Assistant Professor of Economics at Tepper School of Business, Carnegie Mellon University
This talk explains biding dynamics where values and bidding opportunities follow an unrestricted joint Markov process, independent across age.. Bids cannot be retracted, as is frequently the case in auctions. Our main methodological contribution is that we construct a mapping from this general stochastic process into a distribution of values that is independent of the type of auction considered. The equilibria of a static auction with this distribution of values is used to characterize the equilibria of the dynamic auction, making this general class very tractable. Asa result of the option of future rebidding, early bids are shaded and under mild conditions increase toward the end of the auction. Our results are consistent with repeated bidding and skewness of the time distribution of winning bids, two puzzling observations in dynamic auctions. As an application, we estimate the model by matching moments from eBay auctions.
She was an Assistant Professor Of Economics at The Ohio State University before joining CMU. Professor Saeedi conducts research in the fields of Industrial Organization, Applied Microeconomics, and Game Theory. In her research, she focused on online platforms and eBay in particular. She studies various aspects of online markets, such as the value of reputation, the effects of implementing additional regulations on reputation, the effects of changes to the reputation mechanism, and dynamic eBay auctions. In other recent project, she studies the effect of an increase in price transparency in health care market, in particular, on patient choice, hospital prices, and possible facilitation of collusion among hospitals. Professor Saeedi received a B.S. in Mechanical Engineering from Sharif University of Technology in Tehran, Iran, an M.A. in Economics from University of British Columbia In Vancouver, and Ph.D. in Economim from University of Minnesota.