Lesser degrees of explanation: further implications of F. A. Hayek's methodology of sciences of complex phenomena
Keywords:Hayek, explanation, prediction, economics, methodology, complexity
F. A. Hayek argued that the sciences of complex phenomena, including (perhaps especially) economics, are limited to incomplete "explanations of the principle" and "pattern predictions". According to Hayek, these disciplines suffer from—what I call—a data problem, i.e., the hopelessness of populating theoretical models with data adequate to full explanations and precise predictions. In Hayek's terms, explanations in these fields are always a matter of "degree". However, Hayek's methodology implies a distinct theory problem: theoretical models of complex phenomena may be underspecified so that, even when all data is available, a full explanation could not be inferred from the model. Where the sciences of complex phenomena are subject to both the data and theory problems, explanations and predictions will be of even lesser "predictive degree". The paper also considers how to interpret Hayek's claim that pattern predictions are falsifiable.