Factors influencing micro-entrepreneurship among women SHG members of Sikkim

A propensity score matching approach

Bibliographic Data

ID21515798
AuthorsSmriti Prasad (0000-0002-2302-6065, Sikkim University), Manesh Choubey (0000-0002-1949-4499, Sikkim University)
Year2024
Volume51
Issue6
Pages741-756
Publication date2024-05-21
Open AccessYes
TypeARTICLE
VenueInternational Journal of Social Economics (JOURNAL)
Journal identifiersISSN: 0306-8293 • E-ISSN: 1758-6712
PublisherEmerald (PUBLISHER)
DOI10.1108/ijse-01-2023-0070
OpenAlexW4387673028
LanguageEN
Citations received2
References cited29

Purpose The paper identifies the influence of socio-economic factors and livelihood training in stimulating micro-entrepreneurship among women self-help group (SHG) members. Design/methodology/approach The study is based on a sample of 416 women SHG members drawn from all the four districts of Sikkim using cluster sampling procedure. A multivariate binary logistic model is used to find the impact of socio-economic factors, and a Poisson regression has been used to find the impact of training on fostering micro-entrepreneurship. The result is validated using a propensity score matching approach which corrects for the potential self-selection bias in the sample. Subsequently, a covariate adjustment estimator verifies the robustness of the approach. Findings The study finds that “size of landownership”, “amount of loan borrowed”, “member's age”, “number of earning and dependent members”, “number of years of SHG enrolment” as well as the “district to which the member belongs to” have a statistically significant influence on the graduation of SHG members to micro-entrepreneurs. Furthermore, it is found that members attending the livelihood training programmes had a significantly higher number of microenterprises. Originality/value The study differentiates itself by providing empirical evidence on how socio-economic factors and livelihood training stimulate micro-entrepreneurship among SHG women of Sikkim, which has so far remained unexplored. Moreover, advanced econometric method has been used to eliminate the possible self-selection bias involved with training participation and thereby provides reliable and robust results. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2023-0070

Agriculture · Business · Creativity · Demographic economics · Economics · Entrepreneurship · Geography · Livelihood · Originality · Propensity score matching · Selection bias · Statistics · Innovation and Socioeconomic Development · Mathematics · Microfinance and Financial Inclusion · Psychology · Social Psychology · Taxation and Compliance Studies · Marketing

Tools

Open DOI