Caste disparities in institutional credit access and their implications for sustainable development in rural India

Abstract Equitable access to institutional credit is crucial for enhancing the productivity and livelihoods of rural households, particularly in agrarian economies like India. Despite multiple financial inclusion programs, disparities persist across caste groups. This study examines caste-based exclusion in institutional credit among agricultural households using unit-level data from the 77th round of the National Sample Survey (2019). Employing probit regression, we identify key determinants of credit access, while the Blinder–Oaxaca decomposition quantifies the explained (structural) and unexplained (discriminatory) components of disparities. Results show that Scheduled Castes (SCs) and Scheduled Tribes (STs) are significantly less likely to access institutional credit compared to Upper Castes (UCs), with the unexplained discriminatory component accounting for 42% of the gap for SCs, 60% for STs, and 8% for Other Backward Classes (OBCs). Limited landholdings, lower monthly per capita expenditure (MPCE), and reduced education levels contribute to structural disadvantages, while systemic bias further restricts access. The findings highlight that, despite targeted programs such as the Kisan Credit Card (KCC) and Pradhan Mantri Jan Dhan Yojana (PMJDY), implementation gaps and social exclusion hinder equitable credit distribution. Addressing such disparities is critical not only for social justice but also for achieving Sustainable Development Goals (SDGs) related to poverty reduction, reduced inequalities, and decent work. The study calls for caste-sensitive lending policies, improved awareness and outreach in marginalized communities, and monitoring mechanisms to ensure fair credit allocation. By quantifying both structural and discriminatory barriers, this research contributes actionable insights for policymakers to promote inclusive rural development.