Agricultural credit in India: determinants and effects

  • Published: 10 July 2023
  • Volume 58 , pages 169–195, ( 2023 )

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research paper on agricultural credit in india

  • Paramasivam Ramasamy   ORCID: orcid.org/0000-0002-6385-480X 1 &
  • Umanath Malaiarasan 2  

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Credit is used as an instrument to raise the capital required to increase farm productivity, income and welfare of farmers, particularly small and marginal farmers who lack the capital to buy necessary inputs in time for agricultural operation. But the question of whether the goals of credit policies were met still remains unanswered. This study, therefore, attempted to estimate the effect of farm credit on investment, input expenditure, income and other welfare indicators using national-level farm household survey data. We used the logit function to estimate the determinants of credit access and the propensity score matching algorithm to estimate the effect of credit policies. Results revealed that only 33% of farmers have access to credit facilities and that middle-aged farmers and farmers with a larger farm size have shown a higher probability of accessing credit facilities, whereas farmers from underprivileged castes have shown the least probability of credit access. Nevertheless, credit access, overall, has significant positive effects on farm investments, such as land-building, livestock and machinery. It also has a significant positive effect on the farm revenue expenditure, including the expenditure on seeds, machinery, labour, irrigation, plant protection chemicals and livestock inputs. As a result, credit access has an incremental effect on farm income per hectare, livestock income and monthly consumption expenditure. The results imply that although farm credit policies have improved the welfare of beneficiary farmers, the credit distribution system seems to be inefficient as more than 60% of farmers do not have access to credit. This demonstrates that there is a need for inclusive and holistic policy interventions to include all farmers in the credit system, specifically offering term loans to small and marginal farmers. Apart from this, it is also suggested that simplified crop loan and Kisan Credit Card facilities be made available to tenant farmers.

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This manuscript has used secondary data of various published reports and the data are available for cross references.

A confounding variable is a variable other than desired one being studied that is associated with both the output variables and the factor being studied. In this study, confounding variables (e.g., age, education, farm size, etc.,) may distort the effects of credit access on the output variables in question (Austin, 2011 ).

Abebaw, D., Fentie, Y., & Kassa, B. (2010). The impact of a food security program on household food consumption in Northwestern Ethiopia: a matching estimator approach. Food Policy, 35 (4), 286–293.

Google Scholar  

Agbodji, A. E., & Johnson, A. A. (2019). Agricultural credit and its impact on the productivity of certain cereals in Togo. Emerging Market Finance and Trade . https://doi.org/10.1080/1540496X.2019.1602038

Article   Google Scholar  

Ahmed, M. H., Geleta, K. M., Tazeze, A., & Andualem, E. (2017). The impact of improved maize varieties on farm productivity and wellbeing: Evidence from the east Hararghe zone of Ethiopia. Development Studies Research, 4 (1), 9–21.

Austin, P. C. (2011). An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behavioural Research, 46 , 399–424.

Awotide, B. A., T. Abdoulaye, A. Alene, and V.M. Manyong. 2015. Impact of access to credit on agricultural productivity: Evidence from smallholder cassava farmers in Nigeria (No. 1008–2016–80242).

Banerjee, A. V. (2013). Microcredit under the microscope: what have we learned in the past two decades, and what do we need to know? Annual Review of Economics, 5 , 487–519.

Banerjee, A. V., Karlan, D., & Zinman, J. (2015). Randomized evaluations of microcredit: introduction and further steps. American Economic Journal: Applied Economics, 7 (1), 1–21.

Battese, G. E., & Coelli, T. J. (1992). Frontier production functions, technical efficiency and panel data: With application to paddy farmers in India. Journal of Productivity Analysis, 3 (1), 153–169.

Bauchet, J., & Morduch, J. (2013). “Is micro too small? microcredit vs SME finance. World Development, 43 , 288–297.

Benedetto, U., Stuart, J. H., Gianni, D. A., & Eugene, H. B. (2018). Statistical primer: propensity score matching and its alternatives. European Journal of Cardio- Thoracic Surgery, 53 (6), 1112–1117. https://doi.org/10.1093/ejcts/ezy167

Bhalla, G.S., & Singh, G. (2010). Growth of Indian Agriculture: a district level study, Planning Commission, Government of India. Available at http://planningcommission.nic.in/reports/sereport/ser/ser_gia2604.pdf .

Bhatt, M. S., & Bhat, S. A. (2014). Technical efficiency and farm size productivity-micro level evidence from Jammu & Kashmir. International Journal of Food and Agricultural Economics, 2 (4), 27–49.

Binswanger, H. P., & Khandker, S. R. (1995). The impact of formal finance on the rural economy of India. Journal of Development Studies, 32 (2), 234–262.

Bravo-Ureta, B. E., Solís, D., Moreira López, V. H., Maripani, J. F., Thiam, A., & Rivas, T. (2007). Technical efficiency in farming: a meta-regression analysis. Journal of Productivity Analysis, 27 (1), 57–72.

Brookhart, M. A., Schneeweiss, S., Rothman, K. J., Glynn, R. J., Avorn, J., & Sturmer, T. (2006). Variable Selection for Propensity Score Models. American Journal of Epidemiology, 163 (12), 1149–1156.

Buadi, D. K., Anaman, K. A., & Kwarteng, J. A. (2013). Farmers’ perceptions of the quality of extension services provided by non-governmental organisations in two municipalities in the Central Region of Ghana. Agricultural Systems, 120 , 20–26. https://doi.org/10.1016/j.agsy.2013.05.002

Caliendo, M., & Kopeinig, S. (2008). Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys, 22 (1), 31–72.

Cariappa, A.G.A., & Sendhil, R. (2021). Does Institutional Credit Induce on-Farm Investments? Evidence from India, 2021 Conference, August 17–31, 2021, Virtual 315221, International Association of Agricultural Economists.

Carter, M. R. (1989). The impact of credit on peasant productivity and differentiation in nicaragua. Journal of Development Economics, 31 (1), 13–36.

Chakraborty, T., & Gupta, A. (2017). Loan repayment behaviour of farmers: analysing indian households . Kanpur: IIT.

Chand, R., & Singh, J. (2022). Workforce changes and employment: some findings from PLFS data series. NITI Aayog Discussion Paper. New Delhi.

Coleman, B. E. (1999). The impact of group lending in Northeast Thailand. Journal Development Economics, 60 (1), 105e141. https://doi.org/10.1016/S0304-3878(99)00038-3

Coleman, B. E. (2006). Microfinance in Northeast Thailand: who benefits and how much? World Development, 34 (9), 1612–1638. https://doi.org/10.1016/j.worlddev.2006.01.006

Cornejo, J., & McBride, W. (2002). Adoption of bioengineered crops. Agricultural economics report No. 810. 1800 M street, NW, Washington, DC 20036–5831.

Dagar, V., Khan, M. K., Alvarado, R., Usman, M., Zakari, A., Rehman, A., Murshed, M., & Tillaguango, B. (2021). Variations in technical efficiency of farmers with distinct land size across agro-climatic zones: Evidence from India. Journal of Cleaner Production, 315 , 128109.

Datta, S., Tiwari, A. K., & Shylajan, C. S. (2018). An empirical analysis of nature, magnitude and determinants of farmers’ indebtedness in India. International Journal of Social Economics, 45 (6), 888–908.

Deaton, A. (1990) Saving in Developing Countries: Theory and Review . Proceedings of the World Bank Annual Conference on Development Economics 1989. The International Bank for Reconstruction and Development/World Bank.

Dehejia, R. H., & Wahba, S. (2002). Propensity score-matching methods for nonexperimental causal studies. The Review of Economics and Statistics, 84 (1), 151–161.

Dev, M.S. (2012). Small farmers in India: challenges and opportunities. Indira Gandhi Institute of Development Research, Mumbai, Working paper. http://www.igidr.ac.in/pdf/publication/WP-2012-014.pdf

Diagne, A., Zeller, M., & Sharma M. (2000) “Empirical Measurements of Households’ Access to Credit and Credit Constraints in Developing Countries: Methodological Issues and Evidence”. Food Consumption and Nutrition Division (FCND) Discussion Paper 90. International Food Policy Research Institute (IFPRI).

Diagne, A., & Zeller, M. (2001). Access to credit and its impact on welfare in Malawi (Vol. 116). International Food Policy Research Institute.

Eswaran, M., & Kotwal, A. (1990). Implications of credit constraints for risk behaviour in less developed economies. Oxford Economic Papers, 42 (2), 473–482.

FAO (Food and Agriculture Organization) (2012). Sustainable Crop Production Intensification . Twenty-third Session. Rome, Italy.

Ghalib, A. K., Issam, M., & Imai, S. K. (2011). The impact of microfinance and its role in easing poverty of rural households: estimations from Pakistan. Kobe University, 1 , 1–37.

Government of India (2019). Agriculture Census 2015–16. All India Report on number and area of operational holdings agriculture census division. Department of Agriculture, Co-Operation & Farmers Welfare Ministry of Agriculture & Farmers Welfare, New Delhi.

Guirkinger, C. (2008). Understanding the coexistence of formal and informal credit markets in Piura. Peru. World Development, 36 (8), 1436–1452.

Hazarika, G., & Alwang, J. (2003). Access to credit, plot size and cost inefficiency among smallholder tobacco cultivators in Malawi. Agricultural Economics, 29 (1), 99–109. https://doi.org/10.1111/j.1574-0862.2003.tb00150.x

Jayachandran, S. (2006). Selling labor low: wage responses to productivity shocks in developing countries. Journal of Political Economy, 114 , 538–575.

Joshi, P. K., Joshi, L., & Birthal, P. S. (2006). Diversification and its impact on smallholders: evidence from a study on vegetable production. Agricultural Economic Research Review, 19 , 219–236.

Karthick, V., & Madheswaran, S. (2018). Access to formal credit in the indian agriculture: does caste matter? Journal of Social Inclusion Studies, 4 (2), 1–27.

Khandker, S. R., & Faruqee, R. R. (2003). The impact of farm credit in Pakistan. Agricultural Economics, 28 , 197–213.

Khandker, S. R., & Koolwal, G. B. (2016). How has microcredit supported agriculture? Evidence using panel data from Bangladesh. Agricultural Economics, 47 (2), 157–168. https://doi.org/10.1111/agec.2016.47.issue-2

Kumar, A., Mishra, A. K., Saroj, S., & Joshi, P. K. (2017). Institutional versus non-institutional credit to agricultural households in India: Evidence on impact from a national farmers’ survey. Economic Systems, 41 (3), 420–432.

Kumar, A., Mishra, A. K., Sonkar, V. K., & Saroj, S. (2020). Access to credit in eastern india implications for the economic well-being of agricultural households. Economic & Political Weekly, 55 (21), 46–54.

Kumar, A., Singh, R. K. P., Jee, S., Chand, S., Tripathi, G., & Saroj, S. (2015). Dynamics of access to rural credit in India: Patterns and determinants. Agricultural Economic Research Review, 28 , 151–166.

Latruffe, L., Balcombe, K., Davidova, S., & Zawalinska, K. (2004). Determinants of technical efficiency of crop and livestock farms in Poland. Applied Economics, 36 (12), 1255–1263.

Luan, D. X., & Bauer, S. (2016). Does credit access affect household income homogeneously across different groups of credit recipients? Evidence from rural Vietnam. Journal of Rural Studies, 47 , 186–203.

Mal, P., Manjunatha, A. V., Bauer, S., & Ahmed, M. N. (2011). Technical efficiency and environmental impact of Bt cotton and non-Bt cotton in North India. AgBioforum, 14 (3), 164–170.

Malaiarasan, U., Paramasivam, R., & Felix, K. T. (2021). Crop diversification: Determinants and effects under paddy-dominated cropping system. Paddy and Water Environment, 19 , 417–432. https://doi.org/10.1007/s10333-021-00843-w

Manjunatha, A. V., Anik, A. R., Speelman, S., & Nuppenau, E. A. (2013). Impact of land fragmentation, farm size, land ownership and crop diversity on profit and efficiency of irrigated farms in India. Land Use Policy, 31 , 397–405.

Manogna, R. L., & Mishra, A. K. (2020). Price discovery and volatility spillover: an empirical evidence from spot and futures agricultural commodity markets in India. Journal of Agribusiness in Developing and Emerging Economies, 10 (4), 447–473.

Manogna, R. L., & Mishra, A. K. (2022). Agricultural production efficiency of Indian states: evidence from data envelopment analysis. International Journal of Finance & Economics, 27 (4), 4244–4255.

Mendola, M. (2007). Agricultural technology adoption and poverty reduction: a propensity-score matching analysis for rural Bangladesh. Food Policy, 32 (3), 372–393.

Mor, S., & Sharma, S. (2012). Technical efficiency and supply chain practices in dairying: The case of India. Agricultural Economics, 58 (2), 85–91.

Morduch, J. (1999). The microfinance promise. Journal of Economic Literature, 37 (4), 1569–1614.

NABARD (2018). NABARD All India Rural Financial Inclusion Survey - 2016–17.

Nanthakumaran, A., & Palanisami, K. (2013). Efficiency in sugarcane production under tank irrigation systems in Tamil Nadu, India. Journal of Environmental Professional Sri Lanka, 1 (1), 1–13. https://doi.org/10.4038/jepsl.v1i1.5138

Narayanan, S. (2016). The productivity of agricultural credit in India. Agricultural Economics, 47 (4), 399–409.

Nikoloski, Z., & Ajwad, M.I. (2013). Do economic crises lead to health and nutrition behavior responses? analysis using longitudinal data from Russia. World Bank Policy Research Working Paper No. 6538, Available at SSRN: https://ssrn.com/abstract=2297215

National Sample Survey Office (NSSO) (2003a). India - Situation Assessment Survey of Farmers: NSS 59th Round, Schedule 33, Ministry of Statistics and Programme Implementation, Government of India.

National Sample Survey Office (NSSO) (2013). All India Debt & Investment Survey: NSS 70th Round, Schedule 18.2, Ministry of Statistics and Programme Implementation, Government of India.

Ochieng, J., Knerr, B., Owuor, G., & Ouma, E. (2016). Commercialisation of food crops and farm productivity: Evidence from smallholders in Central Africa. Agrekon, 55 (4), 458–482.

Ogubazghi, S. K., & Muturi, W. (2014). The effect of age and educational level of owner/managers on SMMEs’ access to bank loan in Eritrea: evidence from Asmara City. American Journal of Industrial and Business Management, 4 (11), 632.

Pathania, A., Chaudhary, R., & Kumar, K. (2020). Analysis of Agriculture Input Consumption by Indian Farmers. International Journal of Economic Plants, 7 (2), 086–090. https://doi.org/10.23910/2/2020.0369

Pufahl, A., & Weiss, C. R. (2009). Evaluating the effects of farm programmes: Results from propensity score matching. European Review of Agricultural Economics, 36 (1), 79–101.

Quach, M. H., Mullineux, A. W., & Murinde, V. (2005). Access to credit and household poverty reduction in rural Vietnam: a Cross Sectional study . Edgbaston, UK: The University of Birmingham.

Rajeev, M., & Mahesh, H. P. (2014). The indian banking system: reforms and beyond. In J. S. Zajaczkowski & M. Thapa (Eds.), India in the contemporary world: polity, economy, and international relations. India: Routledge.

Ray, D. (1998). Development economics . USA: Princeton University Press.

Reddy, V. R., & Reddy, P. P. (2007). increasing costs in agriculture: agrarian crisis and rural labour in India. Indian Journal of Labour Economics, 50 (2), 273–292.

Richard, L. K., Job, L. K., & Wambua, T. R. (2015). Effects of micro credit on welfare of households: the case of Ainamoi Sub County, Kericho County, Kenya. Developing Country Studies, 5 (18), 72–80.

Robinson, M. (2001). The Micro-finance Revolution: Sustainable Finance for the Poor . Washington D.C.: World Bank.

Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70 (1), 41–55.

Rosenbaum, P. R., & Rubin, D. B. (1985). Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. The American Statistician, 39 (1), 33–38.

Shiferaw, B., Kassie, M., Jaleta, M., & Yirga, C. (2014). Adoption of improved wheat varieties and impacts on household food security in Ethiopia. Food Policy, 44 , 272–284.

Shoji, M., Aoyagi, K., Kasahara, R., Sawada, Y., & Ueyama, M. (2012). Social capital formation and credit access: Evidence from Sri Lanka. World DevelopMent, 40 (12), 2522–2536.

Sidhu, R. S., Vatta, K., & Kaur, A. (2008). Dynamics of institutional agricultural credit and growth in Punjab: contribution and demand-supply gap. Agricultural Economic Research Review, 21 , 407–414.

Singh, A. K., Narayanan, K. G. S., & Sharma, P. (2019). Measurement of technical efficiency of climatic and non-climatic factors in sugarcane farming in Indian states: use of stochastic frontier production function approach. Climate Change, 5 (19), 150–166.

Smith, J. A., & Todd, P. E. (2001). Reconciling conflicting evidence on the performance of propensity-score matching methods. American Economic Review, 91 (2), 112–118.

Sriram, M. S. (2007). Productivity of rural credit: a review of issues and some recent literature. International Journal of Rural Management, 3 (2), 245–268. https://doi.org/10.1177/097300520800300204

Staffa, J. S., & Zurakowski, D. (2018). Five steps to successfully implement and evaluate propensity score matching in clinical research studies. Anesthesia & Analgesia, 127 (4), 1066–1073.

Economic Survey (2015–2016). Ministry of Finance, Government of India, New Delhi.

Swain, R. B., Sanh, N. V., & Tuan, V. V. (2008). Microfinance and poverty reduction in mekong delta in Vietnam. African and Asian Studies, 7 (2–3), 191–215.

Tripathi, R. S., Dev, C., & Sharma, M. L. (1994). Variation of productivity of short-term credit used for wheat production in different zones of Uttar Pradesh Hills. Indian Journal of Agricultural Economics, 49 (3), 491–496.

Wu, W. (2020). Estimation of technical efficiency and output growth decomposition for small-scale rice farmers in Eastern India: A stochastic frontier analysis. Journal of Agribusiness in Developing and Emerging Economies, 10 (2), 139–156.

Wu, Y. (1995). Productivity growth, technological progress, and technical efficiency change in China: A three-sector analysis. Journal of Comparative Economics, 21 , 207–229.

Zeller, M., Schrieder, G., Von Braun, J., & Heidhues, F. (1997). Rural finance for food security for the poor – implications for research and policy . Baltimore: International Food Policy Research Institute.

Zeller, M., & Sharma, M. (2002). Access to and demand for financial services by the rural poor: a multicountry synthesis. In M. Zeller & R. L. Meyer (Eds.), The triangle of microfinance: financial sustainability, outreach and impact. Baltimore: International Food Policy Research Institute.

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Ramasamy, P., Malaiarasan, U. Agricultural credit in India: determinants and effects. Ind. Econ. Rev. 58 , 169–195 (2023). https://doi.org/10.1007/s41775-023-00187-8

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DOI : https://doi.org/10.1007/s41775-023-00187-8

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Journal of Agribusiness in Developing and Emerging Economies

ISSN : 2044-0839

Article publication date: 20 September 2022

This work examines the impact of institutional agricultural credit on crop productivity of some major crops such as paddy, cotton, wheat and pulses for small and marginal farmers across various social groups.

Design/methodology/approach

The cross-sectional field data on socio economic variables was collected from three Indian states from about 400 small and marginal farmers across various social groups using multi-stage stratified random and purposive sampling through a structured questionnaire by interviewing. The method of propensity score matching (PSM) was employed to calculate average treatment effect (ATE) and average treatment effect on the treated (ATET) by categorising sample farmers as treatment group and control group where crop productivity was considered as outcome variable and access to institutional credit was considered as treatment variable.

The PSM estimates reveal that ATE and ATET for all the selected crops are found to be significantly higher for the treated group vis-à-vis non-treated group suggesting that institutional agricultural credit has a statistically and significant positive impact on the crop productivity.

Research limitations/implications

Similar study can be extended for more crops and across regions in India for a universal coverage.

Originality/value

The agricultural credit policy of India has been to increase the access and availability of institutional farm credit. This has led to in general increase in the flow of formal farm credit to agricultural sector. However, the impact of institutional credit and crop productivity especially for small and marginal farmers across social groups is not well recognized in India using field data. Accordingly, this field data study contributes to the existing research by providing fresh evidence from field across social groups for both kharif and rabi crops using recent survey data from small and marginal farmers which has important policy implications.

  • Institutional agricultural credit
  • Small and marginal farmers
  • Crop productivity
  • Social groups
  • Propensity score matching

Acknowledgements

Funding: This study was funded by Ministry of Education (MoE), Government of India under the Impactful Policy Research in Social Science (IMPRESS) supported and implemented by Indian Council of Social Science Research (ICSSR), New Delhi, India. The funding of MoE, Government of India and ICSSR is greatly appreciated.

Yadav, I.S. and Rao, M.S. (2022), "Agricultural credit and productivity of crops in India: field evidence from small and marginal farmers across social groups", Journal of Agribusiness in Developing and Emerging Economies , Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JADEE-05-2022-0092

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This is the second part of the article "Perspectives on Agricultural Credit in India" published in Third Concept (December 2014).

Advances in Life Sciences

Credit is one of the critical inputs for agricultural development. It capitalizes farmers to undertake new investments and/or adopt new technologies. Realizing the importance of agricultural credit in fostering agricultural growth and development, a study has been conducted to analyse the trends and impact of agricultural credit in India. The study was conducted based on secondary data collected from various sources such as government websites, annul reports of NABARD, Indiastat etc. The data were analysed using various techniques such as compound annual growth rate, standard deviation, instability index, analysis of variance and simple regression analysis. The study revealed that in the production credit (short term credit), highest compound annual growth rate was showed for commercial banks (25.66%) and in the case of medium term or long term loans for agriculture, regional rural banks showed a higher rate of growth with 17.74 per cent. The commercial banks are the major providers of agricultural credit at the ground level with a contribution 71 per cent. The ANOVA (single factor) results revealed that there is significant difference between the mean values of loans issued and loans outstanding among cooperative banks, commercial banks and regional rural banks. The simple linear regression analysis also depicted that agricultural credit has significant contribution in the agricultural GDP of the country and also on the agricultural exports from India.

The paper is aimed at highlighting the scope to strengthen Agriculture Finance system for the comprehensive growth of agriculture, food security and rural development. The scope of Agriculture Finance was limited to increase productivity by introduction of high yielding seeds, use of chemical fertilizers and pesticides, and making availability of institutionalized credit for purchasing the preceding inputs. Agriculture Finance till today was addressing institutionalization of credit at farmers’ level in marketing, trade, processing and agribusiness. The study reveals that; though the institutional credit in India to agriculture sector is increased in quantum, serious efforts are required to provide it to the right kind of people, at right time, on right places and in right quantity; that boost Indian agriculture sector in a right way.

Artha Vijnana

Deepak Shah

A sample of 50 households (25 households each from Kolhapur and Pune) was chosen over the period 1995-96 - 1999-2000 to basically study the credit experience of farming families depending on land holding size. Relative importance of formal and informal credit agencies in aggregate loans taken by small, marginal and large farmers, purpose of the loans, default rates, prevalence of excess demand for loans, if any have been analysed. One novel idea employed in the paper is that instead of credit rating agencies assessing the loan repayment capability of borrowers. the authors find out the length of relationship between a lender and its borrowers. Thus, small and marginal farmers may be seen to be the most trusted partners of cooperatives.

Kumardatt Ganjre

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