When Prime Minister Narendra Modi urged Indians to cut down on gold purchases and foreign travel amid concerns over India’s external balance, he was subtly hinting towards a deeper problem in the Indian economy. There is now a significant cohort of Indians whose lifestyle is at par with the rich in high-income countries and who are way ahead of how ordinary Indians earn and spend. This cohort seems to have become bigger over time, as is seen in India’s rising
- The really-rich have seen the lowest increase in spending after reformsIndia’s first income survey is in the process of being conducted. Existing estimates of inequality are based on consumption expenditure surveys (CES) conducted by the National Statistical Office (NSO). Comparing the monthly per capita expenditure (MPCE) of the entire CES, top 10%, top 5% and top 1% between 1993-94 and 2023-24 CES rounds -- the earliest and latest after 1991 reforms -- shows that top 1% have seen the lowest proportionate increase in their MPCE. The catch up of the masses vis-à-vis the classes is almost entirely a result of the former’s high growth in non-food spending.
- Inequality seems to have fallen even within the really richThanks to the trend described above, India’s consumption inequality has fallen in the post-reform period. The Gini coefficient -- the most widespread statistical measure of inequality where 0 shows perfect equality and 1 perfect inequality -- has fallen from 0.33 in 1993-94 to 0.29 in 2023-24. What about inequality within the really rich though? It makes sense to ask this question because it is eminently likely that the super-rich (those who own luxury cars, for example) are still a very small part of the rich (say, those who own a car) and only the former has seen incomes rise. Data seems to suggest otherwise once again. Intra-class Gini has seen the sharpest fall among the richest classes between 1993-94 and 2023-24.
- Is the CES data just counter-intuitive or really not representative?This is the crux of the debate around India’s official inequality estimates. If the CES does not measure the spending of the really rich, it will tend to underestimate inequality. Going deeper into the CES data buttresses theories of the survey undercounting the really rich. For example, the most expensive vehicle bought by a household in the 2023-24 household consumption expenditure survey (HCES) cost just ₹45 lakh. The share of such households in the HCES is eight households per million. This does not really seem to fit consumption standards of India’s super rich. For example, according to the Ministry of Road Transport’s Vahan dashboard, 4,128 Jaguar, 877 Porsche, 92 Lamborghini, 72 Bentley, 54 Rolls Royce, 40 Ferrari, 15 Maserati, 11 McLaren, and six Aston Martin four wheelers were registered in the country in FY 2023-24, makers that typically sell cars priced significantly above ₹45 lakh in India. This non-exhaustive count of 5,295 registrations amounts to a share of 16 households per million using population projections and household size from the HCES. The CES might be undercounting the rich at a wider level than just luxury cars. The share of households/population who spent on air travel in 2011-12 and 2023-24 shows a decline: from 649 households/775 people per million to 471 households/469 people per million. The number of domestic air passengers in India increased from 60.8 million to 153.7 million during this period, according to the Directorate General of Civil Aviation (DGCA), which translates to roughly 49,993 departures per million and 1,10,391 departures per million people in 2011-12 and 2023-24 respectively. This means that the average Indian air traveler would have to take 235 trips in 2024-25 instead of 65 in 2011-12 annually for the HCES data to be correct.
- ConclusionIf the CES is undercounting air travelers, can it be trusted to represent people spending on even higher value goods and services? And if the super-rich are undercounted, how credible are its estimates of economic inequality? This does not, however, mean the CES is a useless statistical database. Sure, it tends to undercount the rich, but it also gives a treasure trove of information on the economic condition of a vast majority of Indians. The numbers above only tell us that one should take the inequality measures from the CES data with some amount of skepticism.
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.
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.