Short Abstract:

Global poverty measures face challenges due to data limitations and diverse human experiences. Countries develop their own multidimensional poverty indices (MPIs) to address this. In India, the revised MPI will consider various dimensions education, health, and social factors, reflecting India's complex poverty landscape, aiding policymakers in poverty alleviation efforts.

Long Abstract:

Introduction

Poverty measures compare people in a society in order to assess the extent of unacceptable disadvantages that exist. Yet any poverty measure is itself imperfect. Imperfections stem primarily from two factors: data limitations and the diversity of human lives being assessed. Internationally comparable measures face a greater challenge on both counts: the pool of comparable data is narrower, and the diversity of lives and contexts being compared is greater (Alkire and Jahan, 2018). There has been development of number of national multidimensional poverty index with the utilisation of context specific dimensions and indicators (Mexico, Colombia, Bhutan, Chile, Costa Rica, El Salvador, Pakistan, Ecuador, Honduras, Armenia, Mozambique, Dominican Republic, Panama, Nepal, Philippines, Nigeria, and Malaysia, among others). In the development of National MPIs many countries have added to the dimensions of Global-MPI to construct National-MPI, for instance, MPI of Latin America and Caribbean added a dimension of Labour. While some countries have used the same dimensions as Global-MPI, however, added to the list of indicators. The first major revision of global-MPI indicators was done in 2018, hence, this study is an exploratory study to further revise the indicators based on indian national development agenda and data availability.

Methodology

This paper utilized data from the fifth National Family and Health Survey (NFHS) round conducted in 2019-2021. The NFHS is a comprehensive cross-sectional demographic health survey conducted throughout India under the authority of the Ministry of Health and Family Welfare. The first NFHS survey was conducted in 1992-93; and since then there have been a total of five survey rounds. The NFHS surveys aim to provide valuable information on various demographic and health indicators at the district, state, and national levels. NFHS-5 employed a two-stage stratified random sampling design to ensure representative coverage. By collecting data from 636,699 households and 2843917 individuals, NFHS-5 aimed to comprehensively understand the demographic and health status.

The Alkire and Foster (AF) methodology was employed to calculate multidimensional poverty indices. This methodology utilizes the dual cut-off method, where individuals or households below specific thresholds for each weighted indicator are identified as poor within that dimension. Subsequently, these individuals are aggregated across dimensions, allowing for a comprehensive understanding of multidimensional poverty. Three estimates of multidimensional poverty—headcount ratio, Intensity of poverty, and Multidimensional Poverty Index (MPI)—has been depicted as follows:

Headcount ratio (H): It represents the proportion of individuals experiencing multidimensional poverty to the total population and can be denoted as-

H=q/n

……….(1)

Where q is the number of multidimensional poor individuals and n is the total population.

Intensity of Poverty (I): It represents the average deprivation score, taking into account the weights assigned to each dimension, for all individuals experiencing multidimensional poverty and can be denoted as-

A=(∑_1^q▒c)/q

……….(2)

Where c is the deprivation score experienced by the multidimensionally poor.

Multidimensional Poverty Index (MPI): It is the product of headcount ratio and Incidence of poverty and can be denoted as-

MPI=H*A

……….(3)

Where H is the headcount ratio, and A is the Intensity of poverty.

A detailed description of the dimensions and indicators of the multidimensional poverty estimation is presented in Table 1.1 and Table 1.2. We have used three dimensions (Health, Education, and Standard of Living) and ten indicators alike the Global-MPI specifications. Under the health dimension, there were two indicators- child mortality and nutrition; under the education dimension, there were two indicators-years of schooling and school attendance; under the standard of living dimension, there were six indicators- cooking fuel, sanitation, drinking water, electricity, housing and asset. The multidimensional poverty threshold was determined at 33% or deprived in one-third of the weighted deprivation score. . The revised framework incorporated modification in child mortality estimation, increase in education threshold, and composition of asset components.

Results

The OPHI estimates have identified 16.4% of individual to be living in multidimensional poverty in 2019-21 with MPI 0.069. While only the child mortality indicator was revised the headcount ratio was increased to 16.5%, whereas, with the revision in education indicator and asset indicator the incidence of poverty was altered to 18.8% and 18.3% respectively. Moreover, the cumulative revision of child mortality and education, and child mortality, education, and asset the head count ratio was 18.9% and 21%. The multidimensional poverty level increased from 16.4% to 21% with the revision of indicators.

Conclusion

This paper is a significant robust estimate of multidimensional poverty. This study is a primary contribution to construct a relevant multidimensional poverty index of India to reflect the multidimensional poverty of the country. Identification of the poverty level is crucial to achieve the aspirational SDG 1.2. Further, this exercise adds to the literature of multidimensional poverty to track the progress and monitoring of various policies and programs in reducing deprivation level in various development indicators.