The Method of Approximation (from Algorithms to Economics)

Jason HartlineAssociate ProfessorNorthwestern University

Phenomena of study in many fields can be viewed as a
processes that operate on inputs and produce outputs. In this talk I
will describe a method of approximation, adapted from the analysis of
algorithms, for understanding these computations. I will survey the
application of this method to economic systems and, in particular,
auctions. In auctions, the input is the bidders' values for the
object for sale, and the output is obtained by composing the
computation of bidders' strategies with the computation of the rules
of the auction. Precise analysis generally fails; I will describe (a)
the method of approximation, (b) how to apply it, and (c) how to
interpret its conclusions. I will use the method to inform the design
of good auctions and to understand the importance of complex
phenomena such as collusion, decentralization, and discrimination.
No prior knowledge of algorithms, economics, or auctions is assumed.
Prof. Hartline's research introduces design and analysis
methodologies from computer science to understand and improve outcomes
of economic systems. This approach is applied to auction theory in
his graduate textbook Mechanism Design and Approximation
( which is under preparation.

Prof. Hartline received his Ph.D. in 2003 from the University of
Washington under the supervision of Anna Karlin. He was a
postdoctoral fellow at Carnegie Mellon University under the
supervision of Avrim Blum; and subsequently a researcher at Microsoft
Research in Silicon Valley. He joined Northwestern University in 2008
where he is an associate professor of computer science. He is
currently on sabbatical visiting Harvard University's Economics

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