The MPI: How Researchers in Oxford Combat Global Poverty – BORGEN

OXFORD, United Kingdom — Researchers at Oxford, in collaboration with the United Nations Development Programme (UNDP), developed the Multidimensional Poverty Index (MPI) to measure poverty across a broad spectrum of indicators. This unique counting-based tool has assisted more than 100 governments in developing effective policies and tracking progress toward poverty reduction targets, including the Sustainable Development Goals (SDGs).

Sustainable Development Goals

The Sustainable Development Goals (SDGs), established by the United Nations (U.N.) Conference on Sustainable Development in Rio de Janeiro in 2012, consists of universal objectives designed to address the most urgent economic, environmental and political challenges worldwide. According to the SDGs, poverty represents the most significant global challenge and is considered an essential factor for sustainable development.

Goal one of the Sustainable Development Goals (SDGs), “End poverty in all its forms everywhere,” highlights the U.N.’s commitment to eradicating poverty. Target 1a aims to reduce by half the proportion of men, women and children living in poverty by 2030. Meanwhile, Target 1b emphasizes that to achieve this, countries need to establish effective policy frameworks at the regional, national and international levels.

More than 100 countries have increased their government spending on poverty alleviation, but the goal of zero poverty remains elusive. Current trends suggest that by 2023, about 575 million people will still be living in extreme poverty. A 2023 progress report on the Sustainable Development Goals (SDGs) indicates that to approach this goal, there should be heightened action and investment in areas like education to enhance social protection for vulnerable groups. While the SDGs offer one method for tracking progress in poverty alleviation, the U.N.’s progress reports are tools for holding governments accountable and outlining global efforts to combat poverty.

Multidimensional Poverty

Fanni Kovesdi, research and development manager at the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, discussed their approach to measuring poverty with The Borgen Project. Fanni explained that multidimensional poverty captures the broader experience of those affected, extending beyond mere financial constraints to include various deprivations. She highlighted that “a lot of the time issues [of poverty]go beyond just lack of money and resources.”

Understanding poverty as being multidimensional could also ensure that those who may not be financially poor but are deprived in other areas receive the support they need. For example, those who live in regions with abundant natural resources and jobs, but who continue to lack access to public services and adequate education due to the remoteness of their location. While these people may have sufficient income, there are other areas in which they are severely deprived such as empowerment and social mobility.

By recognizing poverty as a multidimensional issue, governments and policymakers can potentially develop more effective policies that reflect the real experiences of those in poverty. OPHI’s approach draws on Nobel Economist Amartya Sen’s Capability Approach, which emphasizes empowering individuals to overcome the interconnected challenges that diminish their quality of life. This perspective helps tailor interventions to address the various facets of poverty comprehensively.

Multidimensional Poverty Index

The Multidimensional Poverty Index, developed by Sabina Alkire and James Foster, is a flexible, counting-based tool. It measures poverty both within countries and on a global scale and it can also assess factors like well-being and happiness.

Fanni explained that the first step in developing a Multidimensional Poverty Index (MPI) involves defining key indicators of poverty for a specific country, such as malnutrition, sanitation, access to drinking water and school attendance. Researchers then conduct household surveys to assess deprivation levels for each indicator, assigning scores that reflect the extent of poverty. The MPI calculates the headcount ratio— the percentage of people experiencing any deprivation—and multiplies it by the average deprivation score among the impoverished. This method not only quantifies the prevalence of poverty but also measures its severity, providing a comprehensive picture of both its breadth and depth in the country.

Applications and Impact of the MPI

The MPI can disaggregate data by different criteria such as subnational regions, age and household size, revealing varying poverty levels across different demographics. This comprehensive approach provides a clearer understanding of poverty than merely assessing a country’s GDP against an arbitrary poverty line. The flexibility of the MPI allows for various applications. For instance, the Global MPI, developed jointly by the Oxford Poverty and Human Development Initiative (OPHI) and the UNDP’s Human Development Report Office in 2010, offers an annual assessment for more than 100 countries. This index facilitates comparisons between countries and tracks global progress in poverty reduction, aligning with targets like the SDGs.

National MPIs vary based on the indicators each country selects when adopting the tool. These indexes are tailored to measure the unique experiences of poverty within a specific country and assist governments in crafting policies and tracking progress over time. It is important to note that MPIs complement rather than replace national monetary policies.

Colombia

Colombia has utilized a national MPI for over a decade. Policymakers have used the MPI to foster coordination among various ministries to align their policies effectively. By analyzing its MPI data, it recognized that many factors contributing to poverty occur simultaneously, necessitating the design of interconnected policies rather than isolated measures.

Fanni explained that to facilitate this approach, the president directed a coordination committee encompassing various ministries, assigning each the responsibility for a specific MPI indicator. Additionally, the government implemented a traffic light system to track each ministry’s progress on its indicators, revealing whether the number of households identified as deprived in those areas was decreasing. This method illustrates how the MPI can track progress in a nuanced way that income-based measures cannot.

Costa Rica

Costa Rica utilized its national MPI to inform budget allocation. Fanni explained that policymakers used disaggregated data to compare regional poverty levels with the funding assigned to various social programs. It discovered a mismatch where regions with lower poverty levels received more funding. To address this, the government realigned its budget to prioritize regions with higher poverty, enhancing the allocation of funds to its social programs without increasing overall spending. This adjustment ensured that expenditures more effectively addressed poverty. The Costa Rican approach illustrates how a national MPI can complement, rather than replace, monetary policy by guiding more financially prudent solutions.

Future Impact

Both national and Global MPIs provide governments with a comprehensive understanding of poverty, both locally and globally. The MPI draws from data collected through methods like household surveys, engaging directly with those impacted by poverty and facilitating substantive changes. Fanni emphasized that these MPIs need to connect directly to policymaking to foster real change. As seen in Colombia and Costa Rica, MPIs can potentially influence policy in ways that are both cost-effective and practical. While the concept of multidimensional poverty is now well recognized, the MPIs developed by OPHI offer invaluable insights for governments and individuals alike, serving as essential tools for crafting effective poverty reduction policies.

– Carla Messinger

Carla is based in Oxford, UK and focuses on Global Health and Politics for The Borgen Project.

Photo: Flickr

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