This is a Virtual Satellite. Check on the Whova conference app to add this event to your Networks 2021 Agenda!
Call for Participation:
We are looking for abstracts for the “Complex Networks in Economics and Innovation” satellite event of the Networks 2021 conference.
- Submission Deadline: May 5, 2021
- Notification to Authors: May 21, 2021
- Submission of recorded talk (if that’s your chosen option): June 14, 2021
- Date of Satellite: Wednesday, June 30, 2021
- Daniel Rock, The Wharton School, University of Pennsylvania
- Hyejin Youn, Kellogg School of Management, Northwestern University
- Esteban Moro, Media Lab, MIT
- Yong-Yeol “YY” Ahn, Center for Complex Networks and Systems Research, Indiana University Bloomington
- Marta Gonzalez, Civil and Environmental Engineering, UC Berkeley
- Jiang Zhang, School of Systems Science, Beijing Normal University
- R. Maria del Rio-Chanona, Mathematical Institute, University of Oxford
- Lü Linyuan, University of Electronic Science and Technology of China
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:
- Mapping the relationship of complex economic activities at the global, regional, and local level;
- Tracking flows of knowhow in all its forms;
- Creating networks of related tasks and skills to estimate knockoff effects and productivity gains of automation;
- Investigating the dynamics of research and innovation via analysis of patents, inventions, and science;
- Uncovering scaling laws and other growth trends able to describe the systemic increase in complexity of activities due to agglomeration;
- In general, any application of network analysis that can be used to further our understanding of economics.
Tenative Schedule (Wednesday, June 30, 2021. All times are EST):
- 8:30AM Invited I: Unfolding innovation via the analysis of science and technology data. Lü Linyuan
- 9:10AM Invited II: Occupational mobility networks and the future of work. R. Maria del Rio-Chanona
- 9:50AM Contributed I: Process-driven network analysis of a mobile money system in Asia. Carolina Mattsson and Frank Takes.
- 10:10AM Contributed II: Discovering industries in networks of words. Juan Mateos-Garcia, Bishop Alex and Richardson George.
- 10:30AM Break
- 10:50AM Invited III: The latent structure of national scientific development. Yong-Yeol “YY” Ahn
- 11:30AM Contributed III: From code to market: Network of developers andcorrelated returns of cryptocurrencies. Lorenzo Lucchini, Laura Maria Alessandretti, Bruno Lepri, Angela Gallo and Andrea Baronchelli.
- 11:50AM Contributed IV: What is a Labor Market? Classifying Workers and Jobs Using Network Theory. James Fogel and Bernardo Modenesi.
- 12:10PM Invited IV: The Pathway of Innovation. Hyejin Youn
- 12:50PM Lunch Break
- 1:30PM Invited V: Universal resilience of labor networks. Esteban Moro
- 2:10PM Invited VI: From Urban Sciences to their Spatial Complexities. Marta Gonzalez
- 2:50PM Contributed V: How to Govern Facebook. Seth Benzell and Avinash Collis.
- 3:10PM Contributed VI: The network limits of infectious disease control via occupation-based targeting. Demetris Avraam, Nick Obradovich, Niccolò Pescetelli, Manuel Cebrian and Alex Rutherford.
- 3:30PM Break
- 3:50PM Invited VII: Digital capital and superstar firms. Daniel Rock
- 4:30PM Contributed VII: Measuring Fraudulent Transactions On Complex Economic Networks Using Optimality Gap. Danilo Bernardineli and Wenjia Hu.
- 4:50PM Contributed VIII: Local connections drive global structure for technological innovation. Dion O’Neale, Demival Vasques Filho and Shaun Hendy.
- 5:10PM Invited VIII: Revealing Hidden Information on Large Social and Economic Networks by Machine Learning. Jiang Zhang