# Ethiopia Financial Inclusion Forecasting System
A comprehensive system for forecasting financial inclusion in Ethiopia using time series methods and event impact modeling.
## Project Overview
This project builds a forecasting system to track Ethiopia's digital financial transformation, answering key questions from stakeholders including development finance institutions, mobile money operators, and the National Bank of Ethiopia.
### Key Questions Addressed
1. **What drives financial inclusion in Ethiopia?**
2. **How do events affect inclusion outcomes?**
3. **How will inclusion look in 2025-2027?**
## Project Structure
```
ethiopia-fi-forecast/
├── data/ # Data files
│ ├── raw/ # Raw input data
│ ├── processed/ # Processed data
│ └── enrichment_logs/ # Data enrichment logs
├── notebooks/ # Jupyter notebooks for each task
├── src/ # Source code modules
├── dashboard/ # Streamlit dashboard
├── models/ # Trained models and results
├── reports/ # Reports and figures
├── tests/ # Unit tests
└── requirements.txt # Python dependencies
```
## Installation
1. Clone the repository:
```git clone
github.com cd ethiopia-fi-forecast ```
2. Create a virtual environment (optional but recommended):
```python -m venv venv```
```source venv/bin/activate # On Windows: venv\Scripts\activate```
4. Install dependencies:
```pip install -r requirements.txt```
## Running the Project
Task 1: Data Exploration and Enrichment
```jupyter notebook notebooks/01_data_exploration.ipynb```
Task 2: Exploratory Data Analysis
```jupyter notebook notebooks/02_eda_analysis.ipynb```
Task 3: Event Impact Modeling
```jupyter notebook notebooks/03_event_impact_modeling.ipynb```
Task 4: Forecasting
```jupyter notebook notebooks/04_forecasting.ipynb```
Task 5: Dashboard
```streamlit run dashboard/app.py```
Data Sources
Global Findex Database: Account ownership and usage data
National Bank of Ethiopia: Financial access survey data
GSMA: Mobile money stat …