Economic Fitness and Complexity (EFC) methods and metrics describe economies as evolutionary processes of ecosystems of industries, technologies and infrastructures that are globally interconnected. This data-driven approach is multidisciplinary and addresses emerging phenomena in economics from various points of view: it offers new opportunities to constructively describe technological ecosystems, analyse their structures, understand their dynamics, and introduce new metrics. 

This series of innovative and trans-disciplinary elements has made it possible to analyse and forecast economic growth of countries at a higher level of accuracy than traditional analyses, and has offered scholars and policy makers a tool to predict country and regional trajectories of economic diversification. Several international organisations have adopted EFC methods: the World Bank has introduced Economic Fitness among the World Development Indicators, and the Joint Research Center of the EU Commission has recently adopted EFC for the analysis of the competitiveness of EU countries and for the optimal development and planning of innovation.

EFC methods have gained increasing popularity across multiple disciplines and fields in social sciences, such as economic development, evolutionary economics, economic geography, economics of science, and technological change. Following the increased adoption of Economic Fitness and Complexity methods to study the process of economic development, technological trajectories and scientific production, and the growing demand especially from young scholars interested in implementing these methods in their research, we announce a five-day spring school (5-9 June 2022) to be held at the Enrico Fermi Research Centre (Rome), in collaboration with UNU-MERIT (Maastricht) and with the support of the Young Scholar Initiative of the Institute for New Economic Thinking.

The school builds on recent efforts to gather and synthesize systematically the tools made available by the Economic Fitness and Complexity framework. We aim at reaching young scholars (postgraduate students, including Master’s and PhD), early career researchers and practitioners. The programme will be divided in two parts. In the first part, participants will be offered training on the main tools of the fitness toolbox, such as the economic fitness and complexity algorithm, measures of relatedness, and network inference using random graphs and multilayer networks. In the second part, the school will feature speakers presenting cutting-edge, frontier contributions from the fitness and complexity literature, covering topics such as economic development, technological and scientific production, sustainability, labour markets, and industrial policy.