Abstract:
This study examines the patterns of Multidimensional Poverty reduction in Indian districts between NFHS 4 and NFHS 5 and explores the factors associated with these changes District level figures of Multidimensional Poverty Index are used to analyze how poverty varies geographically . The analysis starts with the descriptive analysis contribution of MPI dimensions to the overall Multidimensional Poverty and then follows the other parts . To understand that the Poverty reduction follows the spatial patterns spatial analytical methods are applied including Morans I which is used to find the overall degree of spatial autocorrelation in MPI reduction in Indian districts and to also find and identify the local clusters of districts with similar levels of Poverty reductions Local Indicators of Spatial Autocorrelation LISA is used .The results from these two methods clearly show that the changes in MPI are not randomly distributed but show clear spatial clusters in Indian districts . Further this study examines the relationship between MPI reduction and some selected socioeconomic determinants that are not directly included in the MPI calculation . The determinants which are used are female literacy ,any household insurance coverage/financial scheme ,sex ratio ,and early marriage of women . correlation analysis and regression analysis were conducted between these determinants and MPI reduction for all districts .The results indicate that there are improvements in female literacy and reductions in early marriage with the reduction in MPI in Indian districts . The findings through these analysis suggest that the determinants including geographical location of districts and socioeconomic determinants that are not including directly in MPI calculation play an important role in poverty reduction patterns.The results related to socioeconomic determinants suggest that improvement in education and social indicators related to women supports progress towards poverty reduction.
