IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/24399.html
   My bibliography  Save this paper

Blockchain Disruption and Smart Contracts

Author

Listed:
  • Lin William Cong
  • Zhiguo He

Abstract

Blockchain technology provides decentralized consensus and potentially enlarges the contracting space using smart contracts with tamper-proofness and algorithmic executions. Meanwhile, generating decentralized consensus entails distributing information which necessarily alters the informational environment. We analyze how decentralization affects consensus effectiveness, and how the quintessential features of blockchain reshape industrial organization and the landscape of competition. Smart contracts can mitigate informational asymmetry and improve welfare and consumer surplus through enhanced entry and competition, yet the irreducible distribution of information during consensus generation may encourage greater collusion. In general, blockchains can sustain market equilibria with a wider range of economic outcomes. We further discuss anti-trust policy implications targeted to blockchain applications, such as separating consensus record-keepers from users.

Suggested Citation

  • Lin William Cong & Zhiguo He, 2018. "Blockchain Disruption and Smart Contracts," NBER Working Papers 24399, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:24399
    Note: AP CF IO LE
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w24399.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Thomas Philippon, 2015. "Has the US Finance Industry Become Less Efficient? On the Theory and Measurement of Financial Intermediation," American Economic Review, American Economic Association, vol. 105(4), pages 1408-1438, April.
    2. Athey, Susan & Bagwell, Kyle, 2001. "Optimal Collusion with Private Information," RAND Journal of Economics, The RAND Corporation, vol. 32(3), pages 428-465, Autumn.
    3. Innes, Robert D., 1990. "Limited liability and incentive contracting with ex-ante action choices," Journal of Economic Theory, Elsevier, vol. 52(1), pages 45-67, October.
    4. Drew Fudenberg & Eric Maskin, 2008. "The Folk Theorem In Repeated Games With Discounting Or With Incomplete Information," World Scientific Book Chapters, in: Drew Fudenberg & David K Levine (ed.), A Long-Run Collaboration On Long-Run Games, chapter 11, pages 209-230, World Scientific Publishing Co. Pte. Ltd..
    5. Johannes Hörner & Wojciech Olszewski, 2006. "The Folk Theorem for Games with Private Almost-Perfect Monitoring," Econometrica, Econometric Society, vol. 74(6), pages 1499-1544, November.
    6. Peter M. DeMarzo & Ilan Kremer & Andrzej Skrzypacz, 2005. "Bidding with Securities: Auctions and Security Design," American Economic Review, American Economic Association, vol. 95(4), pages 936-959, September.
    7. Mailath, George J. & Morris, Stephen, 2002. "Repeated Games with Almost-Public Monitoring," Journal of Economic Theory, Elsevier, vol. 102(1), pages 189-228, January.
    8. repec:zbw:bofrdp:2017_027 is not listed on IDEAS
    9. Jean Tirole, 1988. "The Theory of Industrial Organization," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262200716, December.
    10. Peter DeMarzo & Darrell Duffie, 1999. "A Liquidity-Based Model of Security Design," Econometrica, Econometric Society, vol. 67(1), pages 65-100, January.
    11. Bruno Biais & Christophe Bisière & Matthieu Bouvard & Catherine Casamatta, 2019. "The Blockchain Folk Theorem," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 1662-1715.
    12. David A. Miller, 2012. "Robust Collusion with Private Information," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(2), pages 778-811.
    13. Green, Edward J & Porter, Robert H, 1984. "Noncooperative Collusion under Imperfect Price Information," Econometrica, Econometric Society, vol. 52(1), pages 87-100, January.
    14. David Yermack, 2017. "Corporate Governance and Blockchains," Review of Finance, European Finance Association, vol. 21(1), pages 7-31.
    15. Abreu, Dilip & Pearce, David & Stacchetti, Ennio, 1986. "Optimal cartel equilibria with imperfect monitoring," Journal of Economic Theory, Elsevier, vol. 39(1), pages 251-269, June.
    16. Hart, Oliver D & Moore, John, 1988. "Incomplete Contracts and Renegotiation," Econometrica, Econometric Society, vol. 56(4), pages 755-785, July.
    17. Hendrik Bessembinder & William Maxwell, 2008. "Markets: Transparency and the Corporate Bond Market," Journal of Economic Perspectives, American Economic Association, vol. 22(2), pages 217-234, Spring.
    18. Huberman, Gur & Leshno, Jacob & Moallemi, Ciamac C., 2017. "Monopoly Without a Monopolist: An Economic Analysis of the Bitcoin Payment System," CEPR Discussion Papers 12322, C.E.P.R. Discussion Papers.
    19. Christian Catalini & Joshua S. Gans, 2016. "Some Simple Economics of the Blockchain," NBER Working Papers 22952, National Bureau of Economic Research, Inc.
    20. Rainer Böhme & Nicolas Christin & Benjamin Edelman & Tyler Moore, 2015. "Bitcoin: Economics, Technology, and Governance," Journal of Economic Perspectives, American Economic Association, vol. 29(2), pages 213-238, Spring.
    21. Bloomfield, Robert & O'Hara, Maureen, 1999. "Market Transparency: Who Wins and Who Loses?," The Review of Financial Studies, Society for Financial Studies, vol. 12(1), pages 5-35.
    22. Porter, Robert H., 1983. "Optimal cartel trigger price strategies," Journal of Economic Theory, Elsevier, vol. 29(2), pages 313-338, April.
    23. Max Raskin & David Yermack, 2016. "Digital Currencies, Decentralized Ledgers, and the Future of Central Banking," NBER Working Papers 22238, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kaplow, Louis & Shapiro, Carl, 2007. "Antitrust," Handbook of Law and Economics, in: A. Mitchell Polinsky & Steven Shavell (ed.), Handbook of Law and Economics, edition 1, volume 2, chapter 15, pages 1073-1225, Elsevier.
    2. Mouraviev, Igor, 2006. "Private Observation, Tacit Collusion and Collusion with Communication," Working Paper Series 672, Research Institute of Industrial Economics.
    3. Susan Athey & Kyle Bagwell & Chris Sanchirico, 2004. "Collusion and Price Rigidity," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 71(2), pages 317-349.
    4. Margaret C. Levenstein & Valerie Y. Suslow, 2011. "Breaking Up Is Hard to Do: Determinants of Cartel Duration," Journal of Law and Economics, University of Chicago Press, vol. 54(2), pages 455-492.
    5. Panayiotis Agisilaou, 2013. "Collusion in Industrial Economics and Optimally Designed Leniency Programmes - A Survey," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2013-03, Centre for Competition Policy, University of East Anglia, Norwich, UK..
    6. Joseph E. Harrington, Jr, 2005. "Detecting Cartels," Economics Working Paper Archive 526, The Johns Hopkins University,Department of Economics.
    7. Luke Garrod & Matthew Olczak, 2017. "Collusion Under Imperfect Monitoring with Asymmetric Firms," Journal of Industrial Economics, Wiley Blackwell, vol. 65(3), pages 654-682, September.
    8. Labrecciosa Paola & Colombo Luca, 2010. "Technology Uncertainty and Market Collusion," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 10(1), pages 1-17, March.
    9. Wilson, Alistair J. & Wu, Hong, 2017. "At-will relationships: How an option to walk away affects cooperation and efficiency," Games and Economic Behavior, Elsevier, vol. 102(C), pages 487-507.
    10. Joseph E. Harrington Jr. & Andrzej Skrzypacz, 2007. "Collusion under monitoring of sales," RAND Journal of Economics, RAND Corporation, vol. 38(2), pages 314-331, June.
    11. Garrod, Luke & Olczak, Matthew, 2018. "Explicit vs tacit collusion: The effects of firm numbers and asymmetries," International Journal of Industrial Organization, Elsevier, vol. 56(C), pages 1-25.
    12. van Damme, Eric, 1989. "Renegotiation-proof equilibria in repeated prisoners' dilemma," Journal of Economic Theory, Elsevier, vol. 47(1), pages 206-217, February.
    13. Mailath, George J. & Olszewski, Wojciech, 2011. "Folk theorems with bounded recall under (almost) perfect monitoring," Games and Economic Behavior, Elsevier, vol. 71(1), pages 174-192, January.
    14. Escobar, Juan F. & Llanes, Gastón, 2018. "Cooperation dynamics in repeated games of adverse selection," Journal of Economic Theory, Elsevier, vol. 176(C), pages 408-443.
    15. Andrew Detzel & Hong Liu & Jack Strauss & Guofu Zhou & Yingzi Zhu, 2021. "Learning and predictability via technical analysis: Evidence from bitcoin and stocks with hard‐to‐value fundamentals," Financial Management, Financial Management Association International, vol. 50(1), pages 107-137, March.
    16. Osório-Costa, António M., 2009. "Efficiency Gains in Repeated Games at Random Moments in Time," MPRA Paper 13105, University Library of Munich, Germany.
    17. Etienne Billette de Villemeur & Laurent Flochel & Bruno Versaevel, 2013. "Optimal collusion with limited liability," International Journal of Economic Theory, The International Society for Economic Theory, vol. 9(3), pages 203-227, September.
    18. Jean J. Gabszewicz & Jacques-François Thisse, 2000. "Microeconomic theories of imperfect competition," Cahiers d'Économie Politique, Programme National Persée, vol. 37(1), pages 47-99.
    19. Yuliy Sannikov & Andrzej Skrzypacz, 2007. "Impossibility of Collusion under Imperfect Monitoring with Flexible Production," American Economic Review, American Economic Association, vol. 97(5), pages 1794-1823, December.
    20. Anil Savio Kavuri & Alistair Milne, 2019. "FinTech and the future of financial services: What are the research gaps?," CAMA Working Papers 2019-18, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    More about this item

    JEL classification:

    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • G2 - Financial Economics - - Financial Institutions and Services
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L4 - Industrial Organization - - Antitrust Issues and Policies
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:24399. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.