Academic journal article Erasmus Journal for Philosophy and Economics

Lesser Degrees of Explanation: Further Implications of F. A. Hayek's Methodology of Sciences of Complex Phenomena

Academic journal article Erasmus Journal for Philosophy and Economics

Lesser Degrees of Explanation: Further Implications of F. A. Hayek's Methodology of Sciences of Complex Phenomena

Article excerpt

From the early-1950s on, F. A. Hayek was concerned, among his several other interests, with the development of a methodology of sciences that study systems of complex phenomena.1 According to Hayek, complex phenomena consist of a large number of elements interconnected (both to each other and to the external environment) in such a way as to give rise to an emergent order that possesses "certain general or abstract features which will recur independently of the particular values of the individual data, so long as the general structure [...] is preserved" (Hayek 1967 [1964], 26). The scientist of complex phenomena investigates these emergent orders and their properties, which cannot be fully reduced to the properties of the particular elements involved (Hayek 1967 [1964], 39). However, the knowledge that can be acquired about such orders is limited-in virtue of their complexity (and the comparatively narrow boundaries of human cognitive faculties)-as compared to the knowledge that scientists of simpler phenomena can acquire about the objects of their analyses. In particular, Hayek (1967 [1964], 27) argued that the number of elements of such complex systems is so large as to constrain the capacity of the scientist of complex phenomena to populate theoretical models with data sufficient to generate any but circumscribed explanations ("explanations of the principle") and predictions ("pattern predictions").2

The present paper aims to draw out and clarify a number of further implications of Hayek's methodology of sciences of complex phenomena that have heretofore been unspecified in the primary and secondary literature on Hayek. In particular, the paper seeks to elucidate the implications of Hayek's methodology with respect to the specific dimensions along which the scientist's knowledge of some complex phenomena may be limited. Hayek's fallibilism-i.e., the epistemological position according to which knowledge is never complete and, in any case, always revisable in the light of new evidence-was an essential (if not always explicit) aspect of his arguments against the defenders of both socialism (1948 [1935]; 1948 [1940]) and countercyclical monetary policy (1978 [1975]). Yet, despite the fact that his conceptions of both complex phenomena and the methodology appropriate to their investigation imply that ignorance might beset the scientist in respects beyond the aforementioned difficulties of data collection, he never explicated these latter implications of his methodology.

Predictive capacities are limited wherever such ignorance is rife. More to the point, the specificity of a scientific prediction depends on the extent of the relevant scientist's (or scientific community's) knowledge concerning the phenomena under investigation. The paper offers an account of the considerations which, according to Hayek's methodology, determine the extent to which a theory's implications prohibit the occurrence of particular events in the relevant domain. This theory of "predictive degree" both expresses and-as the phenomena of scientific prediction are themselves complex in Hayek's sense- exemplifies the intuition that the specificity of a scientific prediction depends on the relevant knowledge available.

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According to Hayek's epistemology, knowledge comes in two varieties: there is "scientific" (or "theoretical") knowledge ("knowledge of general rules") and there is empirical knowledge ("knowledge of the particular circumstances of time and place") (Hayek 1948 [1945], 80).3 The possibility of a "full explanation" or a "precise prediction of particular events"4 requires that the scientist possess both kinds of knowledge to a sufficient extent: "[s]uch prediction will be possible if we can ascertain [...] all the circumstances which influence those events. We need for this both a theory which tells us on what circumstances the events in question will depend, and information on the particular circumstances which may influence the event in which we are interested" (2014 [1961]). …

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