JAIIB IEIFS Guide to poverty and unemployment in India: Lines, PLFS and Schemes

The topic of poverty and unemployment in India is one of the highest-yield areas in Module A of the JAIIB paper on Indian Economy and Indian Financial System, because examiners can test it three different ways in the same paper: as a definition question (which committee, which line), as a data question (which survey, which rate), and as an application question (how it feeds priority sector lending). Most candidates lose marks here not because the concepts are hard, but because they quote the wrong committee, confuse the survey that produces employment numbers with the one that produces consumption numbers, or treat a discontinued scheme as live. This guide fixes all three problems.

📏 How Poverty Is Measured in India

Any discussion of poverty and unemployment in India starts with measurement, and poverty has historically been measured as income poverty, using a consumption expenditure threshold called the poverty line. A household whose monthly per capita expenditure falls below that line is counted as poor. The share of such persons in the total population is the Head Count Ratio (HCR) — the number every exam question ultimately asks about.

The committee chain you must memorise

• Working Group (1962) — first attempt at a national minimum consumption norm.
• Dandekar and Rath (1971) — anchored the line to a calorie norm rather than a notional income.
• Alagh Committee (1979) — formalised calorie norms of 2,400 kcal per capita per day in rural areas and 2,100 kcal in urban areas.
• Lakdawala Committee (1993) — retained the calorie anchor but introduced state-specific price deflators.
• Tendulkar Committee (2009) — moved away from pure calorie anchoring to a broader basket covering food, education, health, electricity and transport, using Mixed Recall Period data.
• Rangarajan Committee (2014) — recommended separate rural and urban consumption baskets and a higher line; its estimates were never formally adopted for official headcount reporting.

The last officially reported all-India headcount ratio on the Tendulkar basis was for 2011-12, at roughly 21.9 per cent of the population. The Rangarajan method, applied to the same year, produced a materially higher figure of about 29.5 per cent — the same economy, two different lines. That single contrast is the most frequently examined fact in this chapter. If you understand why the number moves when the basket moves, you also understand why India shifted attention towards multidimensional measures.

💡 Exam Tip: If a question says "as per the last official poverty estimate", the expected answer is the Tendulkar-based figure for 2011-12. If it names Rangarajan, the higher figure is expected. Read the stem for the committee name before you pick a number.

🧭 Multidimensional Poverty and the New Consumption Data

Because no official consumption-based poverty ratio was published between 2011-12 and the return of the Household Consumption Expenditure Survey, India's poverty debate shifted to the National Multidimensional Poverty Index (MPI), published by NITI Aayog and built on the globally accepted Alkire-Foster methodology.

The National MPI measures deprivation across three equally weighted dimensions — health, education and standard of living — using twelve indicators: nutrition, child and adolescent mortality, maternal health, years of schooling, school attendance, cooking fuel, sanitation, drinking water, electricity, housing, assets and bank account. A person is identified as multidimensionally poor if she is deprived in at least one-third of the weighted indicators. The headline MPI value is the product of the headcount ratio (H) and the intensity of deprivation (A), so MPI = H × A.

NITI Aayog's discussion paper estimated that the multidimensional poverty headcount fell from roughly 29 per cent in 2013-14 to around 11 per cent in 2022-23, implying that about 24.8 crore people escaped multidimensional poverty over that period. Note the direction of the exam trap here: this is a deprivation measure, not an income measure, so it cannot be compared line-for-line with the Tendulkar ratio.

Separately, the Household Consumption Expenditure Survey (HCES) for 2022-23 and 2023-24 restored the underlying consumption data series after an eleven-year gap. It showed monthly per capita consumption expenditure of roughly Rs 4,100 in rural India and Rs 7,000 in urban India, and — more importantly for the exam — a narrowing of the rural-urban gap and a falling share of food in the consumption basket, which is classic Engel's Law behaviour. HCES data also feeds the rebasing of the Consumer Price Index, which links this chapter directly to monetary policy and fiscal policy in the same module.

👷 Types of Unemployment and the PLFS Data You Must Quote

The second half of poverty and unemployment in India is the labour market, and JAIIB questions here are almost always about classification first and data second. Learn the categories by their cause, not by their name.

• Structural unemployment — a mismatch between the skills workers have and the skills the economy demands; the dominant long-run form in India.
• Frictional unemployment — short-term joblessness while people move between jobs or search after graduating. It is voluntary and unavoidable in any healthy labour market.
• Cyclical unemployment — caused by a downturn in aggregate demand; it rises in a recession and falls in a boom.
• Seasonal unemployment — work is available only in part of the year, typical of agriculture, sugar mills and construction.
• Disguised unemployment — more people are engaged in an activity than it needs, so the marginal productivity of the extra worker is close to zero. This is the classic Indian farm example.
• Underemployment — the person works, but for fewer hours or at a skill level well below capability. It suppresses the measured unemployment rate.

Where the numbers come from

The official source is the Periodic Labour Force Survey (PLFS), run by the National Statistics Office since 2017-18, which replaced the older quinquennial Employment-Unemployment Surveys. It reports three headline ratios for persons aged 15 years and above: Labour Force Participation Rate (LFPR), Worker Population Ratio (WPR) and Unemployment Rate (UR). PLFS uses two reference concepts: Usual Status, which looks back 365 days and includes principal plus subsidiary activity, and Current Weekly Status, which looks back only seven days and therefore always shows a higher unemployment rate.

On the usual status basis, the all-India unemployment rate for persons aged 15+ has stayed close to 3 per cent in recent annual rounds, while LFPR has risen above 60 per cent, driven largely by increased rural female participation. From 2025 the PLFS was revamped to publish monthly estimates on a Current Weekly Status basis, where the rate sits several percentage points higher — quote the concept along with the number or the answer looks wrong. Supplementary indicators include EPFO net payroll additions and e-Shram registrations for unorganised workers.

⚠️ Common Mistake: Treating PLFS and HCES as interchangeable. PLFS measures employment and unemployment; HCES measures consumption expenditure. A question asking for the source of India's poverty data is never answered with PLFS.

🏛️ Government Schemes on Poverty and Employment

Schemes attacking poverty and unemployment in India are examined as one-liners: what does the scheme guarantee, who administers it, and which ministry runs it. Group them by whether they create demand for labour, build skills, or push credit.

Wage employment and rural livelihoods

• MGNREGA — a statutory guarantee of 100 days of unskilled manual wage employment in a financial year to every rural household whose adult members volunteer for it, with an unemployment allowance if work is not provided in time.
• DAY-NRLM — the rural livelihoods mission that organises poor rural women into Self Help Groups and links them to bank credit, making it the single most important poverty scheme from a banker's point of view.
• DAY-NULM — the urban counterpart, covering street vendors, shelters and self-employment.
• PM SVANidhi — collateral-free working capital loans to street vendors, with escalating limits on timely repayment.

Self-employment, skills and formal jobs

• PMEGP — margin money subsidy for setting up micro enterprises, implemented through KVIC and banks.
• PMMY (MUDRA) — refinance for micro units under Shishu (up to Rs 50,000), Kishore (Rs 50,000 to Rs 5 lakh), Tarun (Rs 5 lakh to Rs 10 lakh) and Tarun Plus (Rs 10 lakh to Rs 20 lakh, for borrowers who have repaid an earlier Tarun loan).
• Skill India / PMKVY and DDU-GKY — short-term training and placement-linked skilling aimed squarely at structural unemployment.
• PM Vishwakarma — credit, toolkit support and skilling for traditional artisans and craftspeople.
• Employment Linked Incentive scheme — the newer central scheme that pays incentives for the creation of additional formal jobs, routed through EPFO records, with a first-timer benefit linked to one month's EPF wage.

Also remember the safety-net leg: subsidised foodgrains under the National Food Security Act, PM Awas Yojana for housing, and the Jan Dhan-Aadhaar-Mobile trinity that makes Direct Benefit Transfer possible. DBT is the reason leakage-based questions now favour "reduced diversion" as the correct option.

🏦 Why Bankers Must Know Poverty and Unemployment in India

This is where the chapter stops being general studies and becomes banking. Every measure of poverty and unemployment in India eventually lands on a bank branch counter as a lending target, a subsidy credit or a financial inclusion metric.

Priority sector lending

Under the RBI's Priority Sector Lending Master Directions, domestic scheduled commercial banks must lend 40 per cent of Adjusted Net Bank Credit (or Credit Equivalent of Off-Balance Sheet Exposure, whichever is higher) to the priority sector, with sub-targets of 18 per cent for agriculture, 7.5 per cent for micro enterprises and a weaker sections sub-target that the 2025 revision raised to 12 per cent. "Weaker sections" is defined by exactly the groups this chapter identifies as poor — small and marginal farmers, artisans, SHG members, scheduled castes and tribes, persons with disabilities and beneficiaries of government poverty programmes. Shortfalls go to the Rural Infrastructure Development Fund and similar funds, so poverty data has a direct balance sheet consequence.

Financial inclusion and credit delivery

Basic savings bank deposit accounts under PMJDY, RBI's Financial Inclusion Index, the business correspondent model, and no-frills insurance and pension products (PMJJBY, PMSBY, APY) exist because income poverty and informal employment keep households outside formal finance. Digital rails matter too: low-cost payments infrastructure is what allows a subsidy to reach a beneficiary without a branch visit, which is why the debate over UPI charges is really a financial inclusion debate. For structure and context, revise the Indian financial system as a whole and the tiering of institutions in India's banking structure, since regional rural banks, small finance banks and cooperative banks are the delivery arms for exactly this population.

Finally, the employment story connects to output. A weak jobs market shows up as sluggish consumption, which shows up in national income accounting in India, while the labour-absorbing capacity of the services sector in the Indian economy explains why growth has not translated into proportionate job creation. External vulnerability adds another layer, which is why examiners also pair this chapter with the external debt of India and with climate change, SDGs and structural issues facing the Indian economy.

📌 Remember: SDG 1 is "No Poverty" and SDG 8 is "Decent Work and Economic Growth". Questions that mix the Sustainable Development Goals with this chapter almost always test these two numbers.

🧠 Practice MCQs: Poverty and Unemployment

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Frequently Asked Questions

Master poverty and unemployment in India by pairing the committee chain with the survey names and the priority sector definitions — that combination answers almost every question the examiner can build from it. Browse more Module A revision notes on the Indian Economy and Indian Financial System tag hub, then lock the concepts in with the full JAIIB course and question bank.