We consider 2-bidder first-price auctions where one bidder's value is commonly known. Such auctions induce an ineffcient allocation. We show that a resale opportunity, where the auction winner can make a take-it-or-leave-it offer to the loser, increases (reduces) the ineffciency of the market...

This paper derives necessary and sucient conditions for the existence of linear equilibria in the Rochet-Vila model of market making. In contrast to most previous work on the existence of linear equilibria in models of market making, we do not impose independence of the underlying random...

In standard auctions with symmetric, independent private value bidders resale creates a role for a speculator - a bidder who is commonly known to have no use value for the good on sale. For second-price and English auctions the efficient value-bidding equilibrium coexists with a continuum of...

We consider the problem of mechanism design by a principal who has private information. We point out a simple condition under which the privacy of the principal's information is irrelevant in the sense that the mechanism implemented by the principal coincides with the mechanism that would be...

The English auction is susceptible to tacit collusion when post-auction inter-bidder resale is allowed. We show this by constructing equilibria where, with positive probability, one bidder wins the auction without any competition and divides the spoils by optimally reselling the good to the...

We consider Kyle's market order model of insider trading with multiple informed traders and show: if a linear equilibrium exists for two different numbers of informed traders, asset payoff and noise trading are independent and have finite second moments, then these random variables are normally...

We consider the simultaneous linear minimax estimation problem in linear models with ellipsoidal constraints imposed on the unknown parameter. Using convex analysis we derive necessary and sufficient optimality conditions for a matrix to define the best linear minimax estimator. For certain...