The Limitations of Income Comparisons in Measuring Poverty

When the government announces that crores of people have crossed the poverty line, what exactly does that number measure? In India, poverty has long been defined by a single yardstick: whether a person spends enough money to buy a basket of essential goods. This income-and-expenditure approach has shaped welfare schemes, eligibility lists, and political debates for decades. Yet a growing body of scholarship argues that money alone is a deeply incomplete measure of who is poor and what poverty actually feels like. Reducing human deprivation to a rupee figure misses much of what makes a life difficult-or dignified.

Why income became the default measure of poverty
The line itself is contested
Market-centric measures miss what people actually value
Capability deprivation versus monetary shortfall
Non-market activities that income statistics ignore
The subsistence and informal economy problem
How markets exclude and differentiate people
What GDP gains hide about the cost of development
Social displacement and uncounted human costs
Better ways to measure poverty and progress
Other beyond-income indicators
The MPI is not flawless either

Why income became the default measure of poverty

The appeal of income comparisons is obvious. Money is easy to count, easy to compare across regions, and easy to track over time. The earliest systematic poverty estimation, by a Planning Commission task force in 1962, took a brutally simple route: calculate the minimum calories a person needs to survive, then find the spending level required to buy that many calories. Everyone below that expenditure was “poor.” That logic has carried through every major committee since.

This is why poverty lines in India have always been tied to consumption expenditure. The Tendulkar Committee of 2009 set the line at roughly ₹816 per capita per month in rural areas and ₹1,000 in urban areas for 2011-12. The later Rangarajan Committee revised this upward to ₹972 rural and ₹1,407 urban. The numbers themselves became flashpoints in national politics. A suggested poverty line of around ₹27 a day for rural areas provoked public outrage-how, critics asked, could anyone survive on that?

The line itself is contested

The deeper problem is that these lines are arbitrary in ways that change the headline figures dramatically. Using the Tendulkar methodology, about 25.7% of rural India was classified as poor in 2011-12. The Rangarajan estimates produced poverty figures that were 19% higher in rural areas and 41% higher in urban areas. Same country, same year, wildly different conclusions-simply because the threshold moved. When the government recently claimed near-elimination of poverty, an independent analysis using the Rangarajan method on the same survey data suggested around 26% of Indians remained below the poverty line. A measure that swings so much based on where you draw the line cannot, on its own, tell us who is truly deprived.

Market-centric measures miss what people actually value

Income comparisons rest on a hidden assumption: that well-being can be read off how much money passes through a market. But a great deal of what sustains human life never enters a market transaction at all. The economist Amartya Sen built an entire framework around this insight, arguing that poverty means much more than lacking income-it means falling short of a basic level of capabilities, the real freedoms a person has to live the kind of life they value.

Sen distinguished between functionings, which are the things a person actually achieves-being well-nourished, being educated, participating in community life-and capabilities, the genuine opportunities a person has to achieve those functionings. Two people with identical incomes can have very different capabilities. A person with a chronic illness needs more resources just to reach the same level of functioning as a healthy person. Income comparisons treat both as equally well-off because they spend the same amount. That is a serious blind spot.

Capability deprivation versus monetary shortfall

Once you adopt this lens, poverty looks different. A household might cross the income poverty line yet still suffer from poor health, malnutrition, or no access to clean water, sanitation, and schooling. Income measures these deprivations only indirectly, and often badly. A family may spend money on medical bills not because they are prospering but because someone is sick-an expenditure that signals distress, not improvement. Counting that spending as a sign of higher living standards inverts reality.

Non-market activities that income statistics ignore

Perhaps the clearest weakness of money-based measures is their treatment of work that has no price tag. National income accounting, and the GDP figures derived from it, count only what is bought and sold. As a result, volunteer work, household labour, and caregiving are excluded because they involve no monetary transaction-even though they are essential to the functioning of any community.

This omission falls heavily on women. Across the world, women perform the overwhelming majority of unpaid care work-cooking, cleaning, raising children, tending to the elderly and the sick. During the COVID-19 pandemic, women globally took on an estimated 512 billion additional hours of unpaid childcare, labour that quietly held economies together while appearing nowhere in any income statistic. In a country with a vast informal and subsistence sector, this gap is enormous. Subsistence farmers who grow food for their own families, women managing entire households, and workers in the unorganised economy all contribute to well-being in ways that market-centric metrics simply cannot see.

The subsistence and informal economy problem

India’s economy includes huge swathes of activity that operate partly or wholly outside formal markets. A farmer who consumes most of what they grow has a low cash income but is not necessarily destitute. A landless labourer with the same low cash income, dependent entirely on buying food, may be far worse off. Income comparisons can rank these two households identically, even though their actual security and capabilities differ greatly. The measure flattens a complex reality into a single misleading number.

How markets exclude and differentiate people

Income comparisons also assume that markets are neutral channels through which everyone can improve their lot if they simply earn more. In practice, market processes themselves create exclusion and inequality. Access to credit, land, education, and employment is shaped by caste, gender, region, and social networks. Two people offered the “same” market may face very different real opportunities within it.

This matters because development driven purely by market growth can deepen rather than reduce these divides. A focus on aggregate income growth can coexist with sharp inequality, where the gains flow disproportionately to those already advantaged. Sen’s later work stressed that poverty must be understood through a relational and group-based lens-looking at how social structures position different communities-rather than purely as an individual shortfall of cash. A Dalit household and an upper-caste household with equal incomes do not necessarily face equal barriers in markets for housing, jobs, or schooling.

What GDP gains hide about the cost of development

Nowhere is the limitation of income-based thinking clearer than in the use of GDP as a proxy for progress. Rising national income is routinely treated as proof of development. But GDP counts the value of goods and services produced without asking what was destroyed or damaged in the process.

Consider environmental degradation. GDP does not account for air pollution, natural resource depletion, or biodiversity loss. Activities like deforestation, overfishing, and burning fossil fuels often raise GDP even as they erode the natural foundations of future well-being. Worse, the logic can run backwards: if a factory pollutes a river, the economic activity raises GDP, and then the spending on cleaning it up raises GDP again. Damage and its repair both register as growth, while the underlying loss vanishes from the books.

Large development projects illustrate the same blind spot. A dam or mining project may boost regional income figures while displacing communities, severing people from land and livelihoods that never had a market price. The income statistics record the new economic output; they do not record the destroyed homes, lost commons, or fractured social networks. By using GDP as a stand-in for development, policymakers risk treating high-GDP nations as automatically well-developed, even when inequality, vulnerability, and ecological strain tell a different story.

Better ways to measure poverty and progress

Recognising these limits, economists and governments have developed measures that look beyond income. The most influential in India is the National Multidimensional Poverty Index (MPI), developed by NITI Aayog in partnership with the Oxford Poverty and Human Development Initiative and the UNDP. Instead of a single income threshold, the MPI assesses deprivation across three equally weighted dimensions-health, education, and standard of living-captured through twelve indicators including nutrition, child mortality, schooling, cooking fuel, sanitation, drinking water, electricity, and housing.

Using this approach, NITI Aayog estimated that around 13.5 crore people moved out of multidimensional poverty between 2015-16 and 2019-21, with the headcount ratio falling from 24.85% to 14.96%. Crucially, the MPI shows not just how many are poor but the intensity of their deprivation and which specific dimensions drive it-information an income figure can never provide. This lets policymakers target the actual gaps, whether that is sanitation in one district or schooling in another.

Other beyond-income indicators

Globally, several alternatives push in the same direction. The Human Development Index combines income with life expectancy and education to give a more rounded picture of well-being. The Genuine Progress Indicator starts from consumption but then subtracts environmental and social costs and adds the value of unpaid work, producing something closer to a net measure of welfare. Bhutan’s Gross National Happiness framework folds in psychological and cultural well-being. None of these is perfect, and each involves subjective judgements about what to include and how to weight it. But together they reflect a growing consensus that genuine progress is about more than the size of the economy.

The MPI is not flawless either

It is worth being honest that multidimensional measures carry their own controversies. The choice of indicators, their weights, and the cut-off for defining who counts as poor are all matters of subjective judgement, and critics argue that small changes in these assumptions can shift the results significantly. The lesson is not that one number replaces another, but that no single index captures poverty fully. Income and multidimensional measures are best read together, each correcting for what the other misses.

The core takeaway is this: poverty is not merely the absence of money. It is the absence of the real freedoms and capabilities people need to lead lives they value. An income figure can be a useful signal, but treated as the whole truth it conceals the unpaid labour that sustains households, the social barriers that markets reproduce, and the environmental and human costs that economic growth often hides. Measuring poverty well means measuring what genuinely matters to human lives.

What do you think? If a household crosses the income poverty line but still lacks clean water, healthcare, and schooling, should we call it non-poor? And how would you balance the simplicity of a single income figure against the richer but messier picture offered by multidimensional measures?

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Table of Contents

Why income became the default measure of poverty 🔗

The line itself is contested 🔗

Market-centric measures miss what people actually value 🔗

Capability deprivation versus monetary shortfall 🔗

Non-market activities that income statistics ignore 🔗

The subsistence and informal economy problem 🔗

How markets exclude and differentiate people 🔗

What GDP gains hide about the cost of development 🔗

Social displacement and uncounted human costs 🔗

Better ways to measure poverty and progress 🔗

Other beyond-income indicators 🔗

The MPI is not flawless either 🔗