Complexity Research in Economics: Past, Present, and Future

In this paper, we provide a brief overview of the field of complexity research in economics. We start the survey of the field with the research that emerged in the 1990s when, under the influence of earlier developments in the natural sciences (e.g., thermodynamics and chaos theory), the term complexity came into fashion to refer to theoretical ideas about how “ordered” patterns at an aggregate level can emerge from the interaction between heterogeneous agents at the microeconomic level. This gave rise to the notion of self-organization in dissipative systems, or “order at the edge of chaos,” to describe economic dynamics. Because disequilibrium plays a large role in these theories, these ideas worked very well in combination with a Schumpeterian view of the economy, which also stresses disequilibrium. In the current literature, economic complexity is mainly used to refer to the application of quantitative methods based on networks that can be created on the basis of very fine-grained data on production or trade. These data are used to produce aggregate measures of development, as well as to describe how production structures may evolve over time. This literature developed largely disconnected from the earlier complexity literature. The new economic complexity paradigm is largely void of economic theory and instead aims to provide a set of data reduction techniques that are used to characterize development. With regard to the outlook for complexity research in (Schumpeterian) economics, on the one hand, we feel that the potential for analyzing the economy as a dissipative, out-of-equilibrium system has not been fully exploited yet. In particular, we propose that–in line with the field of “Big History” (which aims to describe and analyze a coarse history of the universe since the Big Bang)–there is work to be done on the larger issues in economics, in particular climate change and sustainability.