Two Headlines From One Census: Did Family Planning or Out-Migration Slow This District?
District profile, 2011 to 2021. Population rose from 2.18 million to 2.42 million. The average crude birth rate over the decade was 24.6 per 1,000 and the crude death rate 7.4 per 1,000. Registers show 2.6 lakh out-migrants and 1.1 lakh in-migrants during the decade; the out-migrants are mostly men aged 20–34 going to Delhi and Surat, and remittances are estimated at ₹1,380 crore a year, about 19% of district income. The sex ratio fell from 903 to 887 females per 1,000 males. Literacy rose from 61% to 72%, and female literacy from 49% to 63%. The district has one sugar mill, 3,400 small workshops and no large engineering unit; 38% of the population is aged 15–34. A newspaper headline claims that 'slower growth proves the family planning programme has succeeded', while a local MLA says 'the district is emptying out'. Both cite the same census figures.
1. Using the demographic balancing equation, work out how far the gap between natural increase and actual growth is explained by net migration. Show every step.
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Step 1 - Natural increase rate. CBR − CDR = 24.6 − 7.4 = 17.2 per 1,000 per year = 1.72% per year.
Step 2 - Population expected from natural increase alone. Compound over ten years: 2.18 million × (1.0172)^10 = 2.18 × 1.186 ≈ 2.59 million. (Simple interest gives 2.55 million; use the compound figure and say so.)
Step 3 - Actual. 2.42 million. Shortfall = 2.59 − 2.42 ≈ 0.17 million, i.e. about 1.7 lakh people.
Step 4 - Net migration from the registers. Out-migrants 2.6 lakh minus in-migrants 1.1 lakh = 1.5 lakh net loss.
Step 5 - Compare. Net migration (1.5 lakh) accounts for close to the whole shortfall (1.7 lakh); the remaining ~20,000 can be attributed to a modest fall in the birth rate during the decade, plus under-registration.
Conclusion. Growth of 11% over the decade (about 1.05% a year) against a natural rate of 1.72% means roughly four-tenths of potential growth was removed by migration. The newspaper is not wrong that growth slowed, but the dominant cause is migration; the MLA is wrong that the district is emptying - it still grew by 11%. Registered migration also undercounts circular and seasonal movement, so the migration effect is probably larger still.
2. The sex ratio fell from 903 to 887 even though the district exports young men - which should raise it. Is this a paradox? Explain the mechanisms that can produce it.
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Why it looks like a paradox. Male out-migration removes men from the numerator, so the sex ratio at origin should improve. A fall therefore means stronger counter-forces are at work.
Mechanisms to weigh.
- Sex ratio at birth: prenatal sex selection after the spread of ultrasound, and neglect of girl children after birth, cut the number of females at the very base of the pyramid. This is usually the largest factor where the overall ratio falls steadily.
- Male-selective in-migration: the 1.1 lakh in-migrants may be mainly men drawn by the sugar mill, workshops and construction - this lowers the ratio even as out-migration of men raises it.
- Marriage migration: if the district is a net exporter of brides to other districts, young adult women leave permanently and are counted at their husband's residence.
- Enumeration bias: under-reporting of women and girls in some households.
- Female out-migration for work: domestic service and garment work in cities, smaller in volume than male flows but predominantly female.
How to settle it. Ask for the child sex ratio (0–6 years). If that is far below 887, factor 1 dominates and the deficit is being created at birth, not by migration. If the 0–6 ratio is near normal, factors 2 and 3 dominate. So the two observations are consistent - but they point to very different policies.
3. What does this profile imply for the district's dependency burden and its human development prospects, and which single intervention would you prioritise?
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Read the structure. 38% in the 15–34 group signals a large working-age population and a demographic dividend window. But with 1.5 lakh net out-migration concentrated in ages 20–34, the most productive workers are being exported, and the district retains proportionally more children and elderly - so the local dependency ratio worsens even as the national one improves. Remittances of ₹1,380 crore spread over 2.6 lakh out-migrants is about ₹53,000 per migrant per year, which suggests low-skill, often circular, migration rather than high-wage professional migration.
Read the human development signals. Overall literacy 72% against female literacy 63% shows the gap is concentrated among women; the absence of any large engineering unit beside 3,400 workshops means the secondary sector is underdeveloped and cannot absorb the school-leavers.
Judgement. The highest-return intervention is not a new degree college but a combination centred on the outflow: skill certification and portable training for 20–34 year-old migrants so that the same movement earns more, plus retention of girls through secondary school to close the 9-point literacy gap. Attracting one engineering or food-processing unit into the existing workshop cluster is the complementary step that would keep some of the 38% at home.
Caution: remittances are largely spent on consumption; without banking access and small-town infrastructure, they do not become productive investment. That is the assumption to test before planning.