We are looking for abstracts for the “Complex Networks in Economics and Innovation” satellite event of the Networks 2021 conference (Link).
You should submit an abstract of one-page abstract including one optional descriptive figure and caption. If you’re presenting at Networks 2021 or another of its satellites, there should not be too much overlap with your other contributed talks. Your abstract should be submitted to https://easychair.org/my/conference?conf=cnei21.
Economic convergence occurs when developing economies increase their productivity faster than developed economies. Society has a moral imperative to promote economic convergence because it is the most reliable path to lift people out of poverty and achieve decent standards of living. However, today’s global and regional economies are characterized by a high degree of complexity. Thus, economic convergence is best supported by improved understanding of the ecosystem of complementary actors, knowhow, and capital comprising various economic activities. Thus, productivity may be conceptualized 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.
This satellite will collect contributions using complex network analysis to model economic systems and to gain insights into economic development. Recent results on economic complexity, the principle of relatedness, and on the automation of workplace activities have shown how network analysis can uncover the pathways for innovation and economic development while highlighting potential issues. For example, the Product Space analysis showed how a bipartite country-product network reveals economic complexity that is strongly correlated with diversified export portfolios and future GDP growth. More generally, the principle of relatedness unveils hidden relationships between different industrial activities that can be leveraged to diversify an economy. Failure to exploit these opportunities impedes economic convergence through economic friction. There is much to add to this research, ranging from enhancing its spatial granularity (from global/regional economics to the intra-firm level), to exploring the complex dynamics of knowledge exchange (which is at the basis of the development of new skills and, therefore, of new economic activities), to applying similar techniques in new areas of economic research.
Building on the above, the aim of this satellite is to explore the potential applications of complex network analysis to foster our understanding of complex economic systems. Examples include:
Tenative Schedule (Date TBD. All times are EST):