New Delhi: Just about two weeks ago, the author wrote a column arguing that India’s housing statistics obscured two distinct markets moving in divergent directions, with the national slowdown figures misleading by omission rather than error. This argument was based on a city-level dataset covering seven cities in a single sector over one quarter, as captured by Anarock’s tracker and Proptiger’s Real Insight report.
A PRICE and Tata Sons’ new report now evaluates the argument across different aspects of the economies of 100 cities across the nation on a broader scale, examining urban income, spending, saving, and debt over a decade.
The findings reinforce the broader argument that national aggregates can conceal sharply different realities at the city level.
Moreover, the report reveals a particularly notable data point: a city with a population under 1.5 million, positioned at the lowest tier of a four-tier population hierarchy, shares the highest average household income in India with the nation’s tech capital and surpasses all megacities in expenditure.
This city is Chandigarh, which the report designates as a Frontier City (among the lowest average household income), a classification unrecognised by its households.
The observed anomaly of a ‘Frontier City’ with high average household income’ serves as an entry point into a broader pattern, as Chandigarh is not an isolated case. When India’s 100 largest cities are ranked by population, as the report does, four distinct categories emerge: the Big Six, Boomtowns, Breakout cities, and Frontier cities.
These categories provide a defensible framework for organising a country of this magnitude. However, defensible is not the same as descriptive. Notably, none of India’s top five cities by household spending is among the six megacities classified as the pinnacle.
Chandigarh and Thiruvananthapuram, categorised as a Frontier city and a mid-sized Boomtown, respectively, surpass Mumbai, Delhi, and Bengaluru in per-household spending. This phenomenon reflects the housing narrative at the city level rather than the price-tier level.
Joan Robinson’s 1933 analysis of imperfect competition, which explained why India’s housing supply skewed toward luxury rather than the mass market despite a stable national sales figure, describes this type of market segmentation: a seemingly unified market that,
in reality, comprises several distinct markets catering to buyers with divergent behaviours. Population size, like a single quarter’s sales figure, was never meant to capture such nuances.
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Why India’s richest city saves what its poorer ones spend
Once the fracture becomes apparent at the city level, the same logic extends further into households within a single tier. Even among the Big Six cities, disparities in income and expenditure emerge that are not reflected in population figures.
Bengaluru, for instance, has the highest annual average household income among the Big Six, amounting to Rs 28.3 lakh. Yet, it allocates only 54.1 percent of this income to spending, the lowest proportion in the country. In contrast, Chennai’s income is one-third less, at Rs 18.9 lakh, but it allocates 67 percent to spending, the highest proportion among the six cities.
Chandigarh’s classification requires an immediate clarification: it does not accurately reflect the tier under which it is categorised.
Frontier cities, as a group, have the lowest average household income among the four tiers, at Rs 12 lakh, and the highest proportion of financially strained households nationwide, with one in four experiencing chronic or periodic difficulty meeting routine expenses.
Chandigarh does not prove that smaller cities have hidden wealth. Instead, it demonstrates that a tier comprising fifty cities, based solely on population size, can encompass both the highest and most vulnerable household averages in the country. The classification system cannot identify a city’s specific economic status without further examination.
When one looks at the nature of income rather than its magnitude, the reason Bengaluru saves what Chennai spends becomes clear. According to Milton Friedman’s Permanent Income Hypothesis, articulated in his 1957 work, “A Theory of the Consumption Function,” households base their spending on anticipated lifetime earnings rather than annual income fluctuations.
Consequently, bonuses and variable pay are perceived as temporary and are saved rather than incorporated into regular budgets. Bengaluru’s income comes mainly from technology-sector compensation, which aligns with, though does not conclusively prove, the tendency to save more than spend.
The report’s data on weekend spending supports this observation: discretionary categories such as fashion and entertainment increase by more than twofold on Saturdays and Sundays. This effect is most pronounced among the highest earners, whose weekend spending multiplier reaches 2.53 times, compared to 1.37 times for the lowest income bracket.
This pattern does not reflect a household distributing its budget evenly throughout the week. Instead, it indicates a household making a limited number of intentional, discretionary decisions while reserving the remainder, precisely the behaviour predicted by Friedman’s theory for income that a household does not fully trust to recur.
In contrast, Chandigarh does not encounter this trade-off. It maintains high income and expenditure while sustaining robust savings and low debt, achieving prosperity across all dimensions without forcing a choice between them. This characteristic distinctly positions Chandigarh as an outlier, a point to which this analysis frequently returns.
Debt number that looks alarming until you ask what it built
By examining the underlying factors rather than merely the headline figure, a different narrative emerges regarding Chennai’s debt. The city exhibits a debt-to-income ratio of 27.7 percent, which is not only the highest among the Big Six cities but also surpasses all the 100 cities included in the study, including Patna, Jaipur, and Kanpur.
When considered in isolation, the figure suggests financial strain. But, when contextualised with the purposes for which the debt was incurred, primarily housing and vehicles, it suggests a different interpretation. According to the Life-Cycle Hypothesis proposed by Franco Modigliani and Richard Brumberg in the 1950s, borrowing against future income to finance durable assets throughout one’s working life is considered rational behaviour rather than a sign of distress.
Hyderabad exhibits the lowest debt ratio among the Big Six cities at 14 percent. This is not due to greater financial prudence among its households, but their distinct economic positioning: the city hosts the largest concentration of middle-income households in the country, a demographic with limited borrowing capacity and collateral.
Bengaluru’s debt ratio, at 15.7 percent, is similarly low but for a different reason. It is characterised by high-income, high-saving households, where income is not typically allocated to debt. These three cities illustrate distinct debt-to-income narratives, which, when averaged nationally, would obscure their individual financial dynamics.
A hierarchy report’s own numbers are already outrunning
The concept of flattening—averaging away real differences until they disappear into one smooth number—ultimately serves as the unifying element linking each section of this report to the housing component, and it is most evident in the actual locations of India’s urban transformation.
The proportion of urban households in India classified as middle-income has nearly doubled over the past decade, increasing from 29 percent to 53 percent, and is anticipated to reach 60 percent by 2030-31. However, this shift is not evenly distributed across the hierarchical framework the report uses to describe the country.
The middle-income share in the Big Six cities is expected to increase from 59 to 63 percent by 2031, a rise of four percentage points. In contrast, Boomtowns, Breakout cities, and Frontier cities are projected to increase by eight to ten percentage points over the same period.
The lower tiers of the classification are precisely where the transformation is occurring most rapidly. Health coverage presents a different perspective. Frontier cities exhibit the highest proportion of insured households in the nation, at 41.3 percent, compared to only 30.9 percent in the Big Six, which are considered the pinnacle of the hierarchy.
The factors motivating households in Frontier cities to secure financial protection appear to be independent of influences from the megacities. This phenomenon is occurring autonomously.
The report’s appendix contains a very interesting and important detail: to model households that its survey cannot reliably capture, those with incomes exceeding typical sampling thresholds, PRICE employs Vilfredo Pareto’s 1896 work on income concentration.
This century-old methodology is utilised because the data consistently surpass the categories designed to encompass it. This column has previously made the same argument: once for a single quarter of housing sales and once for a decade of urban income.
While the aggregate figures were accurate, they did not represent the entire nation.
(Edited by Ajeet Tiwari)
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