Synopses & Reviews
Causation is asymmetrical in many different ways. Causes precede effects; explanations cite causes not effects. Agents use causes to manipulate their effects; they don't use effects to manipulate their causes. Effects of a common cause are correlated; causes of a common effect are not. This book by one of the preeminent philosophers of science writing today offers the most comprehensive account available of causal asymmetries. It is a major book for philosophers of science that will also prove insightful to economists and statisticians.
Table of Contents
Introduction; 1. Causation and its asymmetries; 2. Metaphysical pictures and wishes; 3. Is causation a relation among events?; 4. Causation, regularities and time: Humeâs theory; 5. Causation and independence; 6. Causation, independence and causal connection; 7. Agency theory; 8. Causal generalizations and agency; 9. The counterfactual theory of causation and the independence of causes; 10. Independence and counterfactual dependence; 11. Counterfactuals, agency, and independence; 12. Agency, counterfactuals and independence; 13. Causation, explanation and laws; 14. Causation, explanation, and independent alterability; 15. Probabilistic causation; 16. Causation and conditional probabilities; 17. Causal graphs and conditional probabilistic dependencies; 18. Intervention, robustness and probabilistic dependence; 19. Interventions and conditional probabilities; 20. Operationalizing and revising the independence theory; 21. Probability distributions and causation; 22. Complications and conclusions.