Fast GSDP growth and falling garment jobs in a southern Karnataka district
A district in Karnataka's southern plateau reports GSDP growth of 8.4% a year for five years, driven by IT-enabled services and a new industrial estate. But registered manufacturing units fell from 410 to 355, and garment employment fell from 9,000 to 5,600, of whom 70% were women. Real estate and logistics grew. The district's per capita income is above the state average, yet 62% of workers are in informal employment without written contracts, female labour force participation fell 6 percentage points, and government school enrolment fell 4% while private school enrolment rose. Literacy is 79%, and 22% of Class 3 children cannot read a Class 2 text. The deputy commissioner must present a 'development' report that is not just about GSDP.
1. How can GSDP grow at 8.4% while garment jobs fall from 9,000 to 5,600? Is the district developing?
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GSDP measures the value of output produced in the district, not the number of jobs or who gets them.
Why the two can coexist:
- IT-enabled services and logistics have high output per worker; a small number of well-paid jobs can raise total output even as labour-intensive garment units close.
- Automation and competition in garments reduce employment while output per remaining unit may rise.
- Displaced workers move into informal work - street vending, domestic work, construction - which is counted in GSDP but provides no contract, no leave and no pension.
- Per capita income rises faster if population growth is low; an average can rise while the median worker's position worsens.
Is it development? The fall in female labour force participation by 6 percentage points is decisive: 70% of the lost garment jobs were held by women, and women leaving paid work is a loss of income and autonomy, not a sign of progress. Add 62% informal employment and 22% of children unable to read a simple text, and the answer is that the district is growing without developing in the capability sense - income is rising, security and human development are not keeping pace. The report should say so plainly.
2. Name four indicators you would add to the report, and explain what each would reveal that GSDP cannot.
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- Share of informal employment and real wages of garment workers. GSDP cannot show whether work has contracts, paid leave or a wage that keeps up with prices. Real wages reveal whether the growth is reaching the workers who lost jobs.
- Female labour force participation and its reasons. The 6-point fall may reflect women withdrawing because of unsafe transport, no crèche, or household care burdens. GSDP is silent on all three, yet they decide whether growth is inclusive.
- Learning outcomes, not just enrolment. The 22% figure for Class 3 reading shows that private enrolment growth may not mean learning. Human capital is the base of future growth; enrolment counts seats, not skills.
- Distribution and environment: Gini or wage share, plus air and water quality. A rising average can hide a widening gap and rising pollution. Both affect whether growth can continue.
A useful rule: pair every income indicator with one distributional and one human-development indicator. Otherwise the report becomes a celebration of one number and hides the adjustment costs borne by workers who lost the garment jobs.
3. Suggest two policy measures for the district, and explain how you would judge whether they worked.
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Measure 1: Skill and workplace transition for displaced garment workers. A short course in industrial machine operation, quality control and logistics, tied to the new estate's employers, with a crèche and safe transport. Judgement: not the number trained, but placement rate, the wage compared with the old garment wage, and retention after six months. If 500 women are trained and 80 are placed, the scheme has failed even if the attendance register looks excellent.
Measure 2: Learning recovery in primary classes. A targeted programme of 60–90 minutes a day for children who cannot read, with teacher training and simple assessment. Judgement: baseline and endline reading scores for the same children, plus the share of schools that sustain the practice after the funds end. A one-time test rise that disappears next year is not a result.
Both measures address the same flaw: the district treated GSDP growth as the goal. Evaluation should use outcome indicators, compare them with a similar district or an untreated group, and publish the results. The test of policy is whether the median woman worker and the median Class 3 child are better off, not whether another tower was built.