IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v66y2025i3d10.1007_s10614-024-10755-6.html

Is Monopolization Inevitable in Proof-of-Work Blockchains? Insights from Miner Scale Analysis

Author

Listed:
  • Aixing Li

    (University of Chongqing Jiaotong
    University of Chongqing Jiaotong)

  • Ke Gong

    (University of Chongqing Jiaotong)

  • Jiashun Li

    (University of Chongqing Jiaotong)

  • Li Zhang

    (Big Data and Optimization Research Institute, Chongqing Polytechnic University of Electronic Technology)

  • Xueting Luo

    (Qiqihar University)

Abstract

Blockchains use the Proof-of-Work (PoW) consensus mechanism to ensure security. However, if a few large miners increasingly control most of the computing power (hashrate) on the blockchain, the blockchain may become inoperable. To investigate whether this concern materializes, we examine the impact of miners’ revenue (i.e., cryptocurrency price and cryptocurrency output volume) on computing power using dynamic panel analysis, instrumental variables, and various robustness tests on miners’ panel data in the Bitcoin blockchain from 2011 to 2024. We found that cryptocurrency prices and output volumes exert a positive effect on all miners’ computing power, with a notably stronger effect observed among smaller-scale miners. The cryptocurrency price has a more positive impact on small miners, whereas the volume of cryptocurrency output has a more positive impact on large miners. Although the decrease in cryptocurrency output caused by the deflationary cryptocurrency issuance mechanism inhibits miners’ computing power expansion, the scale of large miners is more stable than that of small miners in a fluctuating cryptocurrency market. Therefore, there is a risk of large miners monopolizing the blockchain.

Suggested Citation

  • Aixing Li & Ke Gong & Jiashun Li & Li Zhang & Xueting Luo, 2025. "Is Monopolization Inevitable in Proof-of-Work Blockchains? Insights from Miner Scale Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 66(3), pages 1825-1850, September.
    • Handle: RePEc:kap:compec:v:66:y:2025:i:3:d:10.1007_s10614-024-10755-6
    DOI: 10.1007/s10614-024-10755-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-024-10755-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10614-024-10755-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Luisanna Cocco & Michele Marchesi, 2016. "Modeling and Simulation of the Economics of Mining in the Bitcoin Market," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-31, October.
    2. David Garcia & Claudio Juan Tessone & Pavlin Mavrodiev & Nicolas Perony, 2014. "The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy," Papers 1408.1494, arXiv.org.
    3. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    4. Bill Hu & Joon Ho Hwang & Chinmay Jain & Jim Washam, 2022. "Bitcoin price manipulation: evidence from intraday orders and trades," Applied Economics Letters, Taylor & Francis Journals, vol. 29(2), pages 140-144, January.
    5. Evans, David S, 1987. "The Relationship between Firm Growth, Size, and Age: Estimates for 100 Manufacturing Industries," Journal of Industrial Economics, Wiley Blackwell, vol. 35(4), pages 567-581, June.
    6. Das, Debojyoti & Dutta, Anupam, 2020. "Bitcoin’s energy consumption: Is it the Achilles heel to miner’s revenue?," Economics Letters, Elsevier, vol. 186(C).
    7. Balcilar, Mehmet & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2017. "Can volume predict Bitcoin returns and volatility? A quantiles-based approach," Economic Modelling, Elsevier, vol. 64(C), pages 74-81.
    8. Stephen R. Bond, 2002. "Dynamic panel data models: a guide to micro data methods and practice," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 1(2), pages 141-162, August.
    9. Charles W. Bischoff, 1971. "Business Investment in the 1970s: A Comparison of Models," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, pages 13-64.
    10. Luisanna Cocco & Michele Marchesi, 2016. "Modeling and Simulation of the Economics of Mining in the Bitcoin Market," Papers 1605.01354, arXiv.org.
    11. Nick Arnosti & S. Matthew Weinberg, 2022. "Bitcoin: A Natural Oligopoly," Management Science, INFORMS, vol. 68(7), pages 4755-4771, July.
    12. Lin William Cong & Zhiguo He & Jiasun Li & Wei Jiang, 2021. "Decentralized Mining in Centralized Pools [Concentrating on the fall of the labor share]," The Review of Financial Studies, Society for Financial Studies, vol. 34(3), pages 1191-1235.
    13. Stephen Bond, 2002. "Dynamic panel data models: a guide to microdata methods and practice," CeMMAP working papers 09/02, Institute for Fiscal Studies.
    14. repec:bla:obuest:v:61:y:1999:i:0:p:631-52 is not listed on IDEAS
    15. Dean Fantazzini & Nikita Kolodin, 2020. "Does the Hashrate Affect the Bitcoin Price?," JRFM, MDPI, vol. 13(11), pages 1-29, October.
    16. Easley, David & O'Hara, Maureen & Basu, Soumya, 2019. "From mining to markets: The evolution of bitcoin transaction fees," Journal of Financial Economics, Elsevier, vol. 134(1), pages 91-109.
    17. Stephen Bond, 2002. "Dynamic panel data models: a guide to microdata methods and practice," CeMMAP working papers CWP09/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    18. Gur Huberman & Jacob D Leshno & Ciamac Moallemi, 2021. "Monopoly without a Monopolist: An Economic Analysis of the Bitcoin Payment System [Blockchain Economics]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(6), pages 3011-3040.
    19. Lin William Cong & Zhiguo He, 2019. "Blockchain Disruption and Smart Contracts," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 1754-1797.
    20. John E. Marthinsen & Steven R. Gordon, 2022. "The Price and Cost of Bitcoin," Papers 2204.13102, arXiv.org.
    21. Gang Xue & Jia Xu & Hanwen Wu & Weifeng Lu & Lijie Xu, 2021. "Incentive Mechanism for Rational Miners in Bitcoin Mining Pool," Information Systems Frontiers, Springer, vol. 23(2), pages 317-327, April.
    22. Marthinsen, John E. & Gordon, Steven R., 2022. "The price and cost of bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 280-288.
    23. Aleksey K. Fedorov & Evgeniy O. Kiktenko & Alexander I. Lvovsky, 2018. "Quantum computers put blockchain security at risk," Nature, Nature, vol. 563(7732), pages 465-467, November.
    24. Doms, Mark & Dunne, Timothy & Roberts, Mark J., 1995. "The role of technology use in the survival and growth of manufacturing plants," International Journal of Industrial Organization, Elsevier, vol. 13(4), pages 523-542, December.
    25. Charles W. Bischoff, 1971. "Business Investment in the 1970s: A Comparison of Models," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 2(1), pages 13-63.
    26. G. S. Maddala & Shaowen Wu, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 631-652, November.
    27. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    28. J. Maurice Clark, 1917. "Business Acceleration and the Law of Demand: A Technical Factor in Economic Cycles," Journal of Political Economy, University of Chicago Press, vol. 25(3), pages 217-217.
    29. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    30. Frode Kjærland & Aras Khazal & Erlend A. Krogstad & Frans B. G. Nordstrøm & Are Oust, 2018. "An Analysis of Bitcoin’s Price Dynamics," JRFM, MDPI, vol. 11(4), pages 1-18, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hu, Yang & Lang, Chunlin & Oxley, Les & Hou, Yang (Greg), 2026. "Time-varying Granger causality in Bitcoin mining: Uncovering shifting links to environment, sustainability, and profitability," Research in International Business and Finance, Elsevier, vol. 82(C).

    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. Huy Quang Doan, 2019. "Trade, Institutional Quality and Income: Empirical Evidence for Sub-Saharan Africa," Economies, MDPI, vol. 7(2), pages 1-23, May.
    2. Falavigna, Greta & Ippoliti, Roberto, 2023. "SMEs’ behavior under financial constraints: An empirical investigation on the legal environment and the substitution effect with tax arrears," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    3. Andrew Isaak & Baris Istipliler & Suleika Bort & Michael Woywode, 2025. "Regulation, Corruption, and Decentralized Autonomous Organizations: Insights from Bitcoin Trading and Platform Founding Between 2011 and 2023," Organization Science, INFORMS, vol. 36(6), pages 2210-2244, November.
    4. Gnangnon, Sèna Kimm, 2023. "Duration of membership in the world trade organization and investment-oriented remittances inflows," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 258-277.
    5. Mohamed Mnasri & Georges Dionne & Jean-Pierre Gueyie, 2013. "The Maturity Structure of Corporate Hedging: the Case of the U.S. Oil and Gas Industry," Cahiers de recherche 1337, CIRPEE.
    6. Sèna Kimm Gnangnon, 2023. "Do unilateral trade preferences help reduce poverty in beneficiary countries?," International Journal of Economic Policy Studies, Springer, vol. 17(1), pages 249-288, February.
    7. Nisreen Mousa & Abdallah Nassereddine, 2024. "Manufacturing and Economic Growth in Selected MENA Countries: A Kaldorian Approach," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 30(3), pages 327-341, August.
    8. Armey, Laura E. & McNab, Robert M., 2018. "Expenditure decentralization and natural resources," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 52-61.
    9. Vu, Tam Bang & Noy, Ilan, 2013. "Regional Effects of Natural Disasters in China," Working Paper Series 18776, Victoria University of Wellington, School of Economics and Finance.
    10. Scott, K. Rebecca, "undated". "Demand and price volatility: rational habits in international gasoline demand," CUDARE Working Papers 122891, University of California, Berkeley, Department of Agricultural and Resource Economics.
    11. Athanasoglou, Panayiotis P. & Brissimis, Sophocles N. & Delis, Matthaios D., 2008. "Bank-specific, industry-specific and macroeconomic determinants of bank profitability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(2), pages 121-136, April.
    12. Ismail M. Cole, 2023. "The political economy triangle of government spending, interest‐group influence, and income inequality: Evidence and implications from the US states," Economics and Politics, Wiley Blackwell, vol. 35(3), pages 1122-1176, November.
    13. Guerino Ardizzi & Massimiliano Cologgi, 2025. "Business Models and Pricing Strategies in the Market for ATM Withdrawals," Journal of Financial Services Research, Springer;Western Finance Association, vol. 68(2), pages 283-309, October.
    14. Garbero, Alessandra & Chichaibelu, Bezawit Beyene, 2023. "Estimating resilience outcomes in an impact assessment framework with high-frequency data," 2023 Seventh AAAE/60th AEASA Conference, September 18-21, 2023, Durban, South Africa 365957, African Association of Agricultural Economists (AAAE).
    15. Milos Markovic & Michael A. Stemmer, 2017. "Firm Growth Dynamics and Financial Constraints: Evidence from Serbian Firms," Documents de travail du Centre d'Economie de la Sorbonne 17012, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    16. Juanfeng Zhang & Rui Han & Lele Li & Yi Han, 2025. "The Impact of China’s Land Marketization on Urban Industrial Pollution," SAGE Open, , vol. 15(3), pages 21582440251, July.
    17. Atasoy, Burak Sencer & Özkan, İbrahim & Erden, Lütfi, 2024. "The determinants of systemic risk contagion," Economic Modelling, Elsevier, vol. 130(C).
    18. Olper, Alessandro & Raimondi, Valentina & Cavicchioli, Daniele & Vigani, Mauro, "undated". "Does the Common Agricultural Policy Reduce Farm Labour Migration? Panel data analysis across EU regions," Working papers 128790, Factor Markets, Centre for European Policy Studies.
    19. Yongfu Huang, 2011. "Private investment and financial development in a globalized world," Empirical Economics, Springer, vol. 41(1), pages 43-56, August.
    20. Anwar Al-Gasaymeh & Miral R. Samarah, 2023. "Does Country Risk Affect Banking Efficiency: Empirical Evidence from Turkey and Selected Countries from the European Union," Global Business Review, International Management Institute, vol. 24(6), pages 1401-1417, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:kap:compec:v:66:y:2025:i:3:d:10.1007_s10614-024-10755-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.