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The University of Southampton
Interdisciplinary Research Excellence

A long-term vision for computational economics Event

Time:
16:00
Date:
29 October 2014
Venue:
Nightingale Building (67) room 1003, Highfield Campus. All welcome. Refreshments served after the talk.

For more information regarding this event, please email Brendan Neville at bjn1c13@ecs.soton.ac.uk .

Event details

Part of the Complexity Seminar Series 2014-2015

Abstract: The ability to simulate phenomena is probably the biggest driver of theoretical progress in physical science during the last 50 years.  The same is not true in economics and social science in general.   Why is this so?  I will argue that the time is ripe for this to happen and present a plan for how it could be done and what breakthroughs are required.  I will review the accomplishments of agent-based models in economics so far, discuss the key theoretical and practical challenges for creating the next generation of models, and present key lessons from the CRISIS project (for which I am scientific coordinator).   I will particularly focus on the need for large scale simulation models, analogous to the global circulation models used in meteorology and climate, and discuss the similarities and differences with meteorology.  Finally I will present a vision of what such large scale models might be like and what they would enable us to do ten or twenty years from now.

Speaker information

Doyne Farmer,University of Oxford,Prof J Doyne Farmer co-directs the programme on complexity economics, which is part of the INET Oxford research institute. He has broad interests in complex systems, and has done research in dynamical systems theory, time series analysis and theoretical biology. His main interest is in developing quantitative theories for social evolution, in particular for financial markets (which provide an accurate record of decision making in a complex environment) and the evolution of technologies (whose performance through time provides a quantitative record of one component of progress).

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