A systemic framework for the computational analysis of complex economies: An evolutionary-institutional perspective on the ontology, epistemology, and methodology of complexity economics

Abstract

This theses introduces the idea of a symbiotic relationship between evolutionary-institutional and complexity economics. It consists of two major contributions: The first contribution focuses on how the emerging research program of complexity economics can benefit from evolutionary-institutional theory. I show that complexity economics still lacks an adequate philosophical foundation. I explicate why such a foundation is needed if complexity economics is to promote further scientific progress and that such a foundation must consist of an adequate ontology, epistemology, and methodology. The following parts of the theses then draw upon institutionalist and social theory to develop these three aspects: I derive a definition of complex economic systems by identifying their essential properties. I then propose an epistemology that is based on the concepts of mechanism-based explanation, generative sufficiency, and an extended version of Uskali Mäki's concept of Models as Isolations and Surrogate Systems . I continue with some methodological considerations and argue that the method of 'Agent based computational economic modeling' must play a distinctive role for the analysis of complex economies. The second contribution of the theses shows how evolutionary-institutionalism can profit from a methodological transfer from complexity economics. In particular I argue that the method of 'Agent based computational modeling' can advance institutionalism both as a formalization device and by providing theoretical concepts that are useful for institutionalist theorizing itself. The theses closes by discussing a potential convergence of evolutionary-institutional and complexity economics and gives an outlook on avenues for further research.