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DECOMPOSING MULTIDIMENSIONAL POVERTY: A CASE STUDY OF MAMIT DISTRICT, MIZORAM


Dr. C.Lalnunmawia, Prof. Lalhriatpuii
Department of Economics, Mizoram University, Mizoram
Abstract
Purpose: The study intends to examine the incidence and intensity of multidimensional poverty in Mamit District of Mizoram. Methodology: This study was based on primary data which was collected through a multi-stage stratified random sampling technique. At the first stage, Mamit District was selected solely based on socio-economic indicators for conducting the survey. The second stage involved random selection of 15 villages, five villages from each block. Requisite data were then collected randomly through structured questionnaires which was designed based on the requirement for computation of Multidimensional Poverty Index. From the collected data, the incidence of poverty (headcount ratio), the intensity of poverty and MPI were computed using Alkire-Foster Methodology. The study follows the Global MPI Brief Methodological Note, 2017 in the choice of dimensions, indicators, thresholds and weights assigned to each indicator. Results: From the result of the analysis, the multidimensional poverty in the study area is moderate. The incidence of poverty across the study area is ranging between 0.32 - 0.38 while the intensity of poverty shows slight differences with negligible margin ranging between 0.39-0.411. Decompositions by indicators show that the nutrition has surpassed all other indicators with 22 percent contribution to overall MPI of Mamit district followed by year of schooling with 15 percent. Applications of this study: The findings of the study can be based for formulation of government poverty reduction policies and can be used effectively in improving the existing poverty reduction strategies in the state.
Keywords: Multidimensional Poverty, Decomposition, Mamit District, Mizoram.
Journal Name :
EPRA International Journal of Multidisciplinary Research (IJMR)

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Published on : 2023-09-20

Vol : 9
Issue : 9
Month : September
Year : 2023
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