The PIs will conduct research on how to analyze data developed in situations of asymmetric information. The goal is to develop new ways to conduct structural estimation of auction models and to extend these methods to the estimation of contract models.
In the first part of the project, they will continue their previous work on econometric methods for the analysis of auction data. In particular, they will develop ways to estimate parameters of the bidder's utility function from data on bidding behavior. The new method will be used to analyze data from US Forest Service Timber auctions. The second part of the project will develop new econometric methods for the estimation of incentive models of regulation. They will develop both fully parametric and nonparametric estimators. These methods will be used to analyze data from public regulatory commissions that regulate French public transit and California water utilities.
Therefore, this research will identify and estimate risk aversion in auctions and will also develop the econometrics of regulation models, while minimizing prior parametric restrictions in each case. The methods will improve the techniques used by industry analysts, regulators, and other public policy makers to analyze data in these markets.
