Neoclassical economic theory shows that under the right conditions, prices alone can guide markets to efficient outcomes. But what if it it’s hard to find the right price? In many important markets, a buyer’s willingness to pay for one good (say, the right to use a certain part of the radio spectrum range in San Francisco) will depend on the price of another complementary good (the right to use that same spectrum in Los Angeles). The number of possible combinations can rapidly become incalculably complex. Such complex markets require new collaborations between economists and computer scientists to create designs that are both incentive compatible and computationally tractable.
In Discovering Prices: Auction Design in Markets with Complex Constraints (Columbia UP, 2017), 2020 Economics Nobel Memorial Prize winner Paul Milgrom discusses some of the new economics theory he has developed to help address these challenging contexts, in which neither unfettered market forces nor top-down planning will work well. In our interview we explore these ideas in the context of the most complex auction ever created, the FCC’s broadcast incentive auction. This auction, designed and planned by a team led by Professor Milgrom with his company Auctionomics, purchased underutilized broadcast spectrum from television stations and sold it onward to telecoms providers. This reallocation helped improve wireless network performance and pave the way for 5G wireless services, while also generating over $7 billion for the US treasury.
Host Peter Lorentzen is an Associate Professor in the Department of Economics at the University of San Francisco, where he leads a new digital economy-focused Master's program in Applied Economics.
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