Lesser degrees of explanation: further implications of F. A. Hayek's methodology of sciences of complex phenomena


  • Scott Scheall Arizona State University




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.

Author Biography

Scott Scheall, Arizona State University

Scott Scheall teaches in the science, technology, and society department at Arizona State University. He received his PhD in philosophy from Arizona State in 2012. He is a former research fellow with Duke University’s Center for the History of Political Economy and, during the current academic year (2014-2015), is a postdoctoral fellow with the F. A. Hayek program for advanced study in philosophy, politics, and economics at George Mason University. Scott is co-editor of Research in the History of Economy Thought and Methodology.




How to Cite

Scheall, S. (2015). Lesser degrees of explanation: further implications of F. A. Hayek’s methodology of sciences of complex phenomena. Erasmus Journal for Philosophy and Economics, 8(1), 42-60. https://doi.org/10.23941/ejpe.v8i1.183