🧠 Simulated Datasets & Guides for Causal Inference in Investment Management

CausalInvestData is a curated R package offering high-quality simulated datasets and applied tutorials for learning and teaching causal inference in complex real-world contexts.

It is ideal for: - Policy analysts - Economists - Data scientists - Students and instructors

🔍 What You’ll Find Here

• 📊 Datasets for evaluating treatment effects using matching, weighting, IV, regression discontinuity, and more.
• 📚 Tutorials explaining:
  • Propensity score methods
  • Causal forests
  • Difference-in-differences
  • Synthetic control
  • Mediation analysis
  • Double machine learning
• 🧪 Simulation code for understanding bias, identification, and heterogeneity.

🚀 Start Exploring

Visit the Articles to begin applying modern causal inference techniques with ready-to-run R code.

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Built and maintained by Acalytica, empowering learning through causal reasoning and simulation.