Journal Article

Explanation of major determinants of poverty using multivariate statistical approach and spatial technology: a case study on Birbhum district, West Bengal, India

2023

Overview

Poverty is not only the focal issue that has drawn worldwide attention but is also an essential issue in people's livelihoods. This research examines the primary factors of poverty in the Birbhum district. Multivariate statistical techniques have been used to identify the primary determinants. Ten parameters have been identified as significant drivers of poverty, six of which are physical, viz. slope, elevation, drainage density, pond frequency, soil texture, and rainfall. The remaining four sociocultural and economic parameters are literacy, major market center, population growth, and road density. A linear relationship has been established between the explanatory and response variables where the R-square or coefficient of determination value is 0.741, and this relationship explains more than 74% of the variables. The P-value of multi-linear regression is 0.000, which validates the model and permits the data for factor analysis to extract the major determinants. Factor analysis indicates that five essential factors have been found based on their eigenvalue viz., agro-climatic factor, infrastructural and educational factors, hydrological factor, demographic factor, and pedological factors. All the p-values of the correlation matrix are < 0.05, meaning all the relationships are valid and significant. This research also demonstrates the spatial analysis of data using GIS technology. The western part of the study area has been affected by the high influence of all factors due to the presence of plateau fringe and associated low productivity. The outcomes of the research are scientifically significant and this study helps the planners, higher authorities, and social workers to eradicate poverty from this region through formulating better policies and management.

• Publisher: Springer Nature B.V
• Subject: Analysis / Case studies / Correlation analysis / Data analysis / Demography / Density / Determinants / Developing countries / Discriminant analysis / Drainage / Drainage density / Economic factors / Eigenvalues / Environmental effects / Factor analysis / Geographic information systems / Geographical information systems / Geography / Influence / LDCs / Literacy / Livelihoods / Low income groups / Multivariate analysis / Parameter identification / Parameters / Population density / Population growth / Poverty / Productivity / Rainfall / Remote sensing / Social factors / Social workers / Sociocultural factors / Soil properties / Soil texture / Spatial analysis / Spatial data / Statistical analysis / Statistical methods / Technology / Texture / Value / Variables