We think it is important to lift people out of poverty and to guarantee them decent standards of living. However, to successfully promote economic growth, the high degree of complexity of the global market and regional industrial activities requires an integrated understanding of the ecosystem of complementary actors, knowhow, and capital. The way to do so is by conceptualizing productivity as an emerging property of a complex system made by simpler interacting parts. Complex systems are notoriously difficult to control but quantifying these interactions can identify the bottlenecks to growth and inform policy to bolster economic convergence. Using tools from economics, complex systems, and network science, we seek crucial insights that enable economic convergence.
The goal of this Research Topic is to collect contributions using complex network analysis to model economic systems and to gain insights into economic development which has proven to be a valuable scientific undertaking. We want to explore the potential applications of complex network analysis to foster our understanding of complex economic systems. We welcome contributions in the broad areas of:
• Mapping the relationship of complex economic activities to build Product and Industry Spaces at the global, regional, and local level;
• Tracking flows of knowhow in all its forms (business travels, social interrelationships between entrepreneurs, etc);
• Creating networks of related tasks and skills to estimate knockoff effects and productivity gains of automation;
• Investigating the dynamics of innovation via analysis of patents and inventions;
• Uncovering scaling laws and other growth trends able to describe the systemic increase in complexity of activities due to agglomeration, e.g. in cities;
• In general, any application of network analysis that can be used to further our understanding of economics.