This paper considers a natural dynamic auction mechanism in the context of private provision of a discrete public good under incomplete information. There are two bidders with private valuations, and the cost of the public good is common knowledge. No bidder is willing to provide the good on his own. I show that a natural application of open ascending auctions in such environments fails dramatically: The probability of provision is zero in any equilibrium. The mechanism effectively auctions off the "right" to be the last one to contribute, but intuition suggests that neither player wishes to be the last one to contribute. Since the player who contributes first has the advantage of being able to free ride on the contribution of the other player, no player wants to win the auction. In the light of this intuition, I consider an alternative mechanism in which the "right" to contribute first is sold in the first stage, and in the second stage players are playing a sequential contribution game with the order determined in the first stage. I show that under weak conditions, this mechanism weakly outperforms the sequential contribution mechanism with exogenous order, in terms of the probability of provision.

I consider a repeated principal-agent model with moral hazard, in which the agent has β-δ-preferences, which are widely used to capture time-inconsistency. I first analyze the case where the agent is sophisticated in the sense that he is fully aware of his inconsistent discounting. I characterize the optimal wage scheme for such an agent and compare it to time-consistent benchmarks. The marginal cost of rewarding the agent for high output today exceeds the marginal benefit of delaying these rewards until tomorrow. In this sense, the principal does not smooth the agent's rewards over time. When facing a sophisticated agent, it is optimal for the principal to reward the good performance more and punish the bad performance more in the early period, relative to the optimal wage scheme for a time-consistent agent. I also consider the case that the agent is naive in the sense that he is not aware of his time-inconsistency. I show that the principal's maximum utility is the same from a sophisticated agent and a naive agent.

This paper analyzes open innovation projects and their effects on incentives for innovation. We model basic features of the General Public License (GPL), one of the most popular open source licenses and study how firms behave under this license. Under the GPL, there is a trade-off between stimulating innovation and promoting disclosure. By using the open source, a firm can increase its technology level and therefore its probability of innovation success and of achieving a greater profit in that period. However, any innovative findings using open source would be also open source in subsequent periods. This obligation decreases the expected future revenue of the firm. We analyze this trade-off and show that if a firm has the same technology level as the open source, it does not use the source. On the other hand, if a firm has a lower level of production technology than the open source, it is optimal to use the source.