Venetian Sea Levels, British Bread Prices, and the Principle of the Common Cause
- 1 June 2001
- journal article
- Published by University of Chicago Press in The British Journal for the Philosophy of Science
- Vol. 52 (2) , 331-346
- https://doi.org/10.1093/bjps/52.2.331
Abstract
When two causally independent processes each have a quantity that increases monotonically (either deterministically or in probabilistic expectation), the two quantities will be correlated, thus providing a counterexample to Reichenbach's principle of the common cause. Several philosophers have denied this, but I argue that their efforts to save the principle are unsuccessful. Still, one salvage attempt does suggest a weaker principle that avoids the initial counterexample. However, even this weakened principle is mistaken, as can be seen by exploring the concepts of homology and homoplasy used in evolutionary biology. I argue that the kernel of truth in the principle of the common cause is to be found by separating metaphysical and epistemological issues; as far as the epistemology is concerned, the Likelihood Principle is central.Keywords
This publication has 8 references indexed in Scilit:
- CausalityPublished by Cambridge University Press (CUP) ,2009
- Independence, Invariance and the Causal Markov ConditionThe British Journal for the Philosophy of Science, 1999
- TestabilityProceedings and Addresses of the American Philosophical Association, 1999
- Conditioning and InterveningThe British Journal for the Philosophy of Science, 1994
- How to Tell When Simpler, More Unified, or LessAd HocTheories will Provide More Accurate PredictionsThe British Journal for the Philosophy of Science, 1994
- Sober's Principle of Common Cause and The Problem of Comparing Incomplete HypothesesPhilosophy of Science, 1988
- Optimal individual growth and reproduction in perennial species with indeterminate growthEvolutionary Ecology, 1987
- Why do we Sometimes get Nonsense-Correlations between Time-Series?--A Study in Sampling and the Nature of Time-SeriesJournal of the Royal Statistical Society, 1926