Fernando Vega-Redondo

Born in León (Spain), January 1957
Married to Mirèia Carol i Gres
Four children: Manuel, Ferrán, Diego, Olalla

Research Interests: Game Theory, Evolutionary Theory, Learning and bounded rationality, Social networks

Degrees

• Licenciado en Económicas, Universidad Complutense de Madrid, June 1980.
• Doctor of Philosophy, University of Minnesota, August 1984. Thesis supervisor: Professor Leonid Hurwicz.

Teaching and research positions

• Teaching Assistant, University of Minnesota, 1982-84.
• Assistant Professor, Universidad de Alicante, 1984-85.
• Research Fellow, Instituto de Análisis Económico, C.S.I.C, Barcelona, 1986-90.
• Visiting Scholar, Harvard University, 1987-88.
• Research Fellow, Institute for Advanced Studies, Hebrew University of Jerusalem, 1989-90.
• Research Fellow, Institute for Advanced Studies, Vienna, 1993.
• Visiting Scholar, University of California-San Diego, 1995.
• Visiting Scholar, Boston University, 1996.
• Visiting Professor, Cornell University, 2006-7.
• Professor, Universidad de Alicante, since 1990 (currently on leave).
• Professor, University of Essex, 2004-13.
• Professor, European University Institute (Florence), 2007-2013
• Professor, Università Bocconi, since September 2013

Editorial activities

• Editorial board, Lecture Notes in Economics and Mathematical Systems: 2002-4
• Co-editor, Spanish Economic Review: 2001-5
• Associate editor, International Journal of Game Theory: 2007-
• Associate editor, Games and Economic Behavior: 2010-
• Guest editor, Proceedings of the National Academy of Sciences of USA, 2012
• Associate editor, Network Science, 2012-
• Associate editor, Journal of Complex Networks, 2012-
• Guest editor, Operations Research, 2014
• Co-editor, Network Science: 2014-

Professional recognition

• Honorary Fellow of the Spanish Economic Association 2009-
• Fellow of the Society for the Advance of Economic Theory, 2011.
• Fellow of the Game Theory Society, 2017-
• Member of the Council, Game Theory Society, 2011-2017.
• Member of the Council, Society for Economic Science with Heterogenous Interacting Agents, 2011-
• FUE prize for research in economics, 2011.

Research:

My research has largely focused on the theory of games and its economic applications, with a special emphasis on issues of bounded rationality, learning, and evolution. Much of my recent work is devoted to understanding the interplay between individual behavior and the evolution of social networks in large and complex environments. Methodologically, I strive to develop a theory that is suitable to study the large-scale data that is becoming widely available in some social environments.

More specifically, my current work primarily focuses on the following three lines of research:

Production and financial networks: The intricate interaction of the production and financial connections characterizing modern economies can be fruitfully modeled as a complex multilevel network. In this context, I am particularly interested on how real and financial shocks propagate, what is the direct and indirect impact casued by various distortions (e.g. market power), and the features of an economy that make it more or less robust and resilient to shock propagation. The recent availability of highly granular data on the real and the financial sides of some national economies allows for structural testing of the theory and its use as a tool to inform economic policy.

Collaborators: Kenan Huremovic, Gabriel Jiménez, Enrique Moral-Benito, and Jose-Luis Peydró.

Peer networks and innovation: Peer networks are a key channel of information, feedback, and motivation among innovators and entrepreneurs. Understanding better how they operate in the modern hyper-connected world is important to promote innovation and economic development. Starting from a large-scale field experiment conducted in Africa (49 countries and 5,000 entrepreneurs) in both Europe and Africa, we are striving to develop a theory that is consistent with the data and insights obtained from the experiment, then aiming to rely on it to guide the design and implementation of incentive-compatible mechanisms that can exploit the substantial potential for innovation that is achievable through large-scale peer networks in social environments.

Collaborators: Paolo Pin, Diego Ubfal, Cristiana Benedetti, Charles Brummitt, Gaia Rubera, Dirk Hovy, and Tommaso Fornaciari.

Social networks, learning, and collective action: People learn from their connections/friends in various social networks and also aim to coordinate behavior with them. This is particularly evident when some sort of collective action arises in contexts (e.g. riots) where information is crucial and certain individual choices (say, protest) are acutely risky if mis-coordinated with those of others. How does collective behavior unfold under these circumstances in very large populations? What are the factors that make it possible, or the conditions that render it essentially impossible. We currently developing a theory that can suitably account for the main forces at work, bringing it to the analysis of large-scale data on social protests – e.g. those that gave rise to the so-called Arab Spring and its ensuing ``winter."

Collaborators: Lachlan Deer, Chih-Sheng Hsieh, and Michael König.