dssgxuk / bmwi Goto Github PK

Unemployment Rate forecasting tool built for BMWi during the Data Science for Social Good Fellowship https://dssgxuk.github.io/bmwi/

Home Page: https://bmwi-tool.herokuapp.com/

Python 0.22% Jupyter Notebook 99.78% Shell 0.01%

python forecasting vector-autoregression machine-learning open-source data-science-for-social-good

bmwi's Introduction

📊 BMWI Prediction and Visualisation Tool

📖 Resources

You can find all the relevant links for project here:-

Regional Unemployment Forecasting Tool: here
Documentation: here
Video Tutorials: The tutorials to understand how the application works can be found here

🚀 About the Project

This project is a collaboration between German Federal Ministry for Economic Affairs and Energy (BMWi) and Data Science for Social Good Fellowship, UK. The goal of the project is to build a bottom-up forecasting model for predicting economic development in Germany based on regional data. The bottom-up approach focusses on the predictions at the Kreis (county) level rather than a federal level and provides an alternate approach to forecasting. The project draws on fine-grained data on the demographic, economic and sectoral structure of regions with the aim of improving economic forecasts during times of shocks. The unemployment rate in the different regions of Germany has been used as a proxy for the economic development in that region.

Presentation Video

🧰 About the tool

This is a forecasting tool built using Streamlit to forecast the unemployment rate for the next three months at the Kreis level in Germany. The purpose of the tool is to provide a complete pipeline from data analysis to model predictions in a simple easy-to-acess UI.