We consider the problem of allocating multiple units of an indivisible object among agents and collecting payments. Each agent can receive multiple units of the object, and his (consumption) bundle is a pair of the units he receives and his payment. An agent's preference over bundles may be...

A seller is selling multiple objects to a set of agents. Each agent can buy at most one object and his utility over consumption bundles (i.e., (object,transfer) pairs) need not be quasilinear. The seller considers the following desiderata for her mechanism, which she terms desirable: (1)...

We investigate an assignment market in which multiple objects are assigned, together with associated payments, to a group of agents with unit demand preferences. Preferences over bundles, the pairs of (object, payment), accommodate income effects. Among all (Walrasian) equilibria in such a...

We conduct laboratory experiments for the Vickrey auction with and without an announcement on strategy-proofness to subjects. Although the rate of truth-telling among the subjects stays at 20% without the announcement, it increases to 47% with the announcement. Moreover, by conducting...

In multi-object auction models with unitary demand agents, if agents utility functions satisfy quasi-linearity, three auction formats, sealed-bid auction, exact ascending auction, and approximate ascending auction, are known to identify the minimum price equilibrium (MPE), and exhibit elegant...

We study the slot allocation problem where agents have quasi-linear single-peaked preferences over slots and identify the rules satisfying efficiency, strategy-proofness, and individual rationality. Since the quasi-linear single-peaked domain is not connected, the famous characterization of the...

This paper studies a model of mechanism design with transfers where agents' preferences need not be quasilinear. In such a model, (1) we characterize dominant strategy incentive compatible mechanisms using a monotonicity property; (2) we establish a revenue uniqueness result: for every dominant...