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

22 Pages Posted: 4 Jan 2023 Last revised: 30 May 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 - John M. Olin Business School

Catherine E. Tucker

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

Luofeng Zhou

New York University (NYU) - Leonard N. Stern School of Business

Multiple version iconThere are 2 versions of this paper

Date Written: December 23, 2022

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.

Keywords: Blockchain, Information Aggregation, Oracle Networks, Scaling, Smart Contracts

JEL Classification: D20, L86, O33

Suggested Citation

Cong, Lin and Hui, Xiang and Tucker, Catherine E. and Zhou, Luofeng, Scaling Smart Contracts via Layer-2 Technologies: Some Empirical Evidence (December 23, 2022). Available at SSRN: https://ssrn.com/abstract=4312355 or http://dx.doi.org/10.2139/ssrn.4312355

Lin Cong

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 (Contact Author)

Washington University in St. Louis - John M. Olin Business School ( email )

One Brookings Drive
Campus Box 1133
St. Louis, MO 63130-4899
United States

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

New York University (NYU) - Leonard N. Stern School of Business ( email )

44 West 4th Street
Suite 9-160
New York, NY NY 10012
United States

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