Afomiat/ethiopia-fi-forecast

# Forecasting Financial Inclusion in Ethiopia This project tracks, models, and forecasts Ethiopia's digital financial transformation using time series regression and event impact simulation. Built as a pair-programming project for a consortium of stakeholders—including development finance institutions, mobile money operators, and the National Bank of Ethiopia (NBE)—this system analyzes progress on two core targets defined by the World Bank's Global Findex: 1. **Access** — Account Ownership Rate (`ACC_OWNERSHIP`) 2. **Usage** — Digital Payment Adoption Rate (`USG_DIGITAL_PAYMENT`) --- ## 📁 Repository Structure ``` ethiopia-fi-forecast/ ├── .github/workflows/ │ └── unittests.yml # GitHub Actions CI unit test runner ├── data/ │ ├── raw/ # Raw Excel books and exported baseline CSVs │ │ ├── ethiopia_fi_unified_data.xlsx │ │ ├── Additional Data Points Guide.xlsx │ │ ├── reference_codes.xlsx │ │ ├── ethiopia_fi_unified_data.csv │ │ ├── ethiopia_fi_impact_links.csv │ │ └── reference_codes.csv │ └── processed/ # Enriched and clean datasets ready for modeling │ ├── ethiopia_fi_unified_data.csv │ ├── ethiopia_fi_impact_links.csv │ └── reference_codes.csv ├── notebooks/ # Jupyter Notebook deliverables for each task │ ├── 02_exploratory_data_analysis.ipynb │ ├── 03_event_impact_modeling.ipynb │ └── 04_forecasting.ipynb ├── src/ # Core modules and scripts │ ├── extract_sheets.py # Parses raw Excel workbooks and outputs CSVs │ ├── enrich_dataset.py # Appends observations, events, and impact links │ ├── run_eda.py # Runs exploratory data analysis and exports figures │ ├── impact_model.py # Simulates event shocks using mathematical ramp functions │ └── forecaster.py # Performs OLS trend regressions and scenario simulations ├── dashboard/ │ └── app.py # High-fidelity interactive Streamlit dashboa …