02307nam a22001457a 4500 533873 533873 260709b ||||| |||| 00| 0 eng d Bhat, Showkat Ahmad Paltasingh, Kirtti Ranjan Mir, Ab Hamid and Hamid, Ishfaq 61561 Institutional credit and farm technical efficiency: Evidence from a field experiment using stochastic frontier analysis International Journal of Rural Management 22(1), Apr, 2026: p.115-135 This study examines the impact of access to formal credit on the technical efficiency of farms. The stochastic frontier analysis (SFA) is used to estimate technical efficiency by utilising primary survey data collected through a multi-stage random sampling technique. The results reveal that technical efficiency scores range from 0.56 to 0.97. There is a relatively high level of technical efficiency among borrower households (score 0.88) compared to non-borrower households (score 0.67), which implies that credit access enables farmers to use better technologies and optimise input use. The major inputs, such as labour, chemicals, machinery and farm size, are positively associated with farm technical efficiency, whereas land tenancy, seed price and fertilisers tend to decrease farm efficiency. The gamma coefficient (0.76) justifies the application of SFA, implying that inefficiency in the farm inputs is more likely than random shocks. In addition, the age of the household head, farming experience, education, occupation, membership, farm size, household assets and access to credit are the primary factors determining efficiency. These findings highlighted the requirement to have policy interventions in order to improve the socio-economic environment, institutional support, access to credit and managerial skills of farmers, which would increase productivity and achieve sustainable agricultural development.- Reproduced https://journals.sagepub.com/doi/full/10.1177/09730052261423707?_gl=1*aqeh6a*_up*MQ..*_ga*MTIwOTEwMjg3 NS4xNzgzNTg5MjE2*_ga_60R758KFDG*czE3ODM1ODkyMTUkbzEkZzEkdDE3ODM1ODkyNjMkajEyJGwxJGg1OTk5NjEwOTg. Technical efficiency, stochastic frontier analysis, Agricultural credit, Tobit regression. 61562 International Journal of Rural Management AR 0 0 ddc 0 0 409051 IIPA IIPA 2026-07-09 22(1), Apr, 2026: p.115-135 AR139332 2026-07-09 AR