severe deprivations that people face at the same time. Because it was designed to compare acute poverty across developing nations, it is most relevant to less developed countries. We have described the MPI as a measure of ‘acute’ poverty to avoid confusion with the World Bank’s measure of ‘extreme’ poverty that captures those living on less than $1.90 a day.
The MPI constitutes a family or set of poverty measures. These measures can be unpacked to show the composition of poverty 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 is why OPHI describes the MPI as a high resolution lens on poverty: it can be used as an analytical tool to identify the most prevailing deprivations. The MPI measures are explained below:
- Incidence of poverty: the proportion of the population who are poor according to the MPI (those who are deprived in at least one third of the weighted indicators).
- Average intensity of poverty: the average share of deprivations people experience at the same time.
- MPI value: The MPI value, which ranges from zero to one, is calculated by multiplying the incidence of poverty by the average intensity of poverty. It shows the proportion of deprivations that a countries’ poor people experience out of the total possible deprivations that would be experienced if every person in the society were poor and deprived in every indicator. It has many desirable properties.
What do your figures for ‘population vulnerable to poverty’ and ‘population in severe poverty’ mean?
Since 2011, two additional categories of multidimensional poverty have been reported in the HDR Tables. These are called the ‘population vulnerable to poverty’ and the ‘population in severe poverty’. The population vulnerable to poverty is defined as the percentage of the population at risk of suffering multiple deprivations — that is, those people with a deprivation score of 20 –33 percent. The population in severe poverty, meanwhile, measures the percentage of the population in severe multidimensional poverty — that is those with a deprivation score of 50 percent or more.
We have estimated changes to the MPI over time for 50 countries in 2016 where suitable data was available. For details see the MPI data tables. An OPHI Working paper on the topic will be published soon. Please see Alkire, Roche and Vaz 2015 for a previous version of the MPI changes over time analysis.
Background materials that provide the technical guidance needed to apply and adapt the MPI approach, including video guides, are available from OPHI’s Online Training Portal. See also ‘How to Apply the Alkire Foster Method‘ – 12 Steps to a Multidimensional Poverty Measure. Our website also advertises periodic short courses on multidimensional poverty – see OPHI Short Courses.
Income vs MPI
The MPI complements income poverty measures. It measures various deprivations directly. In practice, although there is a clear overall relationship between MPI and $1.90/day poverty, the estimates do differ for many countries. This is a topic for further research, but some possibilities can include public services, as well as different abilities to convert income into outcomes such as good nutrition. For more information, see materials from the workshop ‘Dynamic Comparison between Multidimensional Poverty and Monetary Poverty‘.
The MPI, like the $1.90/day line, is a globally comparable measure of poverty. It measures acute multidimensional poverty, and only includes indicators that are available for many countries. National poverty measures are typically monetary measures, and thus capture something different. The fact that there are differences does not mean that the national poverty number, or the MPI headcount is wrong – these simply measure different conceptions of poverty. At the same time, just as national poverty measures, in contrast, are designed to reflect the national situation more accurately and often differ in very useful ways from the $1.90 measure, some countries may wish to build a national multidimensional poverty index that is tailored to their context, to complement the global MPI (see ‘National policy‘ for details of countries who are doing this).
No. The MPI is intended to complement monetary measures of poverty, including $1.90 a day estimates. The relationship between these measures, as well as their policy implications and methodological improvement, are priorities for further research.
Policies & international adoption
The MPI methodology shows aspects in which the poor are deprived and helps to reveal the interconnections among those deprivations. This enables policymakers to target resources and design policies more effectively. This is especially useful where the MPI reveals areas or groups characterized by severe deprivation. Examples where this has been done in practice already include Mexico’s poverty targeting programme and Colombia’s poverty reduction strategy, tied to their nationally adapted MPIs.
The original MPI indicators were drawn from the former Millennium Development Goals (MDGs) as far as the available internationally comparable data allowed. The ten indicators of the MPI are identical, or relate, to MDG indicators: nutrition (MDG 1), child mortality (MDG 4), access to drinking water (MDG 7), access to sanitation facility (MDG 7) and use of an improved source of cooking fuel (MDG 9). The overall MPI can be broken down into its constituent parts, revealing the overlapping needs of families and communities across a range of indicators which so often have been presented in isolation. This helps policymakers to see where challenges lie and what needs to be addressed. OPHI has suggested that a global MPI 2015+ should be considered for the SDGs; you can read the briefing here. Many countries are now using MPIs to advance the SDGs. This includes reporting the Global MPI, or their national MPI, as indicator 1.2.2. It also means using the MPI as both a policy and governance tool to advance the SDGs and reduce poverty in all its dimensions. In time, the global MPI is likely to be adjusted to reflect the SDG indicators.
The multidimensional poverty approach is often adapted. Countries select the indicators and weights that make sense in their context to create tailored national poverty measures. National MPIs can be useful as a guide to helping governments tailor a poverty measure that reflects local priorities and data sources. In 2009, Mexico became the first country to adopt a multidimensional poverty measure reflecting multiple deprivations on the household level. In 2011, Colombia introduced the first poverty reduction plan to use an adaptation of OPHI’s measure. Colombia’s binding “multidimensional” poverty-reduction targets are tied to its official national Multidimensional Poverty Index Colombia (MPI-Colombia) which assesses broader social and health-related aspects of poverty: education, employment, the condition of children and young people, health, access to public services and housing conditions. The governments of Bhutan, Chile, Colombia, Costa Rica, Ecuador, El Salvador, Honduras, and Pakistan have also released official multidimensional poverty measures. The global MPI was devised as an analytical tool to compare acute poverty across nations – which is something very useful that national MPIs cannot do. However national MPIs made by national statistics offices, and matching national plans and priorities, can be useful policy tools.
Yes. The global MPI indicators were data constrained. National MPIs should use the indicators and weights that make sense. The multidimensional poverty approach to assessing deprivations at the household level can be tailored using country-specific data and indicators to provide a richer picture of poverty at the country level.
Yes. The MPI methodology can and should be modified to generate national multidimensional poverty measures that reflect local cultural, economic, political, climatic and other factors. The MPI will immediately reflect changes in any of its indicators such as school attendance so can be used to monitor progress. Colombia is a powerful example of how the MPI can be used to coordinate national poverty eradication programmes. Costa Rica shows how it is used for budgeting; Bhutan for targeting and so on.
The effects of shocks are difficult to capture in any poverty measure. Because the standard survey data used to estimate the global measure are collected only every three years, the ability to detect changes is limited by the available data. The MPI will reflect the impacts of shocks as far as these cause children to leave primary education or to become malnourished, for example. If more frequent data are available at the country or local level, this can be used to seek to capture the effects of larger scale economic and other shocks.
This is still under investigation: the constraint is no the methodology – which can be easily extended to reflect different faces of poverty – but rather the data. There are no publically available comparable data across the high income countries. The list of all 102 countries that MPI estimates for and country-specific summaries are available on the MPI country briefing page and through the MPI data tables page.
The MPI has some drawbacks, due mainly to data constraints. First, the indicators include both outputs (such as years of schooling) and inputs (such as cooking fuel) as well as one stock indicator (child mortality, which could reflect a death that was five years ago), because flow data are not available for all dimensions. Second, the health data are relatively weak and overlook some groups’ deprivations especially for nutrition, though the patterns that emerge are plausible and familiar. Third, in some cases careful judgments are needed to address missing data. But to be considered multidimensionally poor, households must be deprived in at least six standard of living indicators or in three standard of living indicators and one health or education indicator. This requirement makes the MPI less sensitive to minor inaccuracies. Fourth, as is well known, intra-household inequalities may be severe, but these could not be reflected. Fifth, while the MPI goes well beyond a headcount to include the intensity of poverty experienced, it does not measure inequality among the poor. Rather, OPHI report a separate statistic showing individual and group-based inequalities. Finally, the estimates presented here are based on publicly available data and cover various years between 2005 and 2015, which limits direct cross-country comparability.
We could not include empowerment due to data constraints. The DHS surveys collect data on womens’ empowerment for some countries, but not every DHS survey includes empowerment, and the other surveys do not have these data. Data on men’s empowerment or political freedom are missing.
The data table on OPHI’s website has all MPIs ever published which are available for over 118 countries; each year however we limit publication to countries whose data were fielded within a given time frame, and 102 countries meet these criteria in 2016.
The 2016 MPI relies on the most recent and reliable data available since 2005. As in the case of all poverty measures including income and social statistics, surveys are taken in different years, and some countries do not have recent data. In order to facilitate clear analysis, the year of the survey is reported in the MPI tables. The difference in dates limits direct cross country comparisons, as circumstances may have improved, or deteriorated, in the intervening years. Naturally, this is a stimulus for country governments to collect up-to-date surveys that reflect recent progress. The SDGs’ focus on data should, we hope, give rise to more frequent data for MPI estimations.