st-vin/africa-economic-outlook

Project uses GDP growth data to analyze, forecast, and interpret economic trends for Kenya, South Africa, and Nigeria. By providing insights on economic trajectories, it can help policy makers, investors, and NGOs make decisions that promote sustainable economic development. # Africa Economic Outlook: GDP Growth Forecasting MVP This project is a Minimum Viable Product (MVP) for forecasting the GDP growth of key African economies. It uses a time-series forecasting model (Prophet) to predict annual GDP growth and presents the results in an interactive web application built with Streamlit. ## Project Overview The primary goal of this project is to provide a simple yet effective tool for understanding and forecasting GDP growth in Kenya, Nigeria, and South Africa. The application allows users to: - Visualize historical GDP growth trends. - View a 5-year forecast (2021-2025) with confidence intervals. - Analyze the performance of the forecasting model. - Understand the key drivers of the GDP growth forecast. - Compare economic performance across the selected countries. ## What to Expect The main output of this project is a Streamlit dashboard. The dashboard is organized into several sections: 1. **Historical Trends and 5-Year Forecast**: An interactive chart showing historical GDP growth and the forecasted values for the selected country. 2. **Model Performance**: Key metrics (RMSE, MAE, MAPE) evaluating the model's accuracy on the test set (2016-2020). 3. **Feature Importance**: A bar chart showing the average absolute effect of different features (like inflation, fiscal balance, and trend) on the GDP growth forecast. 4. **Country Comparison and Key Insights**: - A table comparing model performance across all countries. - A line chart comparing historical GDP growth for all countries. - Textual insights from the Exploratory Data Analysis (EDA) and model performance. ### Visualizations Here are some of a few of the visualizations you can expect from this project: **Historical GDP Growth Comparison** **GDP Growth Distribution by Country** ## Setup and Installation To run this project, you need to have Python installed. You can set up the project using either `pip` with a virtual environment or `uv`. ### Using `uv` (Recommended …