CAUSAL ANALYSIS IN LOGIC ECONOMICS AND SOCIOLOGY

This first number has been dedicated to causal analysis in logic, economics and sociology and the essays have been arranged in a sequence that goes from the perception of some problems of causality at a philo- sophical and logical level to the formulation of mathematical models which, though in ~ much more limited sense, seek to solve the problem of the verification of causal relationships.

The first essay, by Maccagnolo, after some rapid references to certain moments in history, affirms that the human tendency to organize the multiplicity of the universe leads men to assume the universe itself as a system of causal rel~tionships. This happens in the mythical or magical vision; but it also happens in science if these relationships are not properly verified; as also in metaphysics, if it uses the principle of cause to demonstrate the existence of a first cause. Maccagnolo therefore wa.rns against the use of causal relationships loaded with anthropomorphic structures and not scientifically valid.

The problem of the scientific validity of causal relationships is also the subject of the essay by Rossi. In it he examines the position of Max Weber, who proposed to consider causal explanations (objectively valid) in the framework off a subjective system of evaluation (value judgements). In his essay Pietro Rossi proposes that this position should be further examined and he shows how the influence of the values transforms a causal explanation into a conditional explanation; for this reason, in order to proceed scientifically, it is necessary that the values premises should be considered as working hypotheses, explanatory models to be reta.ined or rejected depending on verification.

After these two essays of prevalently philosophical character, Pasqui- nelli's essay examines the concept of causal explanation in the various types of explanation. This is an epistemological essay which starts from the various meanings that the word explanation can have and arrives at the differentiation of explanations of a causal type (in the strict sense) from statistical and functional explanations.

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This essay permits one to understand the more limited sense in which the term "causal relationship" is understood when it is sought to verify it on empirical data through statistical correlation indices. The essays by Nowak, Boudon and Capecchi all lead in the same direction and their common objective is to seek to use the knowledge of statistical indices of association to verify a mathematical model in which the relationships between the variables are of the causal (or asymmetrical) type. Nowak analyses this problem in its most general terms and, after an analysis of the spurious correlations, arrives at a typology of the relationaships between three variables, in which the following axe con- sidered as aspects: the temporal order between two variables, the measure of statistical association between the same, the partial relationship between these two variables when a third variable is considered.

In dealing with these problems Boudon considers the contributions of Simon and Blalock on linear causal models and re-proposies Wright's coefficient of dependence, which permits an improved specification of the intensity of the relationships between the variables. Finally, Capecchi uses linear causal models for concrete application to a sociological investi- gation and the originality of this contribution lies in the demonstration that it is possible to use this mathematical instrument to identify a typology of subjects.

Nowak, Boudon and Capecchi are concerned with sociological pro- blems; the three last articles consider applications in the field of economics.

The articles by Majone, Arcelli and Lunghini are essentially concerned with a single subject: the form to give to the models of the social sciences - that is to say, the required content of the methodological and epistemological protopostulates - ff they are to be ~ operationally meaning- ful ' ; if they ~re to "say something" about the reality that it is wished to describe, explain, foresee or modify by means of them.

As Simon observed in an essay, in discussions of the methodology of science it is customary ~to avoid any use of the notion of causation and to speak instead of 'functional relations' and 'interdependence' among variables"; this as a reaction against the ~objectionable ontological and epistemological overtones that have attached themselves to the causal concept over the cause of the history of philosophy".

In scientific research, however, the use of the term ~cause" is cur- rent (and not always exact), since scientific research is always, in some

way, the search for ~causes". When, on the other hand, it is agreed that the concept of cause (as also that of 'structure') is a theoretical concept relating, that is to say, to a model of reality and not to reality

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itself - the problem of whether or not to retain it in the scientific vocabdary may be reduced (as Simon himself showed) "to the question of whether there is any meaning in the assertion that the relationship between two variables in a model is sometimes asymmetrical rather than symmetrical. If the answer to this question is in the negative, there would seem to be good reason for abandoning 'cause' in favour of its synonyms. If the answer is affirmative, the term 'cause', carefully scrubbed free of any undesirable philosophical adhesions, can perform a useful function and should be retained".

Majone's and Arcelli's articles are a contribution in this direction; an attempt to remove from the concept of "cause" all adhesions ines- sential or, more often, deleterious to its use in scientific analysis. Majone, in particular, clarifies the meaning of "variable" and of "functional relationship", underlining the influx of deterministic prejudices in the social scientits have always made of strict functional connections, in spite of the fact that the variable quantities investigated are related in a very loose why. He shows, furthermore, the relationship between errors of specification and the search for causes, and their consequences with regard to the criteria for accepting or rejecting a scientific hypo- thesis; and, finally, he clarifies the distinction between recursive and non-recursive (or interdependent) models. ArceIli, instead, goes deeper into the problem of causal order in economic models, as a technique of analysis of the economic models and, therefore, implicity, as technique of their construction. Arcelli's starting point is the notion of causal order proposed by Simon and elaborated by Papandreou, and therefore the distinction between exogenous and endogenous variables and the resolution of a model into its sub-sets..These concepts are exemplified, finally, in the discussion of the econometric model for the development of the Italian economy prepared by the Pnpi Commission.

The fate of the concept of "structure" is not dissimilar from that of the concept of "cause", both with regard to the need to use it and the risks that accompany its use. Recent advances in psychology, sociology, anthropology and economics have, however, made it possible to refine its meaning to the point of ranking it a concept that is, or could be, of central importance in developments in fields where some conception of the relationship between the "parts" and the "whole" that is not merely arithmomorphic is essential. Lunghini's essay proposes structural analysis on the one hand as an alternative and on the other as an integration of causal analysis; demonstrating the genesis, the content and the limits; proposing its formalization in terms of O. Lange's theory of system

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behaviour; noting its implications with regard to the problem of ag- gregation in economics, and to the ways of remedying the %bstractness" of modern economic macrodynamics which Lunghini shows to derive from a defect of specification: economic macrodynamics is based on the as-

sumptions that in order to know the laws of movement of a system it is sufficient to know the mode of action of its elements.

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