Growth Without Development? Comparing Two Districts
A regional planning unit reports that District A's gross domestic product per capita rose from $820 to $1,040 between 2018 and 2023, while District B's rose from $610 to $700. National officials cite District A as a success. Yet in A, the share of children finishing primary school fell from 78% to 71%, maternal deaths per 100,000 live births stayed near 310, and 46% of households still lack improved sanitation. District B recorded smaller income growth but raised primary completion from 64% to 77% and cut maternal deaths from 290 to 210. Both districts use the same national poverty line, but A's figure is based on a 2016 household survey and B's on a 2022 survey. Local officials in A argue that average income hides a growing gap between a new industrial zone and surrounding farming villages.
1. Which measure should the regional planning unit use to compare welfare progress in Districts A and B, and why is GDP per capita alone misleading in this case?
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GDP per capita measures average output per person, not welfare. In District A, higher average income coexists with falling primary completion, high maternal mortality and poor sanitation, so it cannot show whether people are healthier or better educated. It also hides distribution: the industrial zone may generate profits and wages for a small workforce while farming villages remain poor.
A better single summary is a subnational human development index or multidimensional poverty index, because both combine health, education and living standards. But I would publish a dashboard of primary completion, maternal mortality, sanitation and poverty headcount alongside income. If one composite must be chosen, its weights and components should be stated openly.
The poverty figures are also not comparable: A's 2016 survey predates B's 2022 survey, and prices and questionnaire design may differ. Before ranking the districts, the unit should harmonise the survey year, poverty line and consumption aggregate. The correct judgement is not that income is irrelevant, but that it is insufficient and is currently being compared unfairly.
2. A journalist writes: 'District A is developing faster than District B because its income grew more.' Evaluate this claim.
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The claim is only defensible if 'developing' is defined narrowly as income growth. On income, A grew by $220 per person, about 27%, and B by $90, about 15%, so A grew faster in absolute and proportional terms. But development includes health, education and living standards.
A's primary completion fell by 7 percentage points, maternal mortality remained around 310 and nearly half of households lack improved sanitation. B improved primary completion by 13 points and reduced maternal mortality by 80 deaths per 100,000. On those indicators B is developing faster.
The comparison is further weakened because A's poverty figure comes from 2016 and B's from 2022; A's poverty may have changed since. A's average income may also reflect an enclave industrial zone rather than broad-based improvement. A fair conclusion is that A had faster income growth but not faster human development on the available indicators. The journalist should report both growth and welfare trends, with data years and distributional evidence, rather than a single ranking.
3. Recommend two practical steps to make the poverty comparison between the districts more defensible.
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First, harmonise the survey instruments and reference periods. Use the same consumption module, recall period, poverty line and price deflators in both districts, and update A's 2016 data with a 2022 or 2023 survey. Without this, differences may reflect questionnaire changes or inflation rather than welfare.
Second, publish a transparent data note covering sampling design, response rates, price adjustments and confidence intervals, and disaggregate results by the industrial zone and farming villages. That would show whether growth is inclusive. If resources allow, small-area estimation combining the household survey with census data could produce comparable district poverty estimates.
The unit should also report non-income indicators alongside poverty. These steps do not require perfect data, but they make the comparison defensible and prevent officials from claiming success from incomparable figures.