Table of Contents:
  • Introduction to probabilities, graphs, and causal models
  • Theory of inferred causation
  • Causal diagrams and the identification of causal effects
  • Actions, plans, and direct effects
  • Causality and structural models in social science and economics
  • Simpson's paradox, confounding, and collapsibility
  • Logic of structure-based counterfactuals
  • Imperfect experiments: bounding effects and counterfactuals
  • Probability of causation: interpretation and identification
  • The actual cause
  • Reflections, elaborations, and discussions with readers
  • The art and science of cause and effect.