Poverty cannot be counted until it is defined, and the definition drives the count. That is why the subject is taught as a sequence of committees rather than as a number.
The Indian poverty line has been drawn by successive expert groups — the Task Force using calorie norms, then the Lakdawala, Tendulkar and Rangarajan committees — each revising the basket, the price index used to update it, and whether rural and urban lines should be linked. The examinable point is that a change of committee changes the headcount without anybody’s circumstances changing, which is why comparisons across definitions are meaningless.
Beyond the headcount there are the poverty gap (how far below the line the poor are on average) and the squared poverty gap (which weights the poorest most). A headcount alone says nothing about depth, and two districts with the same headcount can need very different responses.
Given a labour force of 4,200 and employment of 3,906. Asked: the unemployment rate.
\[ \text{Unemployment rate} = \frac{\text{Unemployed}}{\text{Labour force}} \times 100 = \frac{4200 - 3906}{4200} \times 100 = \frac{294}{4200} \times 100 = 7\% \]What the rate does not capture is most of the Indian problem. Someone working one hour a week is employed. Someone who stopped looking is outside the labour force altogether and so is not unemployed. That is why the types below matter more than the rate.
| Type | What it is | Where it shows |
|---|---|---|
| Disguised | More people employed than the work needs; the marginal product is near zero, so removing some would not reduce output | Family farms — the characteristic rural form |
| Seasonal | Work available only part of the year | Agriculture, between sowing and harvest |
| Structural | Skills and locations do not match where the jobs are | Long-term, as an economy changes shape |
| Frictional | Between jobs, searching | Everywhere; short and not a policy problem |
| Cyclical | Deficient demand in a downturn | Industry, in a recession |
| Educated | Qualified people without work matching their qualification | Urban, and politically salient |
Disguised unemployment is the one to understand properly, because it is the bridge to development theory: labour with near-zero marginal product can be moved out of agriculture without output falling, which is the surplus labour that industrialisation was supposed to absorb.
The standard measurement concepts — usual status, current weekly status and current daily status — exist precisely because a single annual question misses seasonal and disguised forms. Daily status gives the highest measured unemployment because it catches days not worked.
Given the share of income received by each fifth of the population, poorest first. Asked: the Gini coefficient.
| Quintile | Population share (%) | Income share (%) | Cumulative population (%) | Cumulative income (%) |
|---|---|---|---|---|
| 1 | 20 | 6 | 20 | 6 |
| 2 | 20 | 10 | 40 | 16 |
| 3 | 20 | 15 | 60 | 31 |
| 4 | 20 | 25 | 80 | 56 |
| 5 | 20 | 44 | 100 | 100 |
The Lorenz curve plots cumulative income against cumulative population. Perfect equality would be the 45° line, where the poorest 20% get 20% of income; here they get 6%, so the curve sags below it. The further it sags, the more unequal the distribution.
The Gini coefficient is twice the area between the line of equality and the Lorenz curve, which is the same as
\[ G = 1 - 2 \times (\text{area under the Lorenz curve}) \]Taking the area under the curve by trapezoids, one per quintile, with both axes in percentages:
| Segment | Trapezoid | Area |
|---|---|---|
| 0 to 20 | \( \tfrac{1}{2}(0 + 6) \times 20 \) | 60 |
| 20 to 40 | \( \tfrac{1}{2}(6 + 16) \times 20 \) | 220 |
| 40 to 60 | \( \tfrac{1}{2}(16 + 31) \times 20 \) | 470 |
| 60 to 80 | \( \tfrac{1}{2}(31 + 56) \times 20 \) | 870 |
| 80 to 100 | \( \tfrac{1}{2}(56 + 100) \times 20 \) | 1560 |
| Total area | 3180 |
A Gini of 0.364. The scale runs from 0 (everyone identical) to 1 (one person has everything), so this is moderate inequality — and the number is only interpretable against another Gini computed the same way, on the same kind of data.
The Lorenz curve and the Gini are statistics, not economics, and this site builds them properly in Measures of Dispersion. What economics adds is the warning about what is being measured: consumption or income, household or person, and whether the survey reached the top of the distribution at all.
Rural–urban disparity shows up in per capita consumption, access to services, literacy and the composition of work. It is self-reinforcing: better services draw people and investment, which fund better services.
Regional disparity is the same phenomenon between states and districts. The standard explanations — historical infrastructure, geography and port access, differences in human capital, and the tendency of investment to go where investment already is — all describe cumulative causation rather than a one-off cause.
The policy instruments are the ones examiners want named: fiscal transfers through the Finance Commission’s devolution formula, centrally sponsored schemes, special incentives for backward areas, and public investment in connectivity. Whether they converge or merely compensate is a live argument, and an answer that notes the argument is better than one that asserts a verdict.
Colin Clark’s three sectors — primary (agriculture, mining), secondary (manufacturing, construction), tertiary (services) — and the Fisher–Clark hypothesis that as income rises, the share of the primary sector falls and the tertiary rises.
The Indian pattern departs from the classical sequence in one specific way, and it is the point worth making: the share of agriculture in output fell far faster than its share in employment. Labour did not move out of agriculture as quickly as value did, so output per worker diverged sharply between sectors. And the shift went substantially from primary to tertiary, rather than passing through a long manufacturing-dominant phase as the classical account expects.
Why the two shares must be read together: a falling output share with a stable employment share means productivity in that sector is falling behind, and that is a statement about incomes, not just structure. Quoting one share without the other is the commonest way to get this question half right.
Planning in India ran through Five Year Plans from 1951, under the Planning Commission, which was replaced in 2015 by NITI Aayog — the National Institution for Transforming India. The change was from an allocating body to an advisory and coordinating one, with resource allocation moving to the Finance Ministry and the Finance Commission.
The major controversies, which is exactly what the syllabus line asks for:
| Policy | Instruments | Treated in |
|---|---|---|
| Fiscal | Tax rates and structure, expenditure, the deficit, fiscal responsibility rules | Unit 4 |
| Monetary | Policy rate, reserve ratios, open market operations, inflation targeting | Unit 3 |
| Industrial | Licensing and its removal, public sector reservation and disinvestment, foreign investment rules, support to small enterprise | this unit |
| Trade | Tariffs, quotas, export promotion, exchange rate management | Unit 5 |
| Agricultural | Support prices, procurement and buffer stocks, input subsidies, credit, marketing regulation, irrigation and research | this unit |
The direction of travel since 1991 is the through-line: from licensing to entry, from quantitative restrictions to tariffs and then lower tariffs, from an administered exchange rate to a managed float, and from monetary financing of deficits to a rule-based framework. An answer that describes that arc is more useful than one that lists measures without a direction.
Agricultural policy carries its own tension, worth stating because it recurs: support prices raise farm incomes and also raise the cost of the food subsidy, skew cropping towards the procured crops, and build stocks beyond what buffer norms require. Every instrument in that row has a cost in another row.