Multidimensional Poverty Index and Development: Enhancing Capabilities and Wellbeing
Poverty, inequality, and development are at the core of Amartya Sen’s Capability Approach that challenged the traditional view of the association of development with only economic growth. The concept of development undertook a paradigm shift when built on two fundamentals: that it should focus on the person as an individual unit of analysis instead of the economy, and the space of progress should consist of freedom and capability, and not only income. The approach also impacted poverty as he described it as a complex and multidimensional concept that should consider the diversity of characteristics and circumstances. It is not just people having a lack of income or resources but also a lack of education, health, and other productive opportunities. Thus, poverty deprives people of their capabilities, and in this framework, it becomes “capability failure” that is limiting the freedom to achieve something and enjoy “beings and doings” necessary for human life. Hence, we need to understand that the concept of poverty is in itself inherently multidimensional.
In 1976, Amartya Sen’s Poverty: An Ordinal Approach to Measurement determined the problems of identifying the poor in the population and constructing a poverty index based on the information of the identified poor. He argued the insensitivity of the headcount ratio to the depth and breadth of poverty and why inequality among the poor should be incorporated in the poverty measures. Headcount ratio lacks monotonicity and does not encourage public spending to identify the disadvantaged poor and change their poverty status. According to him, poverty measurement should consider three things. Firstly, selecting the space in which we can assess poverty, secondly identifying the poor by determining a cut-off for each, space to distinguish the poor from non-poor, and thirdly aggregating the resulting data by an appropriate poverty index. Alkire and Santos (2010,2014) developed the first Multidimensional Poverty Index (MPI) based on Sen’s Capability approach, and the global MPI implements one of the Alkire and Foster (2007 and 2011) class of poverty measures. The Foster-Greer-Thorbecke (FGT) poverty measures were the basis of the framework development. Global MPI has three dimensions: Education, Health, and Living Standards and tracks ten indicators related to them. It shows a comprehensive picture of people living in poverty and allows comparisons across countries, regions, and the world. Within countries, the comparison is by ethnic group, urban or rural location, as well as other household and community characteristics. Different indicators can be chosen depending upon context and purpose of measurement and depending on the needs and priorities of the researcher. MPI respects dimensional monotonicity rather than just having a headcount ratio indicating that whenever a poor person ceases to deprive in a dimension, poverty decreases and measures the poverty status by capturing the intensity and incidence of poverty. It is an index of acute multidimensional poverty that covers over 100 countries and offers a valuable complement to income or consumption-based poverty measures. Oxford Poverty and Human Development Initiative (OPHI) releases Global MPI country briefings yearly for 107 countries, including India.
The standard way of poverty measure by Tendulkar Poverty Line 2011–12 in India is only through monetary poverty, which assesses income or consumption and expenditure poverty of the population of different states in rural and urban areas. If a person spends Rs. 27.2 in rural areas and Rs. 33.3 in urban areas a day, then it is defined as living below the poverty line. And for a family of five that spends less than Rs. 4,080 and Rs. 5,000 in rural and urban areas respectively, is considered below the poverty line. It received criticism on fixing the poverty line too low, so the Rangarajan committee changed it to people living on less than Rs. 32 a day in rural areas and Rs. 47 a day in urban areas as poor (NITI Aayog 2018). In 2013, the Planning Commission released poverty data for 2011–12 based on the Tendulkar Poverty Line. 21.9% of the population, or 269.8 million people, were poor. After this, there was no release of official poverty estimates in India (Gaur & Rao 2020). However, we cannot identify or target a poor person or household if poverty is simply a money metric. It leads to an ‘identification problem’ in poverty measurement. It is pertinent to identify where the poor live and measure their extent of deprivation through the satisfactory level of human function such as nutrition, access to healthcare services, education, employment, and infrastructure. Simple conversion of these functioning requirements into income requirements fails to capture the true extent of deprivation. Even though the country/states/districts are attracting investment to provide an opportunity for high earning, the development is quite imbalanced without adequate public expenditure in the social sector to alleviate poverty. If the poverty problem is shown simply in monetary terms, then so will the solutions.
MPI is not just limited to income-based poverty but shows how people are poor. It captures the multiple, overlapping disadvantages poor people can face at the disaggregated levels. Unlike the Tendulkar committee methodology, MPI allows us to have data that looks at all the dimensions for every person and household of both the states and districts at the same time. Such intersections of deprivation account for critically important dimensions to understand poverty and social inequality. The layered approach to addressing poverty pockets and spatial poverty traps multidimensionally allows the government to improve spatial targeting of public expenditure for inclusive growth. It disaggregates urban/rural areas, and subnational regions(state-wise). It shows the distribution of deprivation scores that make up the intensity of poverty across multidimensionally poor people. During the launch of the 2018 Global MPI report, Angus Deaton talked about the positive correlation between deprivation in different areas with each other and how MPI allows us to have data that reflects on all of the dimensions for every person at the same time.
OPHI used the data of the third & fourth rounds of the National Family Health Survey (NFHS) to calculate Multidimensional poverty across 640 districts. It decomposed into the state-district level, rural-urban area, different age groups, and scheduled caste & tribes. Such granular information on who is poor, how, and where will be available to policymakers for the first time in India to overcome the identification problem. Identification of trends and hotspots of MPI will translate into evidence-based decisions at both micro and macro level for the public resources. As per United Nations 2019 Multidimensional Poverty Index report, India has lifted 271 million people out of multidimensional poverty between 2005–06 and 2015–16 in 10 years. Even with this progress, the country is still home to 364 million people living in multidimensional poverty, the largest in the world. As per the OPHI country briefing of 2020, the national MPI is 0.123. However, the paradigm shift in the mindset of policymakers to look beyond income measures of poverty allows tracking deprivations & poverty in a nuanced manner. Capturing the intensity of poverty allows tracking poverty in the pro-poor pattern and aims to leave no one behind by understanding interlinkages across deprivations for coordinated policy intervention.
With the multidimensional poverty index’s focus on individuals, the concept of development shifts to human development. Expansion of freedom enhances the capabilities that people value and empowers them to contribute to the development of a shared planet. Economic growth is strictly neither necessary nor a sufficient condition to improve human development. Development objectives should also consider the means rather than just the ends.
This article has been written by Samridhi Agarwal, a graduate in Economics with a specialization in Public Policy. She is working as a Research Associate at the Centre for Policy Research, Delhi. She is also working as a Research Assistant on the Multidimensional Poverty Index in India and is the Community lead of Rethinking Economics India Network.
