The paper displays the similarity between the theory of probabilistic causation developed by Glymour et al. since 1983 and mine developed since 1976: the core of both is that causal graphs are Bayesian nets. The similarity extends to the treatment of actions or interventions in the two theories. But there is also a crucial difference. Glymour et al. take causal dependencies as primitive and argue them to behave like Bayesian nets under wide circumstances. By contrast, I argue the behavior of (...) Bayesian nets to be ultimately the defining characteristic of causal dependence. (shrink)

Is the common cause principle merely one of a set of useful heuristics for discovering causal relations, or is it rather a piece of heavy duty metaphysics, capable of grounding the direction of causation itself? Since the principle was introduced in Reichenbach’s groundbreaking work The Direction of Time (1956), there have been a series of attempts to pursue the latter program—to take the probabilistic relationships constitutive of the principle of the common cause and use them to ground the direction of (...) causation. These attempts have not all explicitly appealed to the principle as originally formulated; it has also appeared in the guise of independence conditions, counterfactual overdetermination, and, in the causal modelling literature, as the causal markov condition. In this paper, I identify a set of difficulties for grounding the asymmetry of causation on the principle and its descendents. The first difficulty, concerning what I call the vertical placement of causation, consists of a tension between considerations that drive towards the macroscopic scale, and considerations that drive towards the microscopic scale—the worry is that these considerations cannot both be comfortably accommodated. The second difficulty consists of a novel potential counterexample to the principle based on the familiar Einstein Podolsky Rosen (EPR) correlations in quantum mechanics. (shrink)

Social sciences face a well-known problem, which is an instance of a general problem faced as well by psychological and biological sciences: the problem of establishing their legitimate existence alongside physics. This, as will become clear, is a problem in metaphysics. I will show how a new account of structural explanations, put forward by Frank Jackson and Philip Pettit, which is designed to solve this metaphysical problem with social sciences in mind, fails to treat the problem in any importantly new (...) way. Then I will propose a more modest approach, and show how it does not deserve the criticism directed at a prototype by Jackson and Pettit. (shrink)

Although statistical techniques like regression analysis and path analysis are widely used in the biomedical, behavioral and social sciences to make causal inferences there has been surprisingly little philosophical discussion of the details of such techniques and of the conceptions of causation and explanation implicit in them. There also has been relatively little attempt to compare such techniques with various probabilistic models of causation and explanation in the philosophical literature.In this paper I explore, for reasons of space in a very (...) sketchy and schematic way, some issues in philosophy of science raised by regression analysis. One general conclusion I reach is that it is considerably less obvious than one might suppose that the philosophical theories alluded to above are plausibly viewed as reconstructions of regression techniques. (shrink)

Discontented people might talk of corruption in the Commons, closeness in the Commons and the necessity of reforming the Commons, said Mr. Spenlow solemnly, in conclusion; but when the price of wheat per bushel had been the highest, the Commons had been the busiest; and a man might lay his hand upon his heart, and say this to the whole world, – ‘Touch the Commons, and down comes the country!’.

In this paper I argue that economic theories have never been able to provide a coherent explanation of the causation requirement in tort law. The economic characterization of this requirement faces insurmountable difficulties, because discourse on tort liability cannot be reduced to a cost-benefit analysis without a loss of meaning. More seriously, I try to show that by describing causation in economic terms, economic theories offer an image of the practice in which the participants incur in logical contradictions and develop (...) patterns of inference that are far from intuitive. For this reason, efficiency cannot be the fundamental principle underlying tort law. Finally, I suggest that economic analysis of law can provide a genuine explanation of certain aspects of legal practice if it relinquishes its reductionist claims. (shrink)

Abstract In Section 1 I examine the use of probabilistic data to establish causal conclusions in non?experimental research. In Section 2 I show that the probabilities involved in such research are inhomogeneous ?mixed? probabilities. Section 3 then argues that such mixed probabilities are responsible for the way common causes screen off correlations between their joint effects. Section 4 concludes that mixed probabilities are therefore crucial for the nature of the causal relation itself.

Peter Urbach has argued, on Bayesian grounds, that experimental randomization serves no useful purpose in testing causal hypothesis. I maintain that he fails to distinguish general issues of statistical inference from specific problems involved in identifying causes. I concede the general Bayesian thesis that random sampling is inessential to sound statistical inference. But experimental randomization is a different matter, and often plays an essential role in our route to causal conclusions.

It is widely held that the size of a probability makes no difference to the quality of a probabilistic explanation. I argue that explanatory practice in statistical physics belies this claim. The claim has gained currency only because of an impoverished conception of probabilistic processes and an unwarranted assumption that all probabilistic explanations have a single form.