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Home▶ Journals▶ Indian Journal of Extension Education▶Archive▶Vol. 58 No. 2 (2022)▶Determinant of Access to Credit and Availing Subsidies for…
Indian Journal of Extension Education
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Determinant of Access to Credit and Availing Subsidies for Protected Cultivation in Maharashtra

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P. Prakash — Scientist,ICAR-Central Tuber Crops Research Institute, Thiruvananthapuram 695017, Kerala, India
Pramod Kumar — Principal Scientist, Division of Agricultural Economics, ICAR-Indian Agricultural Research Institute, New Delhi-110012, India
Prabhat Kishore — Scientist, ICAR-National Institute of Agricultural Economics and Policy Research, New Delhi-110012, India
D. Jaganathan — Senior Scientist,ICAR-Central Tuber Crops Research Institute, Thiruvananthapuram 695017, Kerala, India
Sheela Immanuel — Principal Scientist, Extension and Social Sciences, ICAR-Central Tuber Crops Research Institute, Thiruvananthapuram 695017, Kerala, India
S. Varadha Raj — Associate Professor, Department of Social Sciences, Horticultural College and Research Institute, Periyakulam-625601, Tamil Nadu, India
Published 28 Mar 2022 Vol. 58 No. 2 (2022), pp. 167-172 ● Open access
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Abstract

Protected cultivation requires high initial investment and intensive use of inputs for crop production but offers better yield which in turn increases the profitability of the farm. The study attempts to explore the economics of protected cultivation with different interest rates regime and subsidy in Pune and Nasik districts of Maharashtra conducted during 2018-19. About 95 to 97 per cent of the farmers availed subsidy from the government and the rest of the farmers constructed their polyhouse and shade net house without subsidy. About 47 to 50 per cent of the total cost was given as subsidy. Heckman selection model showed that the factors such as years of education, farm size, farm income, membership and occupation were the major determinants of access to credit. The study also indicated that household age, farm size, farm income, distance from the market and access to subsidies were important drivers of technology adoption. Among all, the access to subsidy reflected the availability of external capital support as one of the determining factors for adoption of technology. The factors responsible for non-repayment of loans were increase in farm income, family size and years of schooling.

KeywordsCreditHeckman selection modelMultiple linear regression modelProtected cultivationSubsidyRepayment pattern

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    Copyright © 2022 P. Prakash, Pramod Kumar, Prabhat Kishore, D. Jaganathan, Sheela Immanuel, S. Varadha Raj