StableFees: A Predictable Fee Market for Cryptocurrencies

Soumya Basu (), David Easley, Maureen O’Hara () and Emin Gün Sirer ()
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Soumya Basu: Department of Computer Science, Cornell University, Ithaca, New York 14850
Maureen O’Hara: College of Business, Cornell University, Ithaca, New York 14850
Emin Gün Sirer: Ava Labs, New York, New York 10036

Management Science, 2023, vol. 69, issue 11, 6508-6524

Abstract: Blockchain-based cryptocurrencies must solve the problem of assigning priorities to competing transactions. The most widely used mechanism involves each transaction offering a fee to be paid once the transaction is processed, but this discriminatory price mechanism fails to yield stable equilibria with predictable prices. We propose an alternate fee setting mechanism, StableFees, that is based on uniform price auctions. We prove that our proposed protocol is free from manipulation by users and miners as the number of users and miners increases and show empirically that gains from manipulation are small in practice. We show that StableFees reduces the fees paid by users and reduces the variance of fee income to miners. Data from December 2017 show that, if implemented, StableFees could have saved Bitcoin users $272,528,000 USD in transaction fees while reducing the variance of miner’s fee income, on average, by a factor of 7.4. We argue that our fee protocol also has important social welfare and environmental benefits.

Keywords: cryptocurrency; blockchain; transaction fees (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:69:y:2023:i:11:p:6508-6524

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