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Poverty and Inequality

Learning Objectives​

By the end of this topic, you should be able to:

  1. Distinguish absolute from relative poverty and income poverty from multidimensional poverty.
  2. Trace India's poverty measurement history — Alagh, Lakdawala, Tendulkar, and Rangarajan committees — and the shift to the Multidimensional Poverty Index (MPI).
  3. Measure inequality using the Lorenz curve, Gini coefficient, and shares of top/bottom deciles, and interpret Indian data.
  4. Explain the main causes of poverty and inequality in India and the mechanisms linking them to growth.
  5. Evaluate major Indian anti-poverty instruments: MGNREGA, NFSA/PDS, PM Awas Yojana, Ayushman Bharat, and Direct Benefit Transfers.
  6. Analyse the growth–inequality–poverty relationship, including the Kuznets hypothesis and evidence on inclusive growth.

Quick Answer​

Poverty is the inability to attain a minimum standard of living — measured either by income/consumption falling below a poverty line or by multidimensional deprivation in health, education, and living standards. Inequality is the unevenness of the distribution of income, wealth, or opportunity across a population, typically summarised by the Gini coefficient. The two are related but distinct: a country can reduce poverty while inequality rises — which is broadly India's post-1991 story. NITI Aayog's National MPI shows multidimensional poverty falling from 29.2% (2013-14) to 11.3% (2022-23), yet wealth and income concentration at the top has risen sharply. Understanding both is central to development economics because policy for each is different.

Overview​

Ask "is India winning against poverty?" and you get two truthful, opposite-sounding answers. Yes: by almost every measure — consumption surveys, the MPI, World Bank estimates — the share of Indians in extreme poverty has fallen dramatically since the 1990s, one of history's largest poverty declines by headcount. And no, not entirely: hundreds of millions remain vulnerable just above the line, malnutrition persists, and the gap between the top and the rest has widened to levels some economists compare to the colonial era.

That is precisely why economists treat poverty and inequality as separate concepts requiring separate tools. Poverty asks: how many people fall below a minimum threshold? Inequality asks: how is the whole pie divided? Growth can fix the first while worsening the second. This topic builds both toolkits — lines, indices, curves — and then applies them to India's data and policy record.

Core Concepts​

1. Absolute vs Relative Poverty​

Definition: Absolute poverty is living below a fixed minimum threshold of income or consumption needed for basic needs (food, shelter, clothing). Relative poverty is falling far below the typical standard of one's own society — commonly, below 50–60% of median income.

Explanation: Absolute poverty uses an anchored line — it does not move when society gets richer (except for price adjustment). Relative poverty moves with the median: even in a rich country, those far behind the mainstream are "poor" because they cannot participate normally in social and economic life. Developing countries like India traditionally track absolute poverty (can families eat, dress, house themselves?); rich countries emphasise relative poverty. The World Bank's international extreme poverty line — $2.15/day at 2017 purchasing power parity (revised to $3.00 at 2021 PPP in 2025) — is an absolute standard designed for global comparison.

Example: If the line is ₹1,500/month per person, a family whose per-capita consumption is ₹1,200 is absolutely poor; if everyone's income doubles, they escape absolute poverty even if their rank in society is unchanged.

Real-World Example: World Bank estimates suggest India's extreme poverty rate fell to low single digits by the early 2020s on the $2.15 line - but at the higher $3.65 lower-middle-income line, a much larger share remained poor, showing how the chosen line drives the headline.

Why It Matters: The choice of concept changes the policy target: absolute poverty calls for growth plus basic-needs provision; relative poverty calls for redistribution. Exam answers must always state which line and which year.

Common Misunderstanding: "Poverty fell, so inequality must have fallen." False — absolute poverty can plummet while relative gaps widen, exactly because growth lifts the bottom slower than the top.

2. Measuring Poverty in India: From Calorie Norms to Committees​

Definition: India's official poverty lines have historically been consumption-expenditure thresholds derived from nutritional norms, revised by successive expert committees: Alagh (1979) (calorie norms: 2,400 kcal rural / 2,100 urban), Lakdawala (1993) (state-specific lines), Tendulkar (2009) (moved beyond calories to a broader consumption basket; poverty at 37.2% in 2004-05 and 21.9% in 2011-12), and Rangarajan (2014) (higher lines; 29.5% in 2011-12 — never officially adopted).

Explanation: Each committee wrestled with the same problems: what basket defines "minimum living"? How to update for prices (the index number problem)? Rural vs urban differences? The Tendulkar line (~₹27/day rural, ₹33/day urban in 2011-12 prices) drew criticism for being too low — "can anyone live on ₹33 a day?" — which motivated Rangarajan's higher line and, ultimately, the shift toward multidimensional measurement. A further complication: the 2017-18 consumption survey was junked over data-quality concerns, leaving India without an official consumption-based poverty estimate for over a decade until the Household Consumption Expenditure Survey (HCES) 2022-23/2023-24 resumed the series.

Example: Using Tendulkar methodology on 2011-12 NSS data: 21.9% of Indians (about 27 crore people) were poor — the last official income-poverty figure India published.

Real-World Example: HCES 2022-23 results — showing sharp increases in real consumption and falling rural–urban gaps — were used by NITI Aayog and independent economists (e.g., SBI Research, World Bank) to argue extreme poverty had fallen to very low levels, though methodological changes make strict comparison with 2011-12 contested.

Why It Matters: A poverty line determines eligibility for and evaluation of trillions of rupees of welfare spending. Measurement is not academic housekeeping — it is the accountability mechanism of anti-poverty policy.

Common Misunderstanding: Students often quote a single "India poverty rate" without a source. There is no unique number: Tendulkar 2011-12 (21.9%), Rangarajan 2011-12 (29.5%), MPI 2022-23 (11.3%), and World Bank $2.15 estimates all measure different things.

3. Multidimensional Poverty (MPI)​

Definition: The Multidimensional Poverty Index (developed by Alkire and Foster at OPHI, used by UNDP and adapted by NITI Aayog) measures poverty as simultaneous deprivation across three dimensions — health, education, and living standards — using (in India's national MPI) 12 indicators, from nutrition and child mortality to sanitation, cooking fuel, housing, and bank accounts. A person deprived in a third or more of weighted indicators is MPI-poor. MPI = H × A (headcount ratio × average intensity of deprivation).

Explanation: Income is a means; the MPI measures ends. A household may sit above the income line yet lack a toilet, clean fuel, and schooling — deprivations income statistics hide. The H × A structure also rewards policies that reduce the depth of poverty, not only those that push people just over a line.

Example: A family with income above the Tendulkar line but with an undernourished child, no clean cooking fuel, and no member with six years of schooling could count as MPI-poor because its weighted deprivation score crosses the 1/3 cutoff.

Real-World Example: NITI Aayog's National MPI reports multidimensional poverty declining from 29.17% (2013-14) to 14.96% (2019-21) to a projected 11.28% (2022-23) — about 24.8 crore people exiting multidimensional poverty over nine years — with the fastest improvements in Bihar, UP, and MP, driven by sanitation (SBM), cooking fuel (Ujjwala), electricity (Saubhagya), and bank access (Jan Dhan).

Why It Matters: The MPI directly maps onto scheme dashboards: each indicator corresponds to a flagship programme, letting policy target specific deprivations district by district (the basis of the Aspirational Districts Programme monitoring).

Common Misunderstanding: MPI-poverty and income-poverty rates are not comparable numbers — a fall in MPI does not "prove" income poverty fell equally, because MPI improvements can come from public asset provision (toilets, gas connections) without income growth.

4. Measuring Inequality: Lorenz Curve and Gini Coefficient​

Definition: The Lorenz curve plots the cumulative share of income (or consumption/wealth) held by the cumulative share of the population, ranked from poorest to richest. The Gini coefficient is the ratio of the area between the Lorenz curve and the equality diagonal to the entire area under the diagonal: 0 = perfect equality, 1 = perfect inequality.

Explanation: If the bottom 50% earn 50% of income, the Lorenz curve coincides with the 45° line and Gini = 0. The more the curve bows away from the diagonal, the higher the Gini. Complementary measures include decile/percentile shares (e.g., income share of the top 1%), the Palma ratio (top 10% ÷ bottom 40%), and wealth vs income distinctions — wealth is always distributed more unequally than income because assets accumulate.

Example: In a five-person economy with incomes 10, 10, 20, 20, 40: the bottom 40% hold 20% of income and the top 20% hold 40% — plot cumulatively to draw the Lorenz curve; the bow gives a moderate Gini around 0.28.

Real-World Example: India's consumption Gini has hovered around 0.32–0.36 (consumption Ginis understate inequality). Income-based estimates (PLFS, tax data) are higher — around 0.40 or more. The World Inequality Database (Chancel–Piketty) estimates the top 1% of Indians received roughly 22% of national income and held about 40% of wealth in 2022-23 — the paper's authors called it the "Billionaire Raj," higher on some metrics than under colonial rule; other economists dispute the tax-data methodology. HCES 2022-23, in contrast, showed consumption inequality declining.

Why It Matters: Inequality metrics guide tax design (progressivity), assess whether growth is inclusive, and predict political-economy stress. High wealth concentration also compounds across generations via inheritance and unequal education access.

Common Misunderstanding: A single Gini can hide who gained: two countries with identical Ginis can differ completely in whether the middle or the bottom is squeezed. Always pair the Gini with decile shares, and always note whether the figure is consumption, income, or wealth — they differ hugely.

5. Causes and the Growth–Inequality–Poverty Triangle​

Definition: Poverty and inequality in India stem from interacting economic causes (jobless/skill-biased growth, informality, low agricultural productivity), social causes (caste, gender, and regional disparities; unequal education and health access), and political-institutional causes (historic underinvestment in human capital, leakages in delivery). The Kuznets hypothesis posits inequality first rises then falls with development (inverted-U); the growth elasticity of poverty measures how much poverty falls per unit of growth.

Explanation: Growth is the strongest poverty-killer — but its pattern determines its power. Growth concentrated in capital- and skill-intensive sectors (IT, finance) raises top incomes while the 45%+ of workers in agriculture see slow gains; that simultaneously reduces poverty slowly and raises inequality. Inequality then feeds back: unequal access to nutrition, schooling, and credit blunts the productivity of the poor, lowering future growth — the modern consensus (IMF, World Bank research) that high inequality can harm growth, contra older trade-off views. Intergenerational transmission — poor health → poor learning → low earnings → poor children — creates poverty traps that markets alone do not break.

Example: Two states grow at 7%. In State A growth comes from labour-intensive manufacturing absorbing rural workers — poverty falls fast, inequality is stable. In State B growth comes from capital-intensive petrochemicals — GDP rises but poverty barely moves. Same growth, different poverty elasticity.

Real-World Example: Kerala achieved low poverty and high human development at modest income levels through early public investment in health and education; Bihar's historically low human-capital investment kept poverty elasticity low despite recent rapid growth — a natural experiment in the pattern-of-growth argument.

Why It Matters: This triangle is the intellectual core of "inclusive growth" — the stated objective of Indian planning since the 11th Five-Year Plan — and frames every debate from farm laws to production-linked incentives.

Common Misunderstanding: The Kuznets curve is a hypothesis, not a law. Evidence is mixed — many countries (including India post-1991) show inequality rising with growth for decades with no automatic turn; the "fall" phase historically required deliberate policy (progressive taxation, mass education, welfare states).

6. India's Anti-Poverty Policy Architecture​

Definition: India attacks poverty through four channels: employment (MGNREGA — legal guarantee of 100 days of rural wage work; DDU-GKY skills; PM Vishwakarma), food security (NFSA 2013 covering ~81 crore people via PDS; PM Garib Kalyan Anna Yojana free grain extension), asset and service provision (PM Awas Yojana housing, Ujjwala LPG, Jal Jeevan Mission, Saubhagya electrification, Swachh Bharat sanitation), and financial/social protection (Jan Dhan accounts, Ayushman Bharat PM-JAY ₹5 lakh health cover, PM-KISAN ₹6,000/year to farmers, Direct Benefit Transfers via the JAM trinity — Jan Dhan, Aadhaar, Mobile).

Explanation: The design logic has shifted over decades: from growth trickle-down (1950s–60s), to targeted programmes (IRDP, 1970s–80s garibi hatao era), to rights-based entitlements (2005–13: MGNREGA, RTE, NFSA), to platform-based direct delivery (post-2014: DBT, Aadhaar-linked transfers cutting leakages). MGNREGA doubles as insurance — demand for its work spikes in droughts and downturns (it hit record employment in the COVID year 2020-21), making it a self-targeting automatic stabiliser. DBT has transferred lakhs of crores with substantially reduced duplication and ghost beneficiaries, though exclusion errors (failed biometric authentication) remain a serious concern.

Example: In a drought year a landless household loses farm work; MGNREGA provides 100 days at the notified wage, PDS provides subsidised grain, and PM-KISAN (if they own marginal land) gives cash — three stacked safety nets against one shock.

Real-World Example: During COVID-19, PMGKAY delivered free additional foodgrain to ~80 crore people, and cash went directly to about 20 crore women's Jan Dhan accounts — a delivery capability that would have been impossible pre-JAM and that most analysts credit with preventing famine-scale distress despite the income collapse.

Why It Matters: For exams and policy alike, the evaluation questions are: targeting accuracy (inclusion vs exclusion errors), fiscal cost, work incentives, and whether schemes build capabilities (education, health) or only cushion consumption.

Common Misunderstanding: "Welfare schemes reduce poverty; growth is separate." In practice they interact: schemes protect households from shocks that would otherwise destroy their productive assets (distress sale of land/cattle), preserving their ability to ride growth — protection enables participation.

Visual Learning​

The Poverty–Inequality Analytical Map​

India's Poverty Measurement Timeline​

Key Terms​

TermDefinitionContext / Related Concepts
Poverty lineThreshold of income/consumption below which a person is poorTendulkar, Rangarajan; World Bank $2.15 (2017 PPP)
Absolute povertyDeprivation relative to a fixed minimum standardIndia's official concept
Relative povertyIncome far below society's median (e.g., <50–60%)Standard in rich countries
Headcount ratio (H)Share of population below the lineIgnores depth of poverty
Poverty gapAverage shortfall of the poor from the lineMeasures depth, not just count
MPIMultidimensional Poverty Index = H × A across health, education, living standardsAlkire–Foster; NITI Aayog national version (12 indicators)
Lorenz curveCumulative income share vs cumulative population shareVisual basis of the Gini
Gini coefficientArea-based inequality index, 0 (equal) to 1 (unequal)Consumption Gini < income Gini < wealth Gini
Palma ratioTop 10% share ÷ bottom 40% shareFocuses on the tails
Kuznets hypothesisInequality first rises, then falls with developmentInverted-U; empirically contested
Growth elasticity of poverty% fall in poverty per 1% growthDepends on growth pattern and initial inequality
Inclusive growthGrowth whose benefits are broadly shared11th/12th Plan objective
JAM trinityJan Dhan + Aadhaar + Mobile delivery platformBackbone of DBT
Exclusion errorDeserving beneficiary left out of a schemeTrade-off with inclusion error (undeserving included)
Poverty trapSelf-reinforcing cycle keeping households poorNutrition–learning–earnings channel

Evidence and Data​

  • Tendulkar (2011-12): 21.9% poor (25.7% rural, 13.7% urban) — last official consumption-poverty estimate.
  • NITI Aayog MPI: 29.17% (2013-14) → 14.96% (2019-21) → 11.28% (2022-23 discussion-paper estimate); ~24.8 crore people exited multidimensional poverty.
  • World Bank: Extreme poverty ($2.15, 2017 PPP) in low single digits by 2022-23 per estimates using HCES; 2025 update to $3.00 (2021 PPP) still showed a dramatic decline since 2011-12.
  • World Inequality Lab (2024): Top 1% income share ≈ 22.6%, wealth share ≈ 40% (2022-23) — contested methodology, but the benchmark figure in inequality debates.
  • HCES 2022-23: Consumption inequality fell (rural Gini ~0.266, urban ~0.314), while rural–urban consumption gaps narrowed — illustrating the consumption-vs-income divergence.
  • NFSA/PDS: Legal food entitlement for about two-thirds of the population (~81 crore people); PMGKAY provided free grain from 2020, extended thereafter.

Real-World Applications​

  • Scheme targeting: SECC (Socio-Economic Caste Census) data and MPI district rankings decide who gets PMAY houses and which districts join the Aspirational Districts Programme.
  • Finance Commission devolution: Income-distance and demographic criteria in tax-sharing formulas are, at bottom, inequality-across-states corrections.
  • Business strategy: FMCG "sachet economics" and micro-finance business models are built directly on the shape of India's income distribution.
  • Global reporting: SDG 1 (No Poverty) and SDG 10 (Reduced Inequalities) require India to report these exact indicators internationally.

Common Mistakes​

  1. Misconception: Poverty and inequality are the same thing, so reducing one reduces the other. Why it is wrong: They answer different questions — poverty is about a threshold, inequality about the whole distribution. India post-1991 saw large absolute-poverty declines alongside rising income and wealth concentration at the top. Correct explanation: Growth can lift the floor while stretching the ceiling. Analyse them separately: poverty with lines/MPI, inequality with Gini and top shares — then discuss their interaction (high inequality slows poverty reduction per unit of growth).

  2. Misconception: India's poverty rate is a single settled number. Why it is wrong: Estimates differ by concept (income vs consumption vs multidimensional), line (Tendulkar vs Rangarajan vs $2.15 vs $3.65), and data vintage (2011-12 NSS vs 2022-23 HCES, which changed methods). Correct explanation: Always state measure, line, and year: e.g., "21.9% (Tendulkar, 2011-12)"; "11.28% multidimensionally poor (NITI Aayog MPI, 2022-23 est.)"; "extreme poverty in low single digits (World Bank $2.15, 2022-23)."

  3. Misconception: The Gini coefficient tells you everything about inequality. Why it is wrong: The Gini is a single summary that is most sensitive to the middle of the distribution, cannot say where inequality changed, and differs sharply by base (consumption Ginis look far lower than income or wealth Ginis). Correct explanation: Use the Gini alongside decile shares, top-1%/10% shares, and the Palma ratio, and specify whether the data are consumption, income, or wealth — India's consumption Gini (~0.3) coexists with a wealth share of ~40% for the top 1%.

Comparison and Connections​

DimensionPovertyInequality
Question askedHow many fall below a minimum?How is the total distributed?
Key measuresHeadcount ratio, poverty gap, MPIGini, Lorenz curve, top shares, Palma
BenchmarkPoverty line (absolute) or median share (relative)Perfect equality (Gini = 0)
Effect of uniform growthFalls (people cross the line)Unchanged (all incomes scale equally)
Primary policy leversGrowth, safety nets, basic servicesProgressive taxes, public education/health, asset redistribution
India trend since 1991Sharp decline (all measures)Income/wealth concentration rising; consumption Gini stable-to-falling
SDGSDG 1SDG 10

Frequently confused pairs: headcount ratio vs poverty gap (count vs depth); income vs wealth inequality (flow vs stock); inclusion vs exclusion errors in targeting; Kuznets hypothesis (inequality–growth) vs growth elasticity of poverty (poverty–growth).

Practice Questions​

Recall​

  1. Name the four major committees on poverty estimation in India in chronological order, and state the Tendulkar poverty estimate for 2011-12. Answer guidance: Alagh (1979), Lakdawala (1993), Tendulkar (2009), Rangarajan (2014); Tendulkar 2011-12: 21.9% (rural 25.7%, urban 13.7%).

  2. What are the three dimensions of NITI Aayog's National MPI, and what does the formula MPI = H × A mean? Answer guidance: Health, education, living standards (12 indicators). H = headcount ratio of multidimensionally poor; A = average intensity (share of weighted deprivations among the poor); their product rewards reducing both the number and the depth of deprivation.

Understanding​

  1. Explain how a Lorenz curve is constructed and how the Gini coefficient is derived from it. Answer guidance: Rank population poorest to richest; plot cumulative population share (x) vs cumulative income share (y); the diagonal is perfect equality. Gini = area between diagonal and Lorenz curve ÷ total area under diagonal; 0 = equality, 1 = one person holds everything. Note it's most sensitive to the middle of the distribution.

  2. Why can multidimensional poverty fall rapidly even when household incomes are stagnant? Answer guidance: MPI indicators respond to public provision — toilets (SBM), LPG (Ujjwala), electricity (Saubhagya), bank accounts (Jan Dhan), housing (PMAY) — which governments can deliver independently of household earnings. Hence MPI declines partly reflect asset/service delivery, not necessarily income growth; this is both a strength (measures real welfare) and a caveat (not comparable with income poverty).

Application​

  1. A state government has a fixed budget and must choose between expanding MGNREGA days and a universal cash transfer. Advise, using targeting and insurance arguments. Answer guidance: MGNREGA is self-targeting (work requirement screens out the non-poor) and acts as insurance in bad years, but has administrative costs, delayed wages, and excludes those unable to work. Cash is cheap to deliver via DBT and respects choice, but universal cash spreads the budget thin and lacks the counter-cyclical automatic-stabiliser property. A defensible answer: MGNREGA for able-bodied rural workers + targeted cash/pensions for the elderly, disabled, and widows.

  2. Using the growth elasticity of poverty, explain why 7% growth reduced poverty faster in some Indian states than others. Answer guidance: Elasticity depends on (a) sectoral pattern — labour-intensive growth (construction, manufacturing, agriculture productivity) reaches the poor; capital-intensive growth doesn't; (b) initial inequality — higher inequality means the poor hold a smaller share of each growth increment; (c) human capital — educated, healthy workers can seize new jobs. Contrast e.g. Kerala/Tamil Nadu (high human capital) with resource-driven growth states.

Analysis​

  1. "India's inequality debate is really a data debate." Evaluate, referring to consumption, income, and wealth measures. Answer guidance: HCES 2022-23 shows consumption inequality falling; World Inequality Lab tax-based estimates show top income/wealth shares at record highs. Both can be true: consumption smooths income; surveys under-sample the rich; tax data miss informal incomes; methods changed between survey rounds. Strong answers conclude the direction of top-end concentration is robust while precise magnitudes are contested — and that policy conclusions (progressive taxation vs growth focus) hinge on which measure one privileges.

  2. Assess the Kuznets hypothesis against India's post-1991 experience. Answer guidance: Kuznets predicts inequality rises during structural transformation, then falls. India fits the rising phase (top shares up since liberalisation as labour moved toward high-productivity services) but shows no automatic downturn after three decades. Historical Kuznets "declines" (US/Europe mid-20th century) came from wars, mass education, and welfare states — policy, not automaticity. Conclusion: the inverted-U is a possibility conditioned on policy choices, not a developmental law.

FAQ​

Q1. Does India have an official poverty line today? Not an updated one. The last official estimates used the Tendulkar line on 2011-12 NSS data. The 2017-18 survey was withdrawn, and while HCES 2022-23/2023-24 revived consumption data, the government has not notified a new official line; NITI Aayog's MPI has become the de facto headline poverty measure.

Q2. How can the World Bank say Indian extreme poverty is nearly gone while so much visible deprivation remains? The $2.15/day (2017 PPP) line is an extreme subsistence threshold. At the lower-middle-income line (~$3.65) or the new $3.00 (2021 PPP) standard, many more Indians count as poor, and a very large population sits just above any line — non-poor but highly vulnerable to one illness or drought. Low extreme poverty and mass vulnerability coexist.

Q3. Is rising inequality actually bad for growth? Modern evidence (IMF, OECD studies) suggests high and rising inequality can slow and shorten growth spells — by restricting the poor's investment in education and health, shrinking the consumer base, and generating political instability. But moderate inequality that rewards effort and innovation is part of any market economy; the debate is about extremes and about equality of opportunity versus outcomes.

Q4. Why not just give every Indian a Universal Basic Income (UBI)? The Economic Survey 2016-17 examined UBI as a replacement for leaky schemes: attractive for simplicity and choice, but a meaningful UBI costs ~4–5% of GDP unless it replaces existing subsidies (politically hard), and universality means paying the rich too. Current policy has instead moved toward quasi-UBI segments: PM-KISAN for farmers, state schemes like Rythu Bandhu and KALIA, plus DBT-ised subsidies.

Q5. Which matters more for an exam answer — poverty numbers or the story behind them? Both, in a fixed order: give the number with its source and year (that signals rigour), then interpret — what drove the change (growth pattern, schemes), what the measure misses (vulnerability, quality of education/health), and one limitation of the data. Number → mechanism → caveat is the full-marks structure.

Quick Revision​

  • Poverty = below a minimum threshold; inequality = shape of the whole distribution. They can move in opposite directions.
  • Committees: Alagh (1979, calories) → Lakdawala (1993, state lines) → Tendulkar (2009; 21.9% in 2011-12) → Rangarajan (2014; 29.5%, not adopted).
  • World Bank extreme poverty line: $2.15/day (2017 PPP), updated to $3.00 (2021 PPP) in 2025; India's extreme poverty now in low single digits by these estimates.
  • NITI Aayog MPI = H × A; 3 dimensions, 12 indicators; 29.17% (2013-14) → 11.28% (2022-23); ~24.8 crore exited multidimensional poverty.
  • Lorenz curve bows below the equality diagonal; Gini = bow area ÷ triangle area; 0 = equal, 1 = maximal inequality.
  • India: consumption Gini ~0.27–0.32 (HCES 2022-23, falling); top 1% income share ~22.6% and wealth share ~40% (World Inequality Lab, contested).
  • Kuznets inverted-U: hypothesis, not law — India's inequality has risen through three decades of growth.
  • Growth elasticity of poverty depends on the pattern of growth (labour-intensity), initial inequality, and human capital.
  • Policy stack: MGNREGA (employment guarantee + insurance), NFSA/PDS + PMGKAY (~81 crore covered), PMAY/Ujjwala/SBM/JJM (assets & services), Ayushman Bharat (₹5 lakh health cover), DBT via JAM.
  • Targeting trade-off: inclusion errors vs exclusion errors; self-targeting (MGNREGA work requirement) minimises both cheaply.
  • Full-marks answer format: number + source/year → mechanism → limitation.

Prerequisites​

  • Development Concepts — growth vs development, the framing for poverty analysis.
  • HDI — the human-development measurement approach the MPI extends.

Next Topics​