The majority of deletions in electoral rolls under the ongoing Special Intensive Revision (SIR) exercise can be explained by de-duplication of multiple entries, this newspaper argued on Thursday. The argument was based on a strong correlation between districts by their share in state-wise growth in electors and share in deletions as seen in the draft roll released immediately after the enumeration phase. To be sure, as that analysis pointed out, this circumstantial evidence needs to be backed by more data
- There is a large PC-wise variation in growth in electors between 2009 and 2024 in IndiaThe number of registered voters in India increased from 717.9 million in 2009 – it is the earliest period for which we have comparable parliamentary constituency (PC) boundaries – to 980.8 million in 2024, an increase of 36.7%. As is to be expected, there is a large state-wise variation in this trend with Uttar Pradesh leading the ranking and Delhi at the bottom among major states and union territories which have at least seven PCs. What is even more interesting, however, is the variation at the PC-level where the 10th and 90th percentile value differ by a multiple of 2.5. Even a cursory look at some of the really high voter growth PCs suggests that there are two clear drivers of voter growth in this period. There are PCs such as Faridabad, Gurgaon, Sriprerumbudur and Gautam Buddha Nagar (Noida), that have seen a large economic growth and perhaps in-migration during this period. But then there are also PCs such as Maldah Uttar and Dakshin in West Bengal which are more likely to have high population growth than migration for economic reasons.
- Most migrant importing states show a larger variation in voter growth than in TFRHad the 2021 census been conducted on time, we would have known the exact number of voting age people in every district of India and could have generated a reasonably accurate mapping of these numbers with the number of electors. The 15-year long gap between census population figures means that this cannot be done and we are in the dark as far as the net impact of migration and births and deaths on the number of voters is concerned. One way to approximate the dynamics of this flow can be to compare the variation in TFR (total fertility rate) in the 2015-16 National Family and Health Survey (NFHS) -- the earliest NFHS round after the 2011 census -- across districts and elector growth across PCs between 2009 and 2024. States where migration played a bigger role in driving up voter counts should see a bigger variation in voter growth than TFR numbers. Migrant importing states such as Gujarat, Telgangana, Maharashtra, Kerala, and Delhi indeed show much higher values of coefficient of variation -- it is the standard devaition divided by the mean of a distribution -- for PC-wise voter growth than respective values for district-wise TFR. To be sure, a state need not be a inter-state migrant importing one for this to hold true. Even states with high intra-state migration can show higher variation in voter growth than in TFR.
- And electors are less likely to overshoot voting age population in migrant importing districtsLet us take the state of Uttar Pradesh as an example. A district-wise matching of voting age population from the 2011 census and voters in the 2012 assembly election shows that the count of electors overshot the voting age population by a smaller degree in the intuitively migrant importing districts (not just inter- but also intra-state). The opposite was true for migrant exporting districts. Once again, this confirms the argument we made yesterday that even though voting age adults were recorded as living in some other place in the census, they were still registered as voters in their native places. All of these claims would be significantly stronger if we had census data of a more recent vintage. Hopefully, we will be able to revisit some of these arguments when the census data becomes avialable in 2027.
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.
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.