Access and Determinants of Formal Agriculture Credit In Uttar Pradesh, India


  • Surendra Singh Jatav Assistant Professor,Department of Economics, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India.
  • Sanatan Nayak Professor, Department of Economics, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India.



Indebtedness, Nsso, Rural Credit, Logistic Regression Model, Uttar Pradesh, Regional Credit Disparities .


The study has attempted to examine the determinants of formal agricultural credit in rural Uttar Pradesh using National Sample Survey Organisation data from the 70th round (2012–13). The Binary Logistic Regression (BLR) model is used to examine the determinants of formal credit in Uttar Pradesh. Socio-economic and demographic characteristics such as age, gender, social group, and family size are grouped into social, economic, and extension services. The findings from this study revealed that indebtedness exists and that almost 45 per cent of farmers have taken credit from informal credit agencies. Further, there is significant heterogeneity in terms of socio-economic and demographic features among farmers who have taken credit from formal and informal credit agencies. The BLR results show that gender, literacy rate, operated area, bank account, livestock, and Kisan Credit Card are key social and economic determinants of formal credit in rural Uttar Pradesh. The calculated odds ratio shows a 2.008 times higher probability of literate male farmers taking a loan from formal credit than others. Likewise, there is a 3.10 times higher probability of taking formal credit if farmers follow technical advice provided by agricultural universities, NGOs, and scientists through open-source platforms. Hence, the following policies are suggested to deal with indebtedness: (i) Policymakers can choose to intervene in the rural credit lending system by liberalising policy to more accurately reflect the characteristics of potential borrowers and in light of their current borrowing strategies, (ii) the BLR results depict a positive relationship with land size, and agricultural households with larger land seem to get more benefits. Therefore, the government should focus on marginal and small farmers, who have larger shares in the total operational landholdings, (iii) safety net programmes like the Public Distribution System (ration cards), in the presence of formal credit, may induce farmers and their families to increase their per capita monthly consumption expenditures, and (vi) State intervention is also required in terms of increasing the size of livestock, as this can be an area where Uttar Pradesh can lead the other States as this will help in diversification in the field of agriculture .


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How to Cite

Jatav, S. S., & Nayak, S. (2023). Access and Determinants of Formal Agriculture Credit In Uttar Pradesh, India. Journal of Rural Development, 41(2), 185–197.


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