A Computational and Experimental Examination of the FCC Incentive Auction

<p>In 2016, the Federal Communications Commission debuted a new auction mechanism, the Incentive Auction, with the intention of obtaining high frequency television broadcasting spectrum, repurposing it for cellular use, and reselling these licenses at profitable prices. In designing this process, the traditional mechanism used for spectrum auctions, the Simulta- neous Multiple Round Auction (SMR), was modified in order to speed the process. This new mechanism, the Incentive Forward Auction (IFA), intended to reduce the number of rounds per auction by lumping similar spectrum licenses together. However, the IFA discourages straightforward bidding strategies and can result in bidders committing more in costs than their established budgets will allow.</p> <p>These mechanisms are compared using two methods: a simulated environment using automated bidding strategies, and a lab environment using human subjects. In simulations, it was found that the IFA was successful in reducing the number of rounds per auction compared with the SMR. However, both simulation and experimental results found that using the IFA resulted in consistent losses to auction efficiency and revenue.</p>

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computational and Data Sciences

Year

2020

Author dc:creator

• Gantner, Logan

Contributors dc:contributor

• David Porter
• Abel Winn
• Stephen Rassenti

• Experimental economics
• FCC
• auctions
• allocation
• optimization
• linear programming
• Behavioral Economics

Repository record dc:identifier

https://digitalcommons.chapman.edu/cads_dissertations/6

OAI identifier oai:identifier

oai:digitalcommons.chapman.edu:cads_dissertations-1006