Estimation of Bidder Valuations in an FCC Spectrum Auction

• Main Author: YEO, Jungwon
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2010
• Subjects: Economic Policy; Public Economics
• Online Access: https://ink.library.smu.edu.sg/soe_research/1345; https://ink.library.smu.edu.sg/context/soe_research/article/2344/viewcontent/IIOC2010_526.pdf
• Institution: Singapore Management University

The Federal Communications Commission (FCC) uses auctions to allocate radio spectrum frequencies to wireless service providers. The innovation of the auction design is that it offers many heterogeneous licenses simultaneously in one ascending auction. This paper develops an empirical model and procedure to estimate bidder valuations. Given that the complex nature of the auction does not admit formal modeling in a general setting, I do not explore a particular model of equilibrium bidding. Instead, I propose two revealed preference inequalities which should hold in any reasonable model of these auctions. The first inequality requires that a bidder never bids on a license at a bidding price above the marginal revenue of the license where the marginal revenue is evaluated against the set of licenses the bidder is currently winning. The second inequality is that if a bidder bids on license A, but not on license B, the current marginal surplus from winning license A at the bidding price is greater than that of license B. I employ an estimation strategy that generates a map from the observed bidding behavior to a set of distributions of bidder valuations consistent with these behavioral assumptions. A part of the strategy uses an estimator developed by Pakes, Porter, Ho and Ishii (2006). An advantage of this estimator is that it can accommodate a flexible specification of unobserved heterogeneity. It allows bidder-license specific values to capture private information. I apply the empirical model to an auction held in 2006. Using the estimated distribution of bidder valuations, I estimate bidder markups in order to gauge the level of competition in this auction. The estimated bidder markups are large: the median for local bidders such as rural telephone companies is 26%, whereas it is 31% for global bidders such as nationwide carriers. This suggests that there were large distortionary effects of informational rents in the auction.