Demographic Composition and Socio-Economic Divide: Evidence from Caste-Based Survey of Bihar

Many countries around the world have recognized the importance of caste- or race-based enumeration in promoting inclusive development and equality. In India, caste continues to be one of the most persistent and rigid forms of social segmentation. However, detailed caste data has been absent from the national census since 1931. This lack of caste-disaggregated data hampers the effective design, evaluation and implementation of government policies. In response, several Indian states have undertaken independent initiatives. In this context, the Government of Bihar conducted and released the Jaati Adharit Ganana (Caste-Based Survey) in 2023, an extensive caste enumeration exercise. The present study aims to represent a comprehensive analysis of the 2023 Bihar Caste-Based Survey. The study examines the demographic composition, socio-economic disparities across castes, and factors affecting employment through regression analysis. Key findings highlight that the Extremely Backward Classes (EBCs) constitute the largest group (36.01 percent), and together with the Other Backward Classes (OBCs), account for 63 percent of Bihar’s population. The data reveals significant socio-economic challenges: only 1.5 percent of individuals hold government jobs, 34.13 percent of families subsist on less than ₹6,000 per month, 95.49 percent do not own a vehicle, only 7 percent of the population are graduates (with fewer than 1 percent holding postgraduate degrees), and nearly 99 percent lack access to a computer or laptop. Ordinary Least Squares (OLS) regression results show that technical education, ownership of two-wheelers, and access to computers (with or without internet) significantly improve employment prospects. These findings highlight the crucial role of skills, mobility, and digital access in enhancing employability. Moreover, the study reveals that even within broadly disadvantaged categories, specific jatis continue to experience deeper layers of exclusion and inequality. Nonetheless, the paper also raises serious concerns about the reliability of the data, pointing to potential discrepancies and methodological limitations, especially in light of the government’s decision not to disclose micro-level data.