🏨 Forecasting and Explaining Hotel Demand in the EU (2015–2025)

Hybrid Econometric & Machine Learning Modeling with SHAP Explainability

This project develops a transparent and reproducible pipeline to forecast and interpret hotel demand across 26 European Union countries (2015–2025). It integrates macroeconomic and policy indicators using ARIMAX / SARIMAX and XGBoost / LightGBM models with SHAP explainability and scenario forecasting for 2025.

The workflow quantifies how GDP growth, policy stringency, and turnover dynamics shape post-pandemic tourism recovery across Europe.

📘 Explore the Analytical Workflow

• 🧹 Data Integration & Cleaning
• 🔍 Feature Engineering
• ⚙️ Model Estimation & Forecasting
• 📊 Model Interpretability & Economic Drivers
• 🌍 Scenario Forecasting & GDP Elasticities