Two Blocks, One Budget: Reading Human Development Beyond Income
The district planning committee has ₹4.0 crore for a single block-level package and must choose between two blocks whose six-year data are on the table.
Ranipur block: per capita income ₹1.42 lakh, the highest in the district, driven by a grain mandi and remittances from Gulf-bound workers; female literacy 54%; infant mortality 38 per 1,000 live births; life expectancy 66 years; one primary health centre for 45,000 people.
Dhansu block: per capita income ₹68,000; female literacy 71%; infant mortality 22; life expectancy 71 years; one PHC per 18,000 people; but 28% of students drop out before Class 10 against 12% in Ranipur, and mean years of schooling are 5.1 against 6.4.
The chairman argues: "Ranipur is already rich, so the money must go to Dhansu." A member replies that Ranipur's income figure hides its health record. The committee has no ready HDI ranks for the two blocks, only these raw indicators, and must record its reasoning in the minutes.
1. Using the three dimensions of the Human Development Index, decide which block you would rank higher, and state what data you would still need before committing the money.
Read the worked answer
HDI's three dimensions: health (life expectancy at birth), education (mean years of schooling and expected years of schooling), and command over resources (GNI per capita at PPP).
| Indicator | Ranipur | Dhansu |
|---|---|---|
| Life expectancy | 66 | 71 |
| Mean years of schooling | 6.4 | 5.1 |
| Female literacy | 54% | 71% |
| Infant mortality | 38 | 22 |
| Per capita income | ₹1.42 lakh | ₹0.68 lakh |
Ranking: Dhansu edges ahead. Two reasons.
- The health gap is five years of life expectancy - a large, direct capability difference, reinforced by IMR and by Ranipur's thin PHC coverage.
- HDI takes the logarithm of income. Doubling income from ₹68,000 to ₹1.42 lakh raises the income index by only about 0.1 on a 0–1 scale, not by 100%. Ranipur's schooling advantage (6.4 vs 5.1 years) partly offsets, but its female literacy and mortality point the same way as life expectancy.
Missing data before spending: expected years of schooling for children currently enrolled (the second education sub-index cannot be built without it); whether Ranipur's income is household or district income, since HDI uses GNI per capita and remittances are transfers, not output; and under-5 mortality or stunting, which life expectancy averages away.
Caveat to state aloud: HDI ranks averages and is silent on distribution - a block average can conceal a very poor half.
2. "Ranipur is richer, so fund Dhansu." Examine this argument critically using the income–health mismatch in the data.
Read the worked answer
Partly right, mostly lazy.
Where it is right: if income were the binding constraint, extra rupees in a high-income block would buy less HDI per rupee, because the income index is log-scaled and already near its ceiling.
Where it fails:
- It confuses income with development. Ranipur's ₹1.42 lakh is mandi- and remittance-driven, not evidence of public provisioning. An IMR of 38 and one PHC per 45,000 people show that private income is not converting into health.
- It ignores marginal returns. Ranipur's deficit is a cheap fix: an additional PHC, maternal care and immunisation outreach in a rich block can move IMR and life expectancy quickly per rupee. Dhansu's dropout rate responds to school quality, which is slow and costly.
- It treats "poor block" as a single thing. The two blocks are deprived on different dimensions - health in Ranipur, secondary schooling in Dhansu - so a single winner-takes-all allocation is the wrong instrument.
Judgement for the minutes: split the package dimension-wise rather than block-wise - health money to Ranipur, secondary-schooling money to Dhansu - and record that this is justified by marginal returns, not by which block is "worse". A single-block award would leave one deficit untouched for another six years.
3. Name one additional indicator the committee should add for this district and justify it by identifying which limitation of the HDI it repairs.
Read the worked answer
Recommended: under-5 mortality rate (or the % of children under five who are stunted).
Justification - which HDI limitation it repairs: life expectancy at birth is a period average that is dragged by adult mortality; a block can show a mediocre life expectancy while its child health is acceptable, or the reverse. Under-5 mortality isolates the child-health dimension and is far more sensitive to PHC coverage and immunisation, which is exactly what the ₹4 crore would buy. A block with IMR 38 almost certainly has a high under-5 rate, and the two together separate a genuinely unhealthy block from one with an ageing population.
Other fully acceptable answers, each with its limitation named:
- A gender-disparity measure (female literacy combined with female life expectancy, GDI-style) or the share of women in paid work - HDI averages do not penalise gender gaps, and here the female literacy gap is 54% vs 71%, a sharp, policy-relevant divide that a block average conceals.
- % of households with safe drinking water or sanitation - the environmental dimension, which HDI omits entirely and which drives both IMR and morbidity.
Marking note: credit only answers that name a specific, measurable indicator and state which HDI weakness - averages, inequality, gender, environment - it corrects. "Add more indicators" earns nothing.