Financial literacy, loan repayment, and women's economic resilience in India / K. Riyazahmed.

Format:

Book

Author/Creator:

Riyazahmed, K., author.

Language:

English

Subjects (All):

Agriculture--Economic aspects.

Agriculture.

Physical Description:

1 online resource

Place of Publication:

Los Angeles, CA : SAGE Publications, Inc., 2026.

Summary:

Ramya, the head of an agricultural project in a leading nongovernmental organization (NGO) in Tamil Nadu, a southern state in India, must submit a report to the regional office regarding financial literacy, specifically whether financial literacy training should be continued and whether training positively impacts loan repayment. Furthermore, the NGO wanted to know which region, out of the three that the NGO focuses on for agricultural-driven women empowerment, has better loan repayment. Based on her experience, Ramya felt the Cauvery Delta seems to be better in repayment, and financial literacy initiatives help improve payments. However, the fellow administrators disagreed with Ramya. To support her suggestion, Ramya must analyze the actual repayment and literacy-related data of women-led self-help groups (SHGs) to show that training improved financial literacy, and, in turn, that financial literacy helped improve loan repayment further to the regional differences. Ramya used analysis of variance, paired sample t-tests, and linear regression for this purpose.The results of the analysis showed that there is no regional difference in loan repayment, contradictory to Ramya's belief. However, training significantly improved financial literacy, and, in turn, financial literacy has positively impacted loan repayments of SHGs. Based on this information, Ramya proposed a policy recommendation emphasizing the need for continued training to improve financial literacy and that regional affiliation does not matter. Based on further analysis, she also suggested that medium-sized loan repayment is better, even though there is no difference in the purpose (type) of the loan.This Data Challenge is designed for undergraduate students studying commerce, management, and economics, using a realistic synthetic dataset to help students understand the nuances of data-driven decision-making. Synthetic data refer to artificially generated data. In this context, synthetic data represent simulated SHG-level information on financial literacy, loan repayment, and loan characteristics, created to reflect realistic patterns without using actual beneficiary records. Microsoft Excel (Analysis Toolpak Add-in) or R software can be used to analyze data so that students gain hands-on experience in data analysis and critically evaluate how empirical evidence supports financial literacy initiatives for women empowerment.

Notes:

Description based on XML content.

ISBN:

9798348871130

OCLC:

1616694574

Publisher Number:

T303837