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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM45071
Volume:
9 |
4 |
Apr 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
This study explains the role of financial institutions in the agriculture development in India. Financial institutions play a crucial role in the development of agriculture in India, a country where nearly half the population depends on agriculture for their livelihood. These institutions provide the necessary financial services, infrastructure, and support systems that enable farmers to enhance productivity, adopt modern techniques, and reduce dependency on informal sources of credit. The present study analyzes the performance and growth of financial sources of credit, which are considered vital for agricultural development in India. Agriculture remains a primary sector in the country, providing significant employment opportunities, especially in rural areas. The performance of the agricultural sector depends on various factors, among which access to agricultural credit plays a crucial role. Over the past four decades, the flow of institutional credit to agriculture has shown a consistent upward trend, highlighting its growing importance in supporting agricultural activities and rural livelihoods. The study, based on secondary data collected from various sources, reveals that institutional financial credit to the agricultural sector has increased significantly in real terms over the past several years. The findings from the exponential growth model demonstrate a robust and statistically significant upward trend in institutional credit to the agricultural sector in India. The average annual growth rate is estimated at 15.5%, which is significant at the 1% level, indicating a high level of confidence in the results. Furthermore, the model exhibits a coefficient of determination (R²) of 0.881, implying that approximately 88.1% of the variation in agricultural credit can be explained by the model.
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Publication Date
4/25/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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