Innovation Contests with Entry Auction

We consider procurement of an innovation from heterogeneous sellers. Innovations are random but depend on unobservable effort and private information. We compare two procurement mechanisms where potential sellers first bid in an auction for admission to an innovation contest. After the contest, an innovation is procured employing either a fixed prize or a first-price auction. We characterize Bayesian Nash equilibria such that both mechanisms are payoff-equivalent and induce the same efforts and innovations. In these equilibria, signaling in the entry auction does not occur since contestants play a simple strategy that does not depend on rivals' private information.Contest; Auction; Innovation; Research; R\&D; Procurement; Signaling

Optimal Contracts for Lenient Supervisors

We consider a situation where an agent's effort is monitored by a supervisor who cares for the agent's well being. This is modeled by incorporating the agent's utility into the utility function of the supervisor. The first best solution can be implemented even if the supervisor's preferences are unknown. The corresponding optimal contract is similar to what we observe in practice: The supervisor's wage is constant and independent of his report. It induces one type of supervisor to report the agent's performance truthfully, while all others report favorably independent of performance. This implies that overstated performance (leniency bias) may be the outcome of optimal contracts under informational asymmetries

The efficient provision of public goods through non-distortionary tax contests

We use a simple balanced budget contest to collect taxes on a private good in order to ?nance a pure public good. We show that-with an appropriately chosen structure of winning probabilities-this contest can provide the public good efficiently and without distorting private consumption. We provide extensions to multiple public goods and private taxation sources, asymmetric preferences, and show the mechanism’s robustness across these settings

A dynamic auction for multi-object procurement under a hard budget constraint

We present a new dynamic auction for procurement problems where payments are bounded by a hard budget constraint and money does not enter the procurer's objective function

How to allocate Research (and other) Subsidies

A budget-constrained buyer wants to purchase items from a short-listed set. Items are differentiated by observable quality and sellers have private reserve prices for their items. The buyer’s problem is to select a subset of maximal quality. Money does not enter the buyer’s objective function, but only his constraints. Sellers quote prices strategically, inducing a knapsack game. We derive the Bayesian optimal mechanism for the buyer’s problem. We ?nd that simultaneous take-it-or-leave-it offers are optimal. Hence, somewhat surprisingly, ex-postcompetition is not required to implement optimality. Finally, we discuss the problem in a detail free setting

How to allocate Research (and other) Subsidies

A budget-constrained buyer wants to purchase items from a short-listed set. Items are differentiated by observable quality and sellers have private reserve prices for their items. The buyer’s problem is to select a subset of maximal quality. Money does not enter the buyer’s objective function, but only his constraints. Sellers quote prices strategically, inducing a knapsack game. We derive the Bayesian optimal mechanism for the buyer’s problem. We ?nd that simultaneous take-it-or-leave-it offers are optimal. Hence, somewhat surprisingly, ex-postcompetition is not required to implement optimality. Finally, we discuss the problem in a detail free setting.Mechanism Design; Subsidies; Budget; Procurement; Knapsack Problem

How to allocate Research (and other) Subsidies

A budget-constrained buyer wants to purchase items from a shortlisted set. Items are differentiated by observable quality and sellers have private reserve prices for their items. The buyer’s problem is to select a subset of maximal quality. Money does not enter the buyer’s objective function, but only his constraints. Sellers quote prices strategically, inducing a knapsack game. We derive the Bayesian optimal mechanism for the buyer’s problem. We find that simultaneous takeit-or-leave-it offers are optimal. Hence, somewhat surprisingly, ex-post competition is not required to implement optimality. Finally, we discuss the problem in a detail free setting.Mechanism Design, Subsidies, Budget, Procurement, Knapsack Problem JEL Classification Numbers: D21, D44, D45, D82

License Auctions with Royalty Contracts for (Winners and) Losers

This paper revisits the licensing of a non–drastic process innovation by an outside innovator to a Cournot oligopoly. We propose a new mechanism that combines a restrictive license auction with royalty licensing. This mechanism is more profitable than standard license auctions, auctioning royalty contracts, fixed–fee licensing, pure royalty licensing, and two-part tariffs. The key features are that royalty contracts are auctioned and that losers of the auction are granted the option to sign a royalty contract. Remarkably, combining royalties for winners and losers makes the integer constraint concerning the number of licenses irrelevant