Business News/ Economy / Consumption data exposes the depths of India’s caste divide
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Last month, the Supreme Court allowed states to sub-classify the broader scheduled caste (SC) and scheduled tribe (ST) groupings to determine sub-quotas. The rationale is that these groups are ‘not homogenous’; some particularly disadvantaged sub-groups may need greater protection. The latest consumption spending survey gives us a sneak peek into some data that could help us stitch together how well this adds up.
Last month, the Supreme Court allowed states to sub-classify the broader scheduled caste (SC) and scheduled tribe (ST) groupings to determine sub-quotas. The rationale is that these groups are ‘not homogenous’; some particularly disadvantaged sub-groups may need greater protection. The latest consumption spending survey gives us a sneak peek into some data that could help us stitch together how well this adds up.
India has over 3,000 castes, of which 1,200 are listed as scheduled castes. But government surveys collect data only for the four broad social groups: STs, SCs, Other Backward Classes (OBCs) and a residual category called ‘Others’—a shorthand for traditionally dominant castes. Despite this limitation, it’s possible to gauge economic inequality levels both within and among these four groups using the Household Consumption Expenditure Survey (HCES) held in 2022-23. Its raw data allows us to classify households based on their monthly spending patterns.
India has over 3,000 castes, of which 1,200 are listed as scheduled castes. But government surveys collect data only for the four broad social groups: STs, SCs, Other Backward Classes (OBCs) and a residual category called ‘Others’—a shorthand for traditionally dominant castes. Despite this limitation, it’s possible to gauge economic inequality levels both within and among these four groups using the Household Consumption Expenditure Survey (HCES) held in 2022-23. Its raw data allows us to classify households based on their monthly spending patterns.
Test of ‘homogeneity’
The extent of inequality is captured through an index called the Gini coefficient. It runs from 0 to 1, with 0 reflecting perfect equality and 1 meaning that all spending is by a single person. The closer it is to zero, the lower the likely gap between the spending patterns of two individuals picked at random.
The Gini coefficient of monthly per capita consumption expenditure (MPCE) at the all-India level was 0.317 in 2022-23, the survey showed. But this was largely driven by the ‘Others’ group (0.332). All the other three groups were less unequal, with those from SCs being relatively the most ‘homogenous’, with a Gini coefficient of 0.275. Those belonging to STs had a Gini coefficient of 0.295 and OBCs were at 0.301.
The trend of SC groups being significantly less unequal than the so-called upper castes is true in all major states. Bihar stands out as the least unequal for SC individuals (Gini coefficient of 0.197), and Maharashtra the most unequal (0.298). But this is in line with their overall inequality levels: Bihar and Maharashtra, respectively, are also the least and the most unequal among major states.
Beyond this, not much can be gauged from the HCES data on the disparities between the different castes within the broad classification. Therefore, the only way to understand the court’s verdict would be to have detailed data collection on caste-wise representation in education and employment.
‘Upper’ castes way ahead
However, this simple analysis indicates that the disproportionate influence of certain caste or class groups may be a larger problem among the ‘upper castes’ than among SC/ST groups. An average Indian belonging to a scheduled tribe consumes goods and services worth ₹3,260 per month. This goes up to ₹3,859 for SC persons, ₹4,497 for those from the OBCs, and ₹5,618 for ‘Others’. That means the average ‘upper-caste’ Indian spends 1.5 times what the average SC person does. This gap is particularly high among major states such as Chhattisgarh, Telangana, Rajasthan and Jharkhand.
Arguments calling for affirmative action based on economic position rather than caste identity often cite the presence of a ‘creamy layer’ among SC/ST groups and poverty among the so-called upper castes. While there are rich households among the SC/ST groups, a like-to-like class comparison immediately makes clear the staggering extent of inequality.
The average spending by the poorest 10% of SC individuals was ₹1,619 per month, compared to ₹2,012 among the poorest 10% of the ‘Others’. The average spending for the richest 10% of SCs was ₹8,906 compared to ₹15,193 for the richest 10% among ‘Others’.
In other words, inequality exists even at the bottom and at the top of the consumption ladder, and not just in averages. The poorest among the dominant caste groups are richer than the poorest among the STs and SCs. The gap increases at higher deciles. The richest 10% of the ‘Others’ spend almost two times what the richest 10% among the ST and SC spend.
Unequal representation
Another aspect related to the persistence of caste-based inequality in India is the representation of caste groups among economic classes and positions of power. Roughly 10% of the population sampled in the HCES belongs to the STs, 20% to the SCs, 45% to the OBCs, and 25% are the ‘Others’. In a casteless society, each national decile would have representation from the four social groups in line with their population share (i.e. among the poorest 10% Indians, 10% would be STs, 20% would be SCs, and so on). But the data shows that the SC/STs are overrepresented among the poor, and ‘Others’ are overrepresented among the rich.
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STs and SCs together account for 30% of the total population, but 50% of the poorest 10%. Among the richest 10% of the population, only 13% belong to the SC/STs, while 44% belong to the ‘Others’.
A higher representation among the top economic classes likely provides the so-called ‘upper caste’ groups disproportionate influence over important institutions that shape the policy of representation and redistribution in the country.
Debating reservations ad nauseam in the context of the ever-declining number of public sector jobs does not even begin to capture the problem of persistent caste-based inequality. For a serious discussion on social justice in India, it’s essential to look at the problem of unequal distribution in its totality. A socio-economic caste census could be one way to collect more data to inform this discourse.
(Ishan Anand is an assistant professor of economics at IIT Delhi.)
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