The essay question is affiliated with a topic which has fuelled much debate—which measurement approach or index is characterised by the most efficacy in defining and comprehending poverty, and the extent to which it is existent in different regions of the world. The multidimensional approach is one of many which attempt to most efficiently measure poverty. This essay will explore the concept of multidimensional poverty and assess its strengths and limitations in comparison to other methods of measurements which employ income and consumption as their main tools in determining poverty levels. Firstly, a comprehension of the term—poverty, must be established in order to thoroughly investigate the essay topic.
As a whole, poverty is generally referred to as the paucity of material possessions and/or money, as well as—in some cases—a lack of, or limited access to, basic human needs. However, the definition of the concept of poverty is not limited to this alone. ‘Poverty is a multifaceted concept,’ constituting of social, economic, and political elements (En.wikipedia.org, n.d.). Poverty also refers to a “lack of freedom, enslaved by crushing daily burden, by depression and fear of what the future will bring” (Narayan et al., 2000, p. 37). Poverty does not only refer to an absence or lack of income and monetary resources required to satisfy wants and needs. Walker (2015) notes that it is also associated with the diverse consequences of this absence that are simultaneously experienced by those ensnared by poverty. A good number of these consequences—the non-monetary dimensions of poverty—prolong the existence poverty and can lead to its perpetuation (Walker, 2015). There is no one designated definition for poverty due to the broad nature of the concept. Poverty reduction remains a vital target for virtually all international organisations, including United Nations and the World Bank. Thence, establishing the most appropriate approach to its measurement is of paramount importance and thus fuels a large debate; as this would go some way towards alleviating the inherent obstacles preventing the mitigation of poverty levels.
As asserted by Amartya Sen (1976), the measurement of poverty comprises two rudimentary steps: ascertaining who is poor (identification) and then constructing an index to indicate the extent of poverty (aggregation). Both these steps are origins of numerous debates over time among academics and practitioners about the plausibility of such procedures and whether these are, in fact, the only steps. For an extensive period, unidimensional—rather than multidimensional—measures were implemented to determine affluence and/or poverty levels and differentiate between those who are poor and those who are not. More recently, these have been replaced by new, multidimensional, measures in order to enhance the comprehension of the underlying socio-economic conditions and to more accurately elucidate the evolving concept of poverty.
It is often asserted that the complexity in tackling poverty has escalated over time, thus multidimensional indicators are requisite for the assessment of poverty and the implementation of policies to reduce and eradicate poverty. Therefore, the well-being of a population—and its deprivation—are contingent on both monetary and non-monetary variables. High income levels may enhance the monetary and non-monetary elements of a person or household, however, the markets for a number of non-monetary elements are non-existent, hence implying that higher income may not necessarily result in improved well-being. Consequently, it can be inferred that it would be inadequate to attribute income as the sole indicator of well-being and/or poverty. Rather, it should be supplemented with other variables and indicative components, such as literacy, life expectancy and access to public amenities; to mention but a few.
Assessing poverty solely with an income or expenditure measure is an imperfect method to fully comprehend the deprivations of those ensnared by poverty. Alternatively, multidimensional poverty measures, in which monetary information and elements adjunct non-monetary ones, paints a more accurate, and complete, picture of poverty. Multidimensional poverty measures incorporate a vast array of indicators in order to reflect the intricacy of poverty and facilitate policy formations to mitigate it. It elicits flexibility as different indicators can be employed appropriately to different societies and circumstances, providing a more comprehensive and accurate reflection of divergent situations and regions. These enable a disclosure of who is poor and the causes of their poverty with the different setbacks they experience—a revelation of the root of poverty goes some way toward suggesting potential remedies to alleviate such poverty. As well this, they provide a headline measure of poverty, as these multidimensional measures can be used not only to reveal the poverty level in different areas of a country, but also more specifically the poverty levels among different sub-groups within a country or region (Ophi.org.uk, n.d.).
Over the years, several techniques to measure poverty with the use of a multidimensional methodology have been developed and established. The UNDP’s Human Poverty Indicator (HPI) was feasibly the pioneering influential multidimensional approach. It was calculated at national level with the use of three indicators: rates of mortality, illiteracy and economic deprivation (measured by access to healthcare, clean water and the prevalence of child malnourishment). However, the HPI failed to encapsulate the incidence or nature of multidimensional poverty at an individual level. The Multidimensional Poverty Index (MPI) replaced the HPI in 2010. The Alkire-Foster (AF) counting approach was employed to develop the global MPI (Un.org, 2015). The MPI provides a productive complement to income-based poverty measures with information on the overlapping deprivations experienced simultaneously by individuals. Its ten indices relate to the HPI’s three dimensions, and depict the number of people who are multidimensionally poor as well as the number of divergent deprivations which they encounter. This indicates the incidence and intensity of poverty in a given region at certain time periods. It can be broken down by dimension or by groupings (such as region or ethnicity), with beneficial implications for policy stratagems. Thus it can distinguish between, for instance, a group of poor people who suffer a single deprivations on average, and a group of poor people who suffer three deprivations on average simultaneously.
A fundamental question lies in the reason as to why a multidimensional poverty measure should be employed, rather than a unidimensional one which employs income or consumption as the sole indicators of poverty levels. Administering income as the sole poverty indicator results in an incomplete and inadequate measurement of poverty. Sen (1992) asserted that the well-being of an individual, thence inequality and poverty, is dependent on many dimensions of such as housing, education, life expectancy—income being just one of these dimensions. For instance, economic growth in India has been resonant in recent years. Contrastingly, the ubiquity of child malnutrition is still very much existent, being as high as 50 percent—the highest rates worldwide (Drèze and Sen, 2013). However, if implemented, multidimensional measures can complement income. Those characterised by poverty usually allude to their experience of poverty itself as multidimensional. Participatory exercises reveal that those in poverty refer to their ‘ill-being’ as involving—and being intensified by—poor health, malnutrition, lack of adequate sanitation and access to clean water, social exclusion, poor education, bad living conditions, violence, shame and disempowerment, amongst others (Ophi.org.uk, n.d.); multidimensional measures take such non-monetary indicators into account.
Furthermore, some multidimensional measurement methods, such as MPI, can be employed for additional purposes. In addition to assessing poverty and wellbeing, it can be adapted to “target services and conditional cash transfers or to monitor the performance of programmes” (Ophi.org.uk, n.d.). It also measures monitor changes in poverty and its composition with the use of time series or panel data. This time sensitivity enhances its ability as an effective monitoring tool.
On the other hand, multidimensional methods of measurements possess some limitations. Th MPI is characterised by data constraints.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” (Hdr.undp.org, n.d.). This requirement makes the MPI less sensitive to minor inaccuracies—diminishing its reliability as a poverty indicator. Whilst the MPI does include the intensity of poverty experienced, it fails to measure inequality amongst the poor, albeit fragmentations by groups may illustrate group-based inequalities. Moreover, the absence of a direct income measure and the equivocal causal relationship between poverty, health and education may suggest that the MPI is limited to being merely a measure of low wellbeing rather than poverty as a whole.
In synthesis, poverty remains globally ubiquitous which is why it remains a concept widely debated upon today’s complex world, ranging from its definition to its solution. Poverty had usually been measured with income-based or expenditure-based indicators up until 1996, when the UNDP introduced the multi-dimensions indicators in order to more extensively measure and assess poverty enabling better implementation appropriate policies to mitigate and eliminate poverty worldwide, with particular focus in developing countries. Poverty is subject a variety of indicators and elements, thence it is imperative that these different indicators which influence poverty are employed to enable a more accurate measurement of poverty. Multi-dimensional indicators of poverty measurement are on the rise and are increasingly being employed worldwide by agencies and states and they are likely to become the main index for poverty measurement. Notwithstanding all the advantages multidimensional measures have over income-based and expenditure-based measures, they remain subject to a number of limitations, which are likely to be addressed in any future index generations.