CS-ECON Seminar Series
The Value of Information Concealment
||Friday, October 20, 2017
||12:00pm - 1:00pm
||Gross 304B, Duke
||Lunch will be served.
We consider a revenue optimizing seller selling a single item to a buyer, on whose private value the seller has a noisy signal. We show that, when the signal is kept private, arbitrarily more revenue could potentially be extracted than if the signal is leaked or revealed. We then show that, if the seller is not allowed to make payments to the buyer, the gap between the two is bounded by a multiplicative factor of 3 when the value distribution conditioning on each signal is regular. We give examples showing that both conditions are necessary for a constant bound to hold.
We connect this scenario to multi-bidder single-item auctions where bidders'values are correlated. Similarly to the setting above, we show that the revenue of a Bayesian incentive compatible, ex post individually rational auction can be arbitrarily more than that of a dominant strategy incentive compatible auction, whereas the two are no more than a factor of 5 apart if the auctioneer never pays the bidders and if each bidder's value distribution conditioning on the others' is regular. The upper bounds in both settings degrade gracefully when the distribution is a mixture of a small number of regular distributions. This is joint work with Chris Liaw, Pinyan Lu, and Zhihao Gavin Tang.
Hu Fu is an assistant professor in the Department of Computer Science at University of British Columbia. He obtained his PhD in computer science from Cornell University, after which he worked as postdocs at Microsoft Research New England lab and Caltech. His research applies algorithmic methods to economic questions such as mechanism design and revenue maximization.
Hosted by: Vincent Conitzer