Seminar
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| Location: | SLMath: Eisenbud Auditorium, Online/Virtual |
Deterministic Budget-Feasible Clock Auctions
"School Choice with Information Inequality" - Negar Matoorian
Abstract: “School choice policies are predicated on the assumption that parents have enough information to make an informed decision on where to send their children… districts don't always do a good job of disseminating information and explaining options to certain groups – low-income parents and those whose children are first-generation Americans, for example” (US News & World Report, Aug 2015).
We study the consequence of unequal access to school value information in the popular mechanisms for allocation of seats in the public school system. We show that in the Deferred Acceptance mechanism students with inferior information suffer from curse of assignment and might try to mitigate this curse by ranking schools with higher capacity or schools they have priority at prior to schools that are known to have a higher educational quality. Our model lays the ground for studying the welfare consequences of policies such as information disclosure and priority design in school choice environments with asymmetric information.
"Deterministic Budget-Feasible Clock Auctions" - Dan Schoepflin
Abstract: We revisit the well-studied problem of budget-feasible procurement, where a buyer with a strict budget constraint seeks to acquire services from a group of strategic providers (the sellers). During the last decade, several strategyproof budget-feasible procurement auctions have been proposed, aiming to maximize the value of the buyer, while eliciting each seller's true cost for providing their service. Our main result is a novel method for designing budget-feasible auctions, leading to solutions that outperform the previously proposed auctions in multiple ways. First, our solutions take the form of descending clock auctions, rather than sealed-bid auctions, and thus satisfy a list of very appealing properties, such as obvious strategyproofness and unconditional winner privacy, making these auctions much more likely to be used in practice. Second, in contrast to previous results that heavily depend on randomization, our auctions are deterministic. In fact, our deterministic auctions achieve a constant-approximation for submodular valuations, resolving a main open question in this literature. Finally, we improve the best-known approximation factor for monotone submodular valuations, the focus of most of the prior work.
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