Measuring Urban Poverty: Gender Perspectives and Challenges

Counting the poor sounds straightforward until you try to do it. Decide on a rupee threshold, see who falls below it, and you have your number. But this simple exercise hides deep assumptions about whose money matters, what counts as a deprivation, and who inside a household actually controls resources. When the lens shifts to gender, the cracks in our measurement systems become impossible to ignore. Urban poverty is already harder to capture than rural poverty, and once you ask how poverty is distributed between women and men, the standard tools start to look surprisingly blunt.

How poverty is measured 🔗

The poverty line is the foundation of all official estimates. It is the minimum monetary value a person needs to meet basic needs over a month. Anyone below it is classified as Below the Poverty Line (BPL). There are two broad ways to fix where a household sits relative to that line: by looking at income, or by looking at consumption.

Income-based measurement 🔗

The income approach asks how much a household earns. In theory it is intuitive. In practice it struggles badly in the Indian context, especially in cities. A large share of the urban poor work in the informal economy as street vendors, domestic workers, construction labourers, and small-scale manufacturers, often without contracts or steady pay. These workers operate without social security or stable job guarantees, which means their earnings swing from month to month. Asking a daily-wage worker to state an annual income produces a guess, not a measurement.

Consumption-based measurement 🔗

For these reasons, India primarily relies on consumption rather than income. The official method uses Monthly Per Capita Consumer Expenditure (MPCE), captured through household surveys run by the National Sample Survey Office under the Ministry of Statistics and Programme Implementation. The logic is that what a household actually spends is a steadier signal of its standard of living than what it reports earning. Consumption expenditure also smooths out seasonal income shocks because households can draw on savings or credit to keep spending stable even when earnings dip.

The expenditure thresholds themselves have shifted through a series of expert committees. The calorie-based norms of the 1970s gave way to broader baskets. The Tendulkar Committee in 2009 moved beyond pure calorie counts to include spending on health and education, while the later Rangarajan Committee in 2014 recommended a higher urban poverty line of roughly ₹1,407 per person per month at 2011-12 prices. More recently, NITI Aayog has championed the Multidimensional Poverty Index, which goes beyond money to assess deprivations across health, education, and standard of living.

Why urban poverty resists capture 🔗

Even with consumption as the yardstick, cities pose a distinct problem. Urban poverty is less about insufficient production and more about inadequate access to urban services and opportunities. A family in a Mumbai slum may post higher nominal spending than a rural household yet face crushing rents, polluted surroundings, unreliable water, and expensive private healthcare. A consumption figure that looks adequate on paper can mask severe deprivation in living conditions. The same rupee buys very different levels of dignity in a metro slum versus a village, and the headline poverty line does not always capture that gap.

The gender dimension of urban poverty estimates 🔗

Here is where measurement gets genuinely difficult. Almost all official poverty data is collected at the household level and then assumes that resources are shared equally among everyone inside that household. That assumption is convenient, but it is rarely true. In societies where men typically control household income and decisions, women and girls can experience deeper deprivation than the household-level number suggests.

Female-headed households and vulnerability 🔗

One way researchers try to bring gender into the data is by studying female-headed households, where no adult male is present. A study published in Third World Quarterly examined this directly using the NSS 68th round of consumer expenditure data and found that female-headed households face higher odds of being urban poor than male-headed ones. The reasons are structural. These households often have only one adult earner, frequently confront wage discrimination, and hold fewer assets and weaker safety nets, whether the female headship arises from widowhood, divorce, abandonment, or the migration of male family members.

That same research adds an important nuance. The gender gap in poverty odds largely disappears once the education level of the household head is taken into account, which points to educational disadvantage as both the root cause and the route out. It is a reminder that gender poverty is not a standalone fact but tangles with literacy, marital status, and social group.

The feminisation of poverty 🔗

The broader idea behind these findings is the feminisation of poverty, a term coined by sociologist Diana Pearce in 1978 to describe the disproportionate representation of women among the poor and the structural factors that make it harder for them to climb out. As cities expand and more women head their own households, concern has grown that the female share of the urban poor is rising faster than the male share. Several Indian studies note that women and children make up the overwhelming majority of those below the poverty line.

It is worth being honest about the evidence here, because careful measurement demands it. Not every study confirms a clean story of accelerating female poverty. A review of the empirical literature notes that research from both developed and developing countries does not consistently establish the feminisation of poverty as a settled fact, and some Indian data even show certain women-headed households to be no poorer, or occasionally less poor, than male-headed ones. The disagreement is itself revealing. It often comes down to how poverty is defined and which deprivations the measure chooses to see.

Challenges in measuring gendered poverty 🔗

If the statistics are contested, much of the blame lies with the tools. Three measurement problems stand out, and each one tends to make women’s poverty less visible than it really is.

The household-level blind spot 🔗

The most fundamental issue is that poverty is measured at the household level under the assumption of equal sharing. As UN Women points out, these estimates assume an equal distribution of economic resources among household members, when the reality in societies where men hold power is likely far less equal. A household can sit just above the poverty line while the women inside it eat last and least. NFHS-5 data, for instance, found that fewer than half of women consume dairy or fruit daily, a nutritional gap that no household consumption average will ever reveal.

The shortage of gender-disaggregated data 🔗

You cannot measure what you do not collect separately. Because the core surveys record spending for the household as a whole, breaking poverty down cleanly by sex is difficult. Researchers are forced to use proxies like the sex of the household head, which captures only women who happen to head their own homes and misses the far larger number living within male-headed families. Moving from the household to the individual as the unit of analysis would give a truer gender picture, but the data infrastructure for that remains thin.

Overlooked multiple deprivations 🔗

The third problem is what the money metric leaves out. Income and consumption shortfalls have been criticised for their narrow focus on monetary measures while ignoring other domains of deprivation that are especially significant for women. Chief among these is unpaid care work. Indian women spend an average of 299 minutes a day on unpaid domestic and care work compared with 97 minutes for men, a ratio among the highest in the world. This creates a severe time poverty that conventional poverty lines completely ignore.

The consequences cascade. The same body of research shows that care responsibilities are the primary barrier to women’s labour-force participation, which dropped to a low point in recent years even as the economy grew. In cities, the double burden of paid work plus unrecognised household labour is acute, and the gender wage gap and unpaid labour compound it. A woman working a full day of cooking, cleaning, and child-rearing produces real economic value, yet she registers as economically inactive and her contribution stays invisible in poverty statistics.

Underreporting and identification errors 🔗

Finally, the practical business of identifying the poor is riddled with error. The BPL census system that classifies urban families has long faced criticism over identification problems, data quality, and the content of what is recorded. Migrant women, informal workers, and those without stable addresses are routinely undercounted. When a survey misses the most precarious people in the first place, no amount of clever analysis afterwards can restore them to the count.

Why better measurement matters 🔗

None of this is an academic quibble. Poverty estimates decide who receives ration cards, housing support, and welfare transfers. If the measurement tool cannot see women’s deprivation, programmes will be designed for a poverty that does not match the lived reality. The shift toward multidimensional measures, individual-level analysis, and the formal recognition of unpaid care work all point in the same direction: a richer picture that counts not just rupees, but the full texture of deprivation that falls unequally on women in Indian cities.

What do you think? If unpaid care work were counted in official labour statistics, how might it change the way we measure poverty itself? And should the individual rather than the household become the basic unit for measuring who is poor?

References

1. https://csr.education/development-issues-perspectives/measuring-poverty-india-methods-trends/
2. https://www.drishtiias.com/to-the-points/paper3/poverty-estimation-in-india
3. https://upscgspedia.com/poverty-measurement-in-india/
4. https://www.sankhyathelibrary.com/2024/12/poverty-in-india-how-it-is-measured.html
5. https://www.nextias.com/ca/editorial-analysis/29-05-2026/poverty-measurement-india
6. https://www.tandfonline.com/doi/full/10.1080/01436597.2023.2237426
7. https://socio.health/women-in-economy/feminization-of-poverty-causes-solutions/
8. https://arxiv.org/pdf/1304.5816
9. https://sdg-action.org/poverty-is-not-gender-neutral/
10. https://vajiramandravi.com/current-affairs/feminization-of-poverty/
11. https://discovery.researcher.life/article/invisible-labour-unequal-burden-gender-institutions-and-the-unpaid-care-economy-in-india/917ce90fc0c53836b4e84f155e80f944
12. https://borgenproject.org/gender-and-poverty-in-india/