The Method of Approximation (from Algorithms to Economics) - DLS Talk by Jason Hartline, Northwestern University

Speaker:  Jason Hartline, Associate Professor, Northwestern EECS

Title:  The Method of Approximation (from Algorithms to Economics)

Host: Kevin Leyton-Brown, UBC Computer Science

Abstract: 

Phenomena of study in many fields can be viewed as 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.

Bio:

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 (http://jasonhartline.com/MDnA/) 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 Department.