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Article type: Research Article
Authors: Kumar, Vikas
Affiliations: Azim Premji University, Bengaluru 560100, India | E-mail: vikas.kumar@apu.edu.in
Correspondence: [*] Corresponding author: Azim Premji University
Note: [1] The author is grateful to anonymous referees and Ankush Agrawal for insightful comments on the paper and to government officials in Kohima, Imphal, New Delhi and Senapati for helpful discussions. This paper is an expanded and updated version of “The Limitations of India’s Census Legislation”, Azim Premji University Working Paper No. 13. The usual disclaimers apply.
Abstract: Most discussions on data quality overlook the legal framework within which data are collected. This paper examines India’s Census Act, 1948 that provides the legal framework for conducting population censuses. The Act stipulates punishment for interfering with the process of enumeration but the punitive provisions have not been invoked to deal with cases of widespread manipulation of census. Major instances of manipulation were reported in 1951 and 2001 after the government introduced additional punitive measures in 1948 and 1994, respectively. The paper identifies the structural flaws of the Census Act, 1948 vis-à-vis manipulation. It compares the Act with other Indian laws on the collection of statistics and census laws of other common law countries. It shows that fines are very small compared to per capita income in most countries and yet violators are rarely fined. The paper uses simple games to explain why the punitive provisions might be redundant and suggests that the problem of interference with government statistics can possibly be addressed without recourse to law. The insights drawn from the games are examined in light of the experience of Nagaland and other states of India where census statistics were affected by widespread manipulation in the recent decades.
Keywords: Census, common law, conflict, data quality, game theory, India, Jammu and Kashmir, law, manipulation, Manipur, multiple equilibria, Nagaland, Punjab
DOI: 10.3233/SJI-200651
Journal: Statistical Journal of the IAOS, vol. 36, no. 4, pp. 1143-1160, 2020
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