Other types of MPI and AF-based measures

The MPI is a tool with applications across a variety of different contexts. For example, it can be adapted to measure poverty across regions or subnational regions, or among population groups such as children. 

The MPI is based on the AF method, which has also provided the blueprint for Bhutan’s Gross National Happiness Index, which has measured happiness in Bhutan since 2010, and the Women’s Empowerment in Agriculture Index, which has helped to monitor women's empowerment in the agricultural sector across the world since 2012.  

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  • Regional MPI

    Regional MPIs offer a tool for monitoring multidimensional poverty across a selection of countries which may share some circumstances in terms of, for example, culture, governance, politics, economic development, or climate crises. Regional bodies make use of this information to inform their understanding of their member states.    

    The Revised Arab MPI is an example of a regional MPI spearheaded by the League of Arab States (LAS) and the United Nations Economic and Social Commission for Western Asia (ESCWA). This MPI focuses on moderate poverty across the region and the current version defines poverty in both material and social capability spaces, which are assigned equal weights.  

    More info on the Arab MPI via the MPPN website.  

  • Subnational MPI

    A subnational MPI may be useful in countries which do not yet have a national MPI, but where a state government may wish to make progress in multidimensional poverty reduction.  

    • Andhra Pradesh, India – Although India launched a national MPI in 2021, in 2018, Andhra Pradesh was the first state to publish an official subnational MPI. Its purpose was to understand multidimensional poverty in the state to support evidence-based policymaking in reducing multidimensional poverty.  
    • Ho Chi Minh City, Viet Nam – From 2014 the local government in Ho Chi Minh City chose to complement monetary statistics and track access to basic social services for the period 2016–2020  (education and training, health care, employment and social insurance, living conditions and access to information). A national MPI was introduced in 2015.  

    Ideally, instead of introducing a separate subnational MPI, the disaggregation of subnational results of a national MPI can be used by local governments to catalyse and guide poverty reduction. The state government of Oaxaca, the fifth largest and traditionally the poorest state in Mexico, has used data from the Mexican National MPI to help guide the planning and targeting of public investment and public policies resulting in a reduction of poverty as observed by the MPI. 

  • Child poverty and MPI

    It has been regularly demonstrated in studies of multidimensional poverty that children tend to be poorer than adults. They are poorer when considering the numbers of children affected, the proportion of the child population impacted, and the levels of their poverty. Studies have also shown how the effects of poverty, such as poor nutrition and low levels of education, can have consequences that affect children for the rest of their lives.  

    In the Sustainable Development Goals, the international community recognised the importance of child poverty. As a result, Target 1.2 makes specific reference to children by stating that member states should aim to reduce by half the multidimensional poverty of women, men and children. 

    The MPI is a key tool for monitoring child poverty from a multidimensional perspective. There are a number of possible approaches: 

    Disaggregating a national MPI 

    • Through disaggregation – filtering by age group – an MPI can estimate the incidence and intensity of poverty among children.  
    • Since 2017, the global MPI produced by OPHI has been disaggregated by the age groups of 0–9 and 10–17. 
    • National MPIs which use age disaggregation include the MPIs of Afghanistan, Bhutan, Chile, El Salvador and Nepal 
    • It should be noted that the majority of MPIs are computed using household level data, which is more commonly available than individual level data. This means that a child is considered poor if they live in a poor household.  

    Intrahousehold analyses of a national MPI 

    • Research is underway to explore the microdata of national MPIs to reveal the differing experiences of children living in the same household. Through intrahousehold analysis, it is possible to gain a clearer understanding of whether certain deprivations are more prevalent among children of different ages and genders, or, for example, between children with or without disabilities.  

    Linked Child MPI 

    • A linked Child MPI includes the same dimensions and indicators as the National MPI plus an additional set of child-specific indicators relevant for children within a selected age group. Different developmental stages offer different opportunities for measuring child poverty. A useful indicator for a child under 5 can be different to an indicator that is relevant for a child who is 17. The Sri Lanka Child MPI (2021) demonstrates a linked-Child-MPI approach. This MPI focuses on children under 5 and is based on data gathered at the individual level. 
    • The Nigeria MPI (2022) includes a linked Child MPI for children under 5. The data for this MPI are collected at the household level.   
    • One advantage of a linked Child MPI is to avoid the communication challenges of two distinct measures of multidimensional poverty. The MPI is ultimately a weighted index and two separate measures can make the selection of policy priorities less intuitive.   

    Child MPI 

    • A separate child MPI, in addition to a national MPI, with dimensions and indicators designed specifically for children can identify poverty at the level of the individual child and considers deprivations that are particularly relevant to child development. Such measures can identify poor children living in non-poor households and can also reveal intrahousehold inequality. The Thailand Child MPI, Bhutan’s Child MPI and Panama’s MPI for Boys, Girls and Adolescents demonstrate this approach.    

    OPHI is a member of the Global Coalition to End Child Poverty, a global initiative to raise awareness about children living in poverty across the world and support global and national action to alleviate it.  

  • Bhutan's Gross National Happiness Index (GNH)

    The Gross National Happiness (GNH) Index in Bhutan has measured 'happiness' since 2010 and is perhaps the most well-known measure based on the AF Method. 

    The purpose of the measure, which was constructed by the Centre for Bhutan and GNH Studies, is to guide government, NGOs and businesses to increase societal wellbeing and happiness in Bhutan. The GNH Index identifies four groups of people – unhappy, narrowly happy, extensively happy, and deeply happy. 

    The GNH Index is made up of 33 indicators grouped under nine domains which aim to emphasise different aspects of wellbeing and human flourishing. The domains are psychological wellbeing; health; time use; education; cultural diversity and resilience; good governance; community vitality; ecological diversity and resilience; and, living standards.  

    Learn more about GNH 

  • Women’s Empowerment in Agriculture Index (WEAI)

    The Women’s Empowerment in Agriculture Index (WEAI) is a tool based on the AF Method that measures the empowerment, agency and inclusion of women in the agriculture sector. It does this by tracking women’s engagement in agriculture in five areas: production, resources, income, leadership, and time use. It also measures women’s empowerment relative to men within their households, providing a more robust understanding of gender dynamics within households and communities. 

    The WEAI was originally launched in March 2012 by OPHI with the United States Agency for International Development (USAID) and the International Food Policy Research Institute (IFPRI). It was the first standardised measure to measure women's empowerment and inclusion in agriculture. The measure has been subsequently developed and adapted to create three additional WEAIs including the Abbreviated WEAI (A-WEAI), a shorter version for use in population-based surveys. 

    Learn more about the WEAI 

Bhutan - home of the GNH

Bhutan - home of the Gross National Happiness Index which is based on the AF Method.

© Photo by aaron boris on Unsplash