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Number Theory: What Bihar caste census data does not tell us

Without taking away anything from the importance of the data which has been released, here are some aspects which have been left unaddressed

Updated on: Nov 9, 2023, 13:05:00 IST
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By publishing data on population by sub-caste, and socio-economic attributes, Bihar has become the first state in India to give official data at the sub-caste level. While unit-level release of these caste survey data will lend itself to a far more detailed analysis, even the released numbers provide a lot of information about socioeconomic inequality at not just the broad social group-level, but also at the level of sub-castes.

The Nitish Kumar government released socio-economic caste survey data this week (PTI)
The Nitish Kumar government released socio-economic caste survey data this week (PTI)
What Bihar caste census data does not tell us
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    Number Theory: Biggest omission in the data is a rural-urban break-up
    If there is one thing that stands out in the caste survey data which was released on November 7, it is the fact that more than one-third of the state’s households earn less than 6,000 per month, which is what the state government has taken as a threshold for being poor. Data shows that the share of poor households is as high as 25% even among the population which does not belong to Scheduled Caste (SC), Scheduled Tribe (ST), or Other Backward Classes (OBCs). This suggests that there is more to poverty in the state than just the caste background of a person. Here is where a rural-urban split in the data would have helped. According to the 2011 census – the 2021 census has been delayed indefinitely – Bihar was the most rural among India’s states with a population of at least 10 million.
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    Rural incomes are lower than urban incomes across India
    Not only is this intuitive, multiple surveys show this conclusively. For example, the latest Periodic Labour Force Survey (PLFS) shows that urban incomes across work categories were significantly higher than rural incomes in the country. The advantage of urban incomes over rural incomes holds for different social groups as well.
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    PLFS data shows that upper castes are the most urbanised social group in Bihar
    2022-23 PLFS data shows that the population which does not belong to the SC/ST/OBC group is the most urbanised in Bihar. To be sure, most urbanised is a relative term in this case because Bihar’s 13.9% urban share for non-SC/ST/OBC population is still lower than the national average of urban population for India. It is entirely likely that difference in rural-urban domicile is a much bigger driver of poverty, and perhaps wealth, in the state than social background of a person in Bihar. For example, anybody who knows that state will agree that Kayasths, who have the lowest poverty ratio among all sub-castes in the state, are the most urbanised social group in Bihar. Had the Bihar caste census published these results at the sub-caste level, it would have provided valuable information about social differentiation in urbanisation in the state.
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    Lack of rural-urban data also keeps the question of agrarian transformation in the dark
    19.9% of Bihar’s GSDP came from agriculture in 2022-23. In July 2022-June 2023, 49.6% of the state’s workforce was engaged in agriculture. Both these numbers are significantly higher than the national average of 15.1% and 45.8% respectively. This also makes it clear that unless things improve on the agrarian front, upward mobility will continue to elude the state. However, any programme which seeks to increase incomes in agriculture could have a differential impact in case of unequal land ownership. While the political narrative has always harped on an upper caste dominance in land ownership, official data suggests that the balance of land ownership is not as unfavourable to OBCs as it is made out to be. Data from the Situation Assessment Survey (SAS) of agriculture conducted in 2018-19 shows that while the share of agricultural households – it is defined as rural households with at least one member self-employed in agriculture and agricultural output (including animal farming) of at least 4,000 in 2018-19 – among OBCs with a higher size class of land is lower than the non-SC/ST/OBC population with a higher size class of land, in absolute terms the number of OBC agricultural households owning bigger land holdings is larger than the non-SC/ST/OBC group. It has often been argued that dominant OBCs – they would come under the Backward Classes in the Bihar caste census – own much more land than Extreme Backward Classes. By not collecting and publishing sub-caste wise land ownership data, the Bihar caste census has let go of an important opportunity to tell us more about this inequality.
  • Roshan Kishore
    ABOUT THE AUTHOR
    Roshan Kishore

    Roshan Kishore is the Data and Political Economy Editor at Hindustan Times. He heads the newsroom's data journalism team, which produces Number Theory, a daily data-driven feature for the print edition and the HT app. Number Theory uses data analysis and story-telling based on it to add value to the newsroom’s daily coverage by putting stories in a larger context on a range of issues, including politics, macroeconomy, markets, global affairs and climate. Under his leadership HT’s data journalism work has established itself as a niche product in Indian journalism and pushed the boundaries of marrying academic rigour with news sense and speed. Along with writing and editing data stories, he has also been writing a weekly political economy column called Terms of Trade for HT Premium. A trained economist with an MPhil degree from Jawaharlal Nehru University, Kishore has also been a visiting fellow at the Centre for Advanced Studies of India (CASI) at the University of Pennsylvania. Along with his journalistic work, his writings have also appeared in journals such as the Economic and Political Weekly and working papers for CASI and UNESCAP.Read More

  • Abhishek Jha
    ABOUT THE AUTHOR
    Abhishek Jha

    Abhishek Jha is Assistant Editor-Data at Hindustan Times. He uses statistical programming to generate newsworthy insights from large datasets. He is part of the team that produces Number Theory, a daily data story feature of the paper’s print edition. Since March 2024, he has been writing Weather Bee, a weekly column for the Hindustan Times website. He is a chemical engineer by training, who specialises in stories related to weather, climate, and the environment. Jha has been at HT since 2018, where he offers data-driven perspective and analysis on politics, environment, weather, climate, economy and society. His work includes data coverage of elections in India and abroad, including the 2019 and 2024 Lok Sabha elections; the disasters and extreme weather resulting from changing climate, such as floods, droughts, heat waves, cold waves, and dwindling snow cap in the Himalayas; the factors that drive poor air quality in northern India; the changing patterns of land use; the Covid-19 pandemic and its impact on labour market conditions; the changing pattern of consumer spending seen in the new consumer spending surveys; and social norms seen in the surveys such as the National Family Health Survey.Read More

  • Nishant Ranjan
    ABOUT THE AUTHOR
    Nishant Ranjan

    Nishant Ranjan has been working as a data journalist with Hindustan Times since 2023. In this short period, he has established a niche for creating original datasets and utilising them to produce journalistic work that pushes the boundaries of journalism. The list of datasets and stories done by him include the following: a dataset of all 717 chief ministers India has had since 1952, a dataset of all 3,350 members of India’s council of ministers, a dataset of all 190 deputy chief ministers in India and a dataset of all 279 Supreme Court judges in India (1950-2025). He has also profiled each elected Muslim MLA/MP since 1952. He is a mining engineer by training who decided to pursue a Master's in Development Studies from TISS after working in a coal mine for 10 months. He also worked as a research associate at the Centre for Policy Research, researching local governance in India. He also has a keen interest in analyzing electoral politics and political executives in India.Read More