An empirical take on computation in economics

March 16, 2011

ABSTRACT:
Recent results in complexity theory suggest that various economic
theories require agents to solve intractable problems. However, such
results assume the agents are optimizing explicit utility functions,
whereas the economic theories merely assume the agentsâ€™ behavior is
"rational" where rational behavior is defined via some optimization
problem (e.g., constrained maximization of some utility function).
Might merely generating rational behavior be computationally easier
than solving the corresponding optimization problem? Perhaps
surprisingly, we show that this is indeed the case for what is perhaps
the most basic economic theory, the theory of the consumer. Our
results suggest a new approach to understanding the proper role of
computational constraints in economics which complements previous
work, and is more in keeping with traditional economic thought.

Joint work with Federico Echenique and Adam Wierman.

Bio:

Daniel Golovin is a postdoctoral fellow in Caltech's Center for the Mathematics of Information. His current research mainly focuses on online and approximation algorithms for machine learning and optimization, with an eye towards creating principled solutions that work well in practice. Prior to joining Caltech, he obtained a PhD from Carnegie Mellon University in 2008, and spent an additional year there at the Center for Computational Thinking. He did his undergraduate work at Cornell University.

Joint work with Federico Echenique and Adam Wierman.

Bio:

Daniel Golovin is a postdoctoral fellow in Caltech's Center for the Mathematics of Information. His current research mainly focuses on online and approximation algorithms for machine learning and optimization, with an eye towards creating principled solutions that work well in practice. Prior to joining Caltech, he obtained a PhD from Carnegie Mellon University in 2008, and spent an additional year there at the Center for Computational Thinking. He did his undergraduate work at Cornell University.