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Conference Website CCS 2017

Institutions, Industry Structure, Evolution - Complexity Approaches to Economics

Satellite Meeting of the Conference on Complex Systems (CCS) 2017 in Cancun, Sep. 17-22, 2017
The satellite will take place on Thursday, in Cozumel 5.



Torsten Heinrich
Institute for New Economic Thinking (INET) at the Oxford Martin School
University of Oxford, UK

Claudius Gräbner
Institute for the Comprehensive Analysis of the Economy (ICAE)
Johannes Kepler University Linz, Austria






9.00 - 10.30

Hyejin Youn

Urbanisation and Innovation (tentative title)

10.30 - 11.00

coffee break


Contributed Papers




11.00 - 11.45

Stojan Davidovic, Mirta Galesic and Gerd Gigerenzer

The 2007–2009 financial crisis and paradigm shift: A study of analogies in the history of economics

11.45 - 12.30

Carlos Perez and Katya Perez Guzman

The structural drivers behind neoextractivism: a discussion about edge centralities

12.30 - 14.30

lunch break


14.30 - 15.15

Francesca Lipari, Alberto Antonioni and Massimo Stella

Investigating the coevolution of institutions within an adaptive multiplex network model

15.15 - 16.00

Francois Hulot, Mariano Beguerisse and Neave O'Clery

The network structure of industry agglomeration

16.00 - 16.30

coffee break


16.30 - 17.15

Xin Zhang, Ling Feng, Yonatan Berman, Ning Hu and H. Eugene Stanley

Exacerbated vulnerability of coupled socio-economic risk in complex networks


Recent developments in fields such as network science, artificial intelligence and evolutionary dynamics have revolutionized the modern approach to complex adaptive systems. It became possible to work with systems of massive complexity. The limits of computation power and data storage capacity as well as those in the minds of the researchers were extended considerably. Methods, approaches, and objectives that had never seriously been considered before now became feasible.

In economics, the application of these advances is just at the beginning - but it is as scientifically promising as it is urgently needed: Agent-based models allow to work with truly microfounded models with massive numbers of agents, simulating entire sectors, or even entire economies. Advances in machine learning and the improved situation of available data allow the efficient estimation and calibration of those models. Models from complex systems science, network science and evolutionary dynamics help developing the theory required for a better understanding and interpretation of the numerical results provided by modern automated systems. They can be applied to stress testing in the financial sector, innovation economics, industrial dynamics, and many other fields.

The challenges to be faced by complexity economists are numerous: the socio-economic systems are shaken by the financial crisis, by occasional political and social turmoil, by progressive climate change, unabated poverty, and unresolved social and societal questions. The economic and social implications of new technologies are not as well-understood as it seemed only recently. Consider for example the effects of big data on recent elections combined with the failure of established pre-election polls to provide accurate predictions. Other examples include the economic implications of autonomous vehicles, AI understanding of natural languages, industry 4.0, progressive social centrality of digital social networks, the "death of privacy", and the wide availability of big data in virtually every economic sector. These examples show that the potential applications for complexity economics are numerous and of highest social and political interest.

On the other hand, some non-orthodox branches of economics have long advocated a turn towards complex systems. They anticipated the need to understand the economy as a complex dynamics system and to study it from an interdisciplinary viewpoint if any deeper understanding of the role of institutions, of the evolution of economic structure and of economic development should be gained. Institutional and evolutionary economics has pioneered the use of agent- based modelling, network theory, evolutionary dynamics and complex systems science in economics. They have tackled many of the meta-theoretical questions underlying the application of methods of complexity economics and developed most useful theoretical frameworks into which complexity economics research could be fruitfully embedded. Nevertheless, the connections between the two research camps are still very limited.

This is unfortunate because the continued interdisciplinary exchange between complexity science on the one hand, and institutional and evolutionary economics on the other is of the utmost importance for both sides. This satellite aims at bringing together exceptional scholars from both research communities to advance the complexity approach to economics.

Keywords: institutions, complexity economics, evolutionary economics, agent-based modeling, network formation in economic systems, systemic risk, economic crises

The satellite meeting shall address topics including (but not limited to):

  • The complex systems perspective on economics, institutions, and industry structure,
  • Evolution in economics, e.g. co-evolution of institutions and innovation structures,
  • The role of innovation and new technologies in economics and their co-evolution with institutions,
  • Opinion dynamics and its consequences for the formation of institutions and economic structure,
  • "Fake news", "alternative facts" and their institutional and economic consequences,
  • Structuration processes and network formation mechanisms,
  • Models for innovation networks, trade networks, financial exchange and lending networks,
  • Economic crises and the role of institutions,
  • The application of agent-based modeling and other methods from complexity science to economics, as well as
  • Complex economic systems and complex networks in economics in general.

The satellite thus aims at bringing together scholars from different fields and backgrounds to constructively exchange ideas in the field of complexity economics. We expect the different contributions to be complementary and to encourage continuous collaboration among participants.