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An Empirical Analysis of Microfinance on India Rural Households


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1 Gokhale Institute of Politics and Economics, Deccan Gymkhana, Pune-411004, India
     

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This study examines the impact of micro-credit on rural households to extricate them from poverty trap in India. Although earlier studies have measured poverty based on income, expenditure and consumption related data of Microfinance borrowers, this investigation is focused on measuring poverty through an alternative approach, which encompasses creating a standardised index of socio-economic status of Microfinance clients, including variables relating to assets, food and shelters. The socio-economic status (SES) index is constructed with the help of principal component analysis, which assigns a single score to each household. The logistic regression is used with standardised SES index, which shows that credit through SHGs significantly increasing level of economic status of borrowers as compared to non-borrowers. The study emphasises upon the need to train the clients with respect to investment credit for micro-enterprises which would provide employment on a sustainable basis.


Keywords

Micro-credit, Principal Component Analysis, Logistic Regression, SHGs, Economic Status.
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  • An Empirical Analysis of Microfinance on India Rural Households

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Authors

Sangram Panigrahi
Gokhale Institute of Politics and Economics, Deccan Gymkhana, Pune-411004, India
Deepak Shah
Gokhale Institute of Politics and Economics, Deccan Gymkhana, Pune-411004, India

Abstract


This study examines the impact of micro-credit on rural households to extricate them from poverty trap in India. Although earlier studies have measured poverty based on income, expenditure and consumption related data of Microfinance borrowers, this investigation is focused on measuring poverty through an alternative approach, which encompasses creating a standardised index of socio-economic status of Microfinance clients, including variables relating to assets, food and shelters. The socio-economic status (SES) index is constructed with the help of principal component analysis, which assigns a single score to each household. The logistic regression is used with standardised SES index, which shows that credit through SHGs significantly increasing level of economic status of borrowers as compared to non-borrowers. The study emphasises upon the need to train the clients with respect to investment credit for micro-enterprises which would provide employment on a sustainable basis.


Keywords


Micro-credit, Principal Component Analysis, Logistic Regression, SHGs, Economic Status.