Scaling Smart Contracts Via Layer-2 Technologies: Some Empirical Evidence

22 Pages Posted: 6 Feb 2023 Last revised: 12 Apr 2023

See all articles by Lin William Cong

Lin William Cong

Cornell University - Samuel Curtis Johnson Graduate School of Management; National Bureau of Economic Research (NBER)

Xiang Hui

Washington University in St. Louis

Catherine E. Tucker

Massachusetts Institute of Technology (MIT) - Management Science (MS)

Luofeng Zhou

Columbia University

Multiple version iconThere are 2 versions of this paper

Date Written: February 2023

Abstract

Blockchain-based smart contracts can potentially replace certain traditional contracts through decentralized enforcement and reduced transaction costs. However, scalability is a key bottleneck hindering their broader application and adoption, often leading to concentrated or exclusive networks. To avoid falling short of the original promise of the technology, firms actively explore "layer-2" methods for scaling. We provide some initial evidence on the economic implications of a layer-2 scaling solution, which moves information aggregation from on-chain to off-chain peer-to-peer networks. A parallel-system experiment allows clean identification because we observe the same unit in the treatment and control systems at the same time. We find that this scaling solution reduces operating costs by 76%, and importantly, leads to decentralization with lower market concentration and more participation, which in turn improves data accuracy. The findings provide initial evidence of how blockchain and smart contracting technologies evolve towards achieving decentralized and scalable trust.

Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Suggested Citation

Cong, Lin and Hui, Xiang and Tucker, Catherine E. and Zhou, Luofeng, Scaling Smart Contracts Via Layer-2 Technologies: Some Empirical Evidence (February 2023). NBER Working Paper No. w30912, Available at SSRN: https://ssrn.com/abstract=4349545

Lin Cong (Contact Author)

Cornell University - Samuel Curtis Johnson Graduate School of Management ( email )

Ithaca, NY 14853
United States

HOME PAGE: http://www.linwilliamcong.com/

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Xiang Hui

Washington University in St. Louis ( email )

Catherine E. Tucker

Massachusetts Institute of Technology (MIT) - Management Science (MS) ( email )

100 Main St
E62-536
Cambridge, MA 02142
United States

HOME PAGE: http://cetucker.scripts.mit.edu

Luofeng Zhou

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
6
Abstract Views
289
PlumX Metrics