Economic Drivers of Cryptocurrency Adoption

• Difficulty: Beginner (Economics and Data Science)
• Term Length: Fall 2025 - Winter 2026

Description

This project investigates whether macroeconomic conditions can predict cryptocurrency adoption. We built an Economic Anxiety Index combining inflation expectations, monetary expansion, and recession fears, then tested its relationship with on-chain crypto adoption metrics. Our analysis found a strong correlation (r = 0.67, p < 0.0001), supporting the “crypto as inflation hedge” narrative with empirical evidence.

Key Findings

Explore our live dashboard, methodology, and complete findings here: Economic Drivers of Cryptocurrency Dashboard

Skills Gained

• Data collection from FRED API and blockchain data providers
• Statistical analysis: correlation, Granger causality, time series validation
• Machine learning comparison: Ridge, Random Forest, XGBoost, LSTM
• Honest model evaluation and overfitting detection
• Building live dashboards with real-time data updates

Technical Details

• Data Analysis: Python (pandas, scikit-learn, statsmodels)
• Visualization: Matplotlib, Seaborn, Recharts
• Dashboard: Next.js + Vercel with live FRED data integration
• Data Integration: Economic and blockchain datasets