A data-driven affordability model for income, rent, food, transport, utilities, savings, and independence in Ghana.
# Can a Young Ghanaian Afford Life?
A Ghana-first data science and storytelling project that models the real affordability of young adult life using official economic data, household expenditure sources, local price samples, and survey responses.
## Core question
> Can a young Ghanaian worker realistically afford independent life after rent, food, transport, utilities, mobile data, family support, savings, and basic personal needs?
## Why this matters
A salary can look decent until real life starts subtracting from it. This project examines the gap between what young people earn and what life actually costs in Ghana.
## Main outputs
- Affordability metrics: Survival Gap, Expense Ratio, Rent Burden, Food Burden, Transport Burden, Independence Score.
- Young Ghanaian Affordability Line (YGAL): a transparent monthly income threshold for different living scenarios.
- Persona analysis: national service worker, junior office worker, junior tech worker, freelancer, young family.
- Dashboard: interactive monthly budget simulator.
- Optional ML layer: financial stress classifier or survival gap regression.
- Final case study: a polished public-facing report.
## Suggested data layers
1. **Official Ghana data**: GSS Microdata, GSS StatsBank, GSS inflation reports, Ghana Open Data, Bank of Ghana.
2. **Local lived-cost data**: rent listings, food basket prices, transport fares, mobile data, utilities, toiletries.
3. **Survey data**: young Ghanaian income, housing, spending, savings, debt, family support, financial stress.
## Repository structure
```text
can-young-ghanaian-afford-life/
├── config/ # Project settings and assumptions
├── data/ # Raw, processed, survey, and template data
├── dashboard/ # Streamlit dashboard
├── docs/ # Charter, methodology, sources, ethics
├── notebooks/ # Step-by-step analysis notebooks
├── reports/ # Case study and executive summary templates
├─ …