The opening phrase of this introduction was the motto for the Cowles Commission for Economic Research: science is measure-ment. The Cowles Commission initiated the methods most commonly used in econometrics in America today, and its ideas, in a very primitive form, play a central role in my argument. I will focus on the structures of econometrics in this book, but not because of either the successes or the failures of econometrics as a science;
rather because of the philosophic job it can do. We may see intui-tively that correlation has something to do with causality. But intui-tion is not enough. We need an argument to connect probabilities with causes, and we can find one in econometrics.
My ultimate position is more radical. The pure empiricist should be no more happy with laws than with capacities, and laws are a poor stopping-point. It is hard to find them in nature and we are always having to make excuses for them: why they have exceptions—big or little; why they only work for models in the head; why it takes an engineer with a special knowledge of real materials and a not too literal mind to apply physics to reality.14 The point of this book is to argue that we must admit capacities, and my hope is that once we have them we can do away with laws. Capacities will do more for us at a smaller metaphysical price.
My aim in this argument has been to make causes acceptable to those who demand a stringent empiricism in the practice of science.
Yet I should be more candid. A measurement should take you from data to conclusions, but probabilities are no kind of data. Finite fre-quencies in real populations are data; probabilities are rather a kind of ideal or theoretical representation. One might try to defend probabilities as a good empirical starting-point by remarking that there are no such things as raw data. The input for any scientific infe-rence must always come interpreted in some way or another, and probabilities are no more nor less theory-laden than any other concepts we use in the description of nature. I agree with the first half of this answer and in general I have no quarrel with using theo-retical language as a direct description of the empirical world. My suspicion is connected with a project that lies beyond the end of this book. Yet it colours the arguments throughout, so I think it should be explained at the beginning.
The reason I am uneasy about taking probabilities as an empirical starting-point is that I do not believe in these nomological regular-ities, whether they are supposed to hold for 100 per cent of cases or for some other percentage. I do not see many around, and most of those I do see are constructions of the laboratory. The more general picture I have in view takes the capacities which I argue for in this book not just to stand alongside laws, to be equally necessary to our image of science, but rather to eliminate the need for laws altogether.
Capacities are at work in nature, and if harnessed properly they can be used to produce regular patterns of events. But the patterns are tied to the capacities and consequent upon them: they do not exist everywhere and every when; they are not immutable; and they do not license counterfactuals, though certain assumptions about the arrangement of capacities may. They have none of the usual marks they are supposed to have in order to be counted as nomologicals; and there is no reason to count them among the governors of nature.
What makes things happen in nature is the operation of capacities.
I will argue that the metaphysics that underpins both our experi-mental and our probabilistic methods for establishing causes is a metaphysics of capacities. One factor does not produce the other haphazardly, or by chance; it will do so only if it has the capacity to do so. Generic causal laws record these capacities. To assert the causal law that aspirins relieve headaches is to claim that aspirins, by virtue of being aspirins, have the capacity to make headaches dis-appear. A single successful case is significant, since that guarantees that the causal factor does indeed have the capacity it needs to bring about the effect. That is why the generic claim and the singular claim are so close. Once the capacity exhibits itself, its existence can no longer be doubted.
This book begins with a defence of causal laws, which have received rough treatment at the hands of a number of empiricist philo-sophers. Hume would reduce them all to associations; Mach and Russell would cast them out of science. But in the last fifteen years in philosophy of science, causes have become more acceptable. A number of authors already discussed—Clark Glymour, Elliott Sober and Ellery Eells, or Wesley Salmon—maintain that Russell and Mach were wrong. In addition to the concept of a functional relation or a probabilistic law, science needs a separate notion of causal law as well. I want to argue in this chapter that they have not gone far enough: in addition to the notion of causal law, we also need the con-cept of capacity; and just as causal laws are not reducible to func-tional and statistical laws, so too ascriptions of capacity are not reducible to causal laws. Something more is required.
Perhaps, though, that is a misleading way to put the point. For the concept of causation that is employed in most of these authors is already a concept of capacity; and I am very glad to have recognized this, since it brings my views more into line with those of others. For I maintain that the most general causal claims—like 'aspirins relieve headaches' or 'electromagnetic forces cause motions perpendicular to the line of action'—are best rendered as ascriptions of capacity.
For example, aspirins—because of being aspirins—can cure head-aches. The troublesome phrase 'because of being aspirins' is put there to indicate that the claim is meant to express a fact about properties and not about individuals: the property of being an aspirin carries with it the capacity to cure headaches. What the capa-cities of individuals are is another, very complex, matter. For instance, must the relevant conditions for the exercise of the capacity be at least physically accessible to the individual before we are willing to ascribe the capacity to it? These are questions I will have nothing to say about.
Rather I offer, in its stead, another version of empiri-cism that I think can be taken seriously—and has been by large numbers of scientists since the seventeenth century—the empiricism of testing and measuring, an empiricism already too demanding to admit much of modern theoretical science, especially physics, which is prone to be driven more by the needs of mathematics than it is by the phenomena. Nevertheless, it does not exclude tendencies and causes.
Still, to say this is to side-step a crucial criticism. For the testing of causal claims at any level—whether claims about a single happening, about a more generic causal law, or about capacities and their opera-tions—necessarily presupposes some metaphysical assumptions that cannot be tested by the same stringent logic. Yet this in no way dis-tinguishes these claims from any other claims about the world. This is obvious in the case of laws of association. No regularity of pattern will tell us that a law obtains unless we know enough to ensure that the connections involved are law-like to begin with. Otherwise we are forced back to the hypothetico-deductive method, and that method provides no test at all. I think the same is universally true. Even what are supposed to be the 'purest' empirical assertions, like 'this facing surface is red', employ concepts which cannot be given ostensively but only make sense relative to an entire structure of other concepts in which they are embedded. Nor can they be tested, as many hoped, by pure inspection, without a rich background of assumptions, both physical and metaphysical, assumptions not much different in kind from those necessary to test causal claims.