Design of the Reverse Auction in the FCC Incentive Auction

We consider important design issues of the reverse auction, a key and innovative part of the FCC’s Incentive Auction. In the reverse auction, broadcasters compete to repurpose television broadcast spectrum for mobile broadband use. The Comment Public Notice (FCC 14-191) outlined the basic structure of the reverse auction. We take that basic structure as given and then examine critical elements of the design to maximize the FCC’s objectives of efficiency, simplicity, transparency, and fairness. Based on extensive simulation analysis of the FCC’s basic design, we identify important enhancements to the design that maintain its basic structure, yet improve the chance of a successful auction. This is accomplished by strengthening incentives for broadcaster participation and relying on competitive forces to determine auction clearing prices. Our analysis is based on a carefully-crafted reservation price model for broadcasters together with inevitable uncertainties of these reservation prices. In our simulations, we are able to clear 126 MHz of spectrum at a cost that is well within plausible revenues from the forward auction. This is accomplished with an improved scoring rule and replacing Dynamic Reserve Prices (DRP) with a much simpler Round Zero Reserve (RZR, pronounced “razor”) to promote objectives of transparency and simplicity. We also propose a much simplified method of setting the clearing target and an information policy that allows for important outcome discovery. Relative to the FCC’s proposal outlined in the Comment PN, our enhanced proposal is more robust, more efficient, simpler, more transparent, and fairer. 1 Peter Cramton is Professor of Economics at the University of Maryland; since 1983, he has conducted widely-cited research on auctioning many related items, and has applied that research to major auctions of radio spectrum, electricity, financial securities, and other products. Hector Lopez is a doctoral candidate at the Economics Department of the University of Maryland, specializing in market design. David Malec is a post-doc at the Economics Department of the University of Maryland; he is a computer scientist specializing in algorithmic game theory. Pat Sujarittanonta is Assistant Professor of Economics at Chulalongkorn University, specializing in market design. The four authors comprise Cramton Associates, a consultancy providing expert advice on auctions and market design. We have benefitted from the extensive help of many U.S. broadcasters. We are grateful to members of the Expanding Opportunities for Broadcasters Coalition (EOBC) for funding this research. The views presented are our own and not necessarily those of EOBC or its members. 1