Research

This paper studies inference on number of potential bidders in selective entry for first-price sealed-bid auctions. Information of potential bidders set is of great empirical importance in auctions. However, such a set is often constructed by ad hoc methods. I develop a method to test whether these methods are plausible. The test is based on the comparison of bidders' value distributions in two models. The first one is a selective entry model given information of potential bidders. The second one is another selective entry model with the number of potential bidders unknown and random. I apply the methods to procurement auctions from the Californian Department of Transportation (Caltrans). I find that recovered private value distributions fluctuate significantly when different construction methods are employed. I examine the widely used construction method that relies on the time length of a bidder's previous participation. The results show that the time length criterion for Caltrans data should be selected from 120 to 180 days.

This paper studies entry behaviors in procurement auctions with incomplete contracts held by Caltrans. I first provide some reduced-form evidence that contractual incompleteness affects bidders' entry negatively. Motivated by the evidence, I propose a structural model that incorporates both selective entry and contractual incompleteness. I show the model is nonparametrically identified. Applying the model to Caltrans data, I find that, on one hand, expected contractual incompleteness decreases bidders' entry probability. On the other hand, expected holdup from incomplete contracts will cause bidders more likely to enter. From a counterfactual analysis among different models, I show that the estimation of bidders' cost distribution will be biased when neglecting either entry behaviors or incompleteness in procurement auctions.

This paper investigates an important factor of China’s high housing prices: local governmental signaling in land market auctions. We first identify that the winning price of a land auction affects the nearby housing prices positively and such effect could be temporary. We propose a structural model to explain the phenomena. In the model, a local government strategically sends a signal to bidders on possible factors that may increase the value of the auctioned land. The signal affects bidders valuations and the winning prices. Using the model and data on land auctions and housing prices, we structurally estimate the contribution of governmental signaling on high housing prices in China.