Tracing Performance Trends of Self-Help Groups Across India: A Social Computing Analysis

Self Help Groups (SHGs) are voluntary associations of economically disadvantaged individuals, primarily rural women in India, who come together to overcome poverty and address community issues through self-reliance and collective action. This paper endeavors to scrutinize the impacts of savings and loan disbursement on the Non-Performing Assets (NPAs) of banks concerning SHGs. The study seeks to identify the performance of SHGs in India over time, using appropriate social computing analytical methods, specifically during 2007–08 to 2022–23 across six regions of India, namely, central, eastern, northeastern, northern, southern, and western India. Initially summary statistics on the chosen variables have been calculated. For the purpose of analysis, panel data regression analyses have been used, prior to which test for stationarity of the variables of interest have been conducted and test for co-integration have been performed. Hausman test has been used to choose between random effects and fixed effects models. All variables have been found to be stationary at first difference and the presence of cointegration has been supported. Hausman test gave evidence in favour of random effects model. The analysis reveals that NPAs are the most volatile variable, followed by loan disbursement and savings per SHG. Interestingly, the study concludes that loan disbursement and savings have a detrimental effect on NPA growth concerning SHGs. There is a need for financial institutions to develop effective mechanisms for managing the credit risk associated with lending to SHGs, while also supporting their efforts to improve their economic situation.

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Publication Details

Published
2025-02-07
DOI
https://doi.org/10.1109/icccit62592.2025.10927783
Primary Topic
Digital Mental Health Interventions
Type
article
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Tracing Performance Trends of Self-Help Groups Across India: A Social Computing Analysis

Bhaswati Roy, Sandip Mukherjee, Indrani Sengupta, Sayanti Samanta
Digital Mental Health Interventions
article

Tracing Performance Trends of Self-Help Groups Across India: A Social Computing Analysis

Bhaswati Roy, Sandip Mukherjee, Indrani Sengupta, Sayanti Samanta
article en

Abstract

Self Help Groups (SHGs) are voluntary associations of economically disadvantaged individuals, primarily rural women in India, who come together to overcome poverty and address community issues through self-reliance and collective action. This paper endeavors to scrutinize the impacts of savings and loan disbursement on the Non-Performing Assets (NPAs) of banks concerning SHGs. The study seeks to identify the performance of SHGs in India over time, using appropriate social computing analytical methods, specifically during 2007–08 to 2022–23 across six regions of India, namely, central, eastern, northeastern, northern, southern, and western India. Initially summary statistics on the chosen variables have been calculated. For the purpose of analysis, panel data regression analyses have been used, prior to which test for stationarity of the variables of interest have been conducted and test for co-integration have been performed. Hausman test has been used to choose between random effects and fixed effects models. All variables have been found to be stationary at first difference and the presence of cointegration has been supported. Hausman test gave evidence in favour of random effects model. The analysis reveals that NPAs are the most volatile variable, followed by loan disbursement and savings per SHG. Interestingly, the study concludes that loan disbursement and savings have a detrimental effect on NPA growth concerning SHGs. There is a need for financial institutions to develop effective mechanisms for managing the credit risk associated with lending to SHGs, while also supporting their efforts to improve their economic situation.

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Digital Mental Health Interventions
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