We consider a resource allocation problem with two types of goods: a plentiful good that all agents have approximately the same value for, and a scarce good that agents value differently (imagine, e.g., job requests on an ordinary computing cluster versus a restricted high-performance cluster). A social planner seeks to allocate the scarce resource to the agent who values it most. We depart from the usual mechanism design approach by assuming monetary payments are infeasible, and instead use lotteries and the threat of non-allocation to elicit truthful value reporting. Adapting ideas developed in the context of revenue redistribution, we address whether there exist allocation rules yielding expected welfare that -- in ex post equilibrium -- exceeds that of a baseline that randomly assigns the scarce resource.
Dr Cavallo is a research scientist at Yahoo, New York. He got his PhD from Harvard University and BA from Cornell University. He was previously a Yahoo postdoc (in a group led by Preston McAfee), and in the interim between Yahoo jobs, he was a founding member of the Microsoft Research lab in NYC. More information can be found in his website: http://www.eecs.harvard.edu/~cavallo/