Choosing One Capital Project for a Peri-Urban Ward
Ward 7 on the edge of Yangon Region grew from 21,000 to 28,400 residents between 2014 and 2019. A household survey found 31% of residents under 15, 29% aged 15–29, 34% aged 30–59 and 6% aged 60 and over. About 62% of employed adults work in garment and light-manufacturing factories within 6 km, and many men had previously worked in Thailand, but remittances have fallen. The ward has one 16-bed clinic staffed by two nurses, and a primary school running two shifts with 68 pupils per class. There is no piped water: households buy from tankers at roughly three times the municipal tariff. About 58% of dwellings are unregistered and stand on farmland. The township has one capital project to allocate to the ward this year and has shortlisted either expanding the clinic to 40 beds or building a secondary school.
1. Calculate the total dependency ratio and the child dependency ratio, and state what each implies for the choice between the clinic and the school.
Read the worked answer
Working-age population (15–59) = 34 + 29 = 63%. Dependants = 31 (under 15) + 6 (60+) = 37%.
- Total dependency ratio = 37 ÷ 63 = 0.59, i.e. about 59 dependants per 100 working-age people.
- Child dependency ratio = 31 ÷ 63 = 0.49.
Interpretation: nearly four in ten residents are dependants, and almost all of that burden is children rather than elderly people. Child dependency of 0.49 signals a young population still in the family-formation stage, so demand for school places is large now and will persist for at least a decade. The 29% aged 15–29 is the group about to form households, which means births - and therefore future primary and secondary enrolment - will keep rising even if fertility per woman falls.
The implication is not that health needs vanish; the 16-bed clinic serves 28,400 people, which is a thin service. But the age structure makes the school the more defensible single investment, because the school-age cohort is large, growing, and already visibly overcrowded at 68 pupils per class on two shifts.
2. Recommend one project and justify it. Name the single piece of data that would most change your recommendation.
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Recommend the secondary school, on three grounds. First, the age structure: 31% under 15 plus 29% aged 15–29 means the secondary-age cohort will grow for years regardless of policy, and the present arrangement - two shifts, 68 per class - is already a rationing device that cuts instruction time. Second, cost per beneficiary: a school building serves thousands of pupils for decades, while a 24-bed addition serves a smaller number at a time. Third, primary leavers in the ward currently have no local secondary place, so the school removes a barrier to completion rather than merely improving an existing service.
The clinic case is real but can be partly met short-term by outreach, mobile clinics and referrals. The most decision-changing datum would be travel time to the nearest hospital offering emergency obstetric and surgical care. If that hospital is more than about an hour away in traffic, maternal and injury deaths become the dominant risk and the clinic expansion becomes the stronger choice - 40 beds plus referral transport could then be justified. Attendance and repetition data from the primary school would be a secondary check on demand.
3. Explain why the ward's recorded birth rate might understate the need for school places.
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The denominator is wrong as well as the numerator. Crude birth rate divides births by total population, but this ward is receiving large inflows of young adult migrants (it grew 35% in five years). Those migrants inflate the population denominator without yet having children in the ward, which pushes the crude rate down even though the number of births is rising. Many arrived recently and will have children in the next few years.
On the numerator side, the survey records come from registered dwellings, yet 58% of dwellings are unregistered and on farmland. Births in those households are easily missed by ward administration, and some mothers travel to relatives or to a hospital in another township to deliver, so the event is registered elsewhere.
Any calculation of school demand should therefore use the count of children aged 0–4 and 5–9 from a household listing, and migration flows, rather than a crude birth rate. A single year's birth rate cannot show the shape of a cohort that will need classrooms in six and twelve years' time.