Poverty experts, policymakers and the general public have unanimously acknowledged the significance of measuring poverty as it sheds light on who the poor are, how many they are, where they live and what their deprivations are,  as shared here and here. They have not reached a consensus, however, on how to measure poverty. For this reason, a number of poverty measures have been developed and these can be traced to the pioneering work on poverty measurement of  Charles Booth and  Seebohm Rowntree in the late 1800s. Examples of such measures are Income Poverty Lines ( such as the International Poverty Line of USD 1.90 a day),  the Human Poverty Index,  the Sen Poverty Index, the Alkire-Foster Method,  the Foster–Greer–Thorbecke poverty measures and the Global Multidimensional Poverty Index (Global MPI). Despite all these efforts, the poverty measurement debate is still raging, and you can read about it here, here and here.

In 2016,  influenced by the assertion by Stiglitz, Sen and  Fitoussi that “what we measure affects what we do; and if our measurements are flawed, decisions may be distorted”,  I reviewed the commonly used poverty measures: the Income Poverty Line and the Global MPI and shared my findings at the Brunei-Malaysia Forum 2016, the publication of which can be accessed here. In my review, I acknowledged the claim by the World Bank, which is also shared by UNICEF, that ‘there is no such thing as a perfect poverty measure’. I submitted, however, that a poverty measure needs to be ‘least imperfect’ for it to effectively measure poverty. I defined a ‘least imperfect’ poverty measure as that which sufficiently acknowledges that poverty is multidimensional, individual/context-specific and experiential. According to this definition, I concluded that both Income Poverty Line and Global MPI are not ‘least imperfect’.

The failure to duly acknowledge the individual/context-specific trait of poverty is one of the shortcomings of both measures. Using a single poverty measure, Income Poverty Line or Global MPI, to measure poverty in different countries or urban and rural contexts presents a challenge of underestimating poverty. David Satterthwaite, a poverty researcher at the International Institute for Environment and Development, shared the same sentiment, albeit with reference to the urban context. In his critique of the Global MPI,  he stressed that the tool underestimates the “real deprivation in living conditions for urban populations” as it overlooks other key indicators of urban poverty. Where housing conditions are concerned, for example, the Global MPI only measures the housing material for the floor, roof or walls. But one can still be classified as housing poor even if he or she has a house built of quality material for the three components that the Global MPI focuses on. In Brunei Darussalam, for example, housing poverty is described as having a house without enough rooms for household members and cooling facilities, not only having a house built out of poor building materials.

The Oxford Poverty and Human Development Initiative (OPHI) is, however, improving remarkably the Global MPI. The improvements include ensuring that the Global MPI can be adopted in and adapted to any context: country, rural, urban and business and can be used to measure poverty for any age group. There are now several indexes such as the National Multidimensional Poverty Index, the Business Multidimensional Poverty Index and the Child Multidimensional Poverty Index that can be designed based on what is regarded as poverty in a given country or context.

OPHI, in collaboration with the Food and Agriculture Organization of the United Nations(FAO), recently unveiled the  Rural Multidimensional Poverty Index (Rural MPI), which addresses our concern that the Global MPI treats rural and urban poverty in the same way. The Rural MPI covers 4 dimensions of poverty: food security and nutrition, education, living standards, rural livelihoods and resources and risk; and has 18 corresponding indicators. In this blog post, I share 3 reasons why the development of the Rural MPI is a notable achievement.

The Rural MPI has enormous potential to present a real picture of rural poverty: The tool recognises the specificity of rural poverty. It accepts that rural poverty is “much more than an empty bank account ”  and goes beyond deprivation in health, education and material. In addition to these forms of poverty, which are all that Income Poverty Lines and Global MPI capture, the Rural MPI focuses on livelihoods and resources as well as exposure to risks. Thus, it potentially does not underestimate rural poverty in terms of the number of poor rural people and their poverty conditions.  By way of example, 14% of the rural poor in Malawi identified by the Rural MPI were classified as better off by the Income Poverty Line (FAO & OPHI).

The tool can be adapted by countries in keeping with their rural contexts:  The meaning of rurality varies from country to country, as explained by the United Nations. There is therefore some degree of difference in the rural way of life in countries. In Zimbabwe, for example, rural people predominantly depend on farming whereas, in many rural/interior parts of Brunei Darussalam, people depend mainly on livelihoods from urban areas. This implies that what constitutes rural poverty could be country-specific. Ideally, therefore, countries should have rural poverty measurement tools that correspond to their rural contexts.  Rural MPI, like other measures that build on the Global MPI, can be adapted to any rural context. Thus, for the Rural MPI, countries can choose poverty dimensions and indicators that suit their rural contexts.

It is an effective guiding tool for rural poverty reduction policies: Rural poverty has long been underestimated and this could explain its persistence. As highlighted above, the Rural MPI has the potential to capture the actual deprivations of rural people, providing reliable information on the number of rural poor and the forms of deprivation they experience. This information is essential as it minimises inclusion and exclusion errors in poverty eradication.    Furthermore, the tool’s focus on livelihoods and risks, for example, can help policymakers to determine what to focus on in their efforts to eradicate rural poverty.

The introduction of the Rural MPI is, without doubt, a commendable achievement. I am certain that if countries adopt the tool, they will be able to effectively reduce rural poverty.  It is, however, my wish to see the development of an Urban MPI, given that urban poverty is on the rise due to the Covid-19 pandemic.