Mincerian wage analysis of GLSS 7 (Ghana) — Data for Impact Datathon 2026, UCC. Returns to education in formal vs informal sectors.
# Degrees Without Dividends
**Data for Impact Datathon 2026 — UCC Data Literacy Week | 3rd June 2026**
*Department of Data Science and Economic Policy, University of Cape Coast*
> *"More schools will not close this gap. More formal jobs will."*
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## What This Project Is About
Ghana has invested heavily in education. Tertiary enrolment tripled in two decades. Yet over 80% of Ghana's workforce remains in the informal economy — where, as this analysis shows, education earns almost nothing.
Using the Ghana Living Standards Survey 7 (GLSS 7, 2016/17) and Mincerian wage regression, we follow 4,029 working-age adults to answer one question:
**Does education pay off — and for whom?**
The answer depends entirely on which sector you end up in.
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## Key Findings
| Finding | Result |
|---------|--------|
| Aggregate return to schooling | **13.8% per year** (95% CI: 12.8–14.8%) |
| Formal sector return | **17.3% per year** (p **Note:** Raw GLSS 7 `.sav` data files are not included in this repo — they are proprietary survey microdata (~440 MB). See Data below for where to download them.
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## Data
**Survey:** Ghana Living Standards Survey 7 (GLSS 7)
**Fielded by:** Ghana Statistical Service (GSS)
**Period:** 2016/17
**Original sample:** 59,864 individuals
**Analysis sample:** 4,029 working-age adults with valid wage records (after winsorising at 1st/99th percentile)
### Download the GLSS 7 Microdata
The data is publicly available (free registration may be required):
| Source | Link |
|--------|------|
| **Ghana Statistical Service (official microdata portal)** |
statsghana.gov.gh |
| **World Bank Microdata Library** |
microdata.worldbank.org |
After downloading, place these three files in the **project root** (they are gitignored and will be found automatically by the Rmd):
```
g7sec0.sav — Section 0: household roster
g7sec1_5.sav — Sections 1–5: individual characteristics, …