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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
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    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. 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.
    5. John E. Marthinsen & Steven R. Gordon, 2022. "The Price and Cost of Bitcoin," Papers 2204.13102, arXiv.org.
    6. 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.
    7. 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.
    8. 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.
    9. Dean Fantazzini & Nikita Kolodin, 2020. "Does the Hashrate Affect the Bitcoin Price?," JRFM, MDPI, vol. 13(11), pages 1-29, October.
    10. Das, Debojyoti & Dutta, Anupam, 2020. "Bitcoin’s energy consumption: Is it the Achilles heel to miner’s revenue?," Economics Letters, Elsevier, vol. 186(C).
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Luisanna Cocco & Michele Marchesi, 2016. "Modeling and Simulation of the Economics of Mining in the Bitcoin Market," Papers 1605.01354, arXiv.org.
    18. Nick Arnosti & S. Matthew Weinberg, 2022. "Bitcoin: A Natural Oligopoly," Management Science, INFORMS, vol. 68(7), pages 4755-4771, July.
    19. 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.
    20. Stephen Bond, 2002. "Dynamic panel data models: a guide to microdata methods and practice," CeMMAP working papers 09/02, Institute for Fiscal Studies.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. repec:bla:obuest:v:61:y:1999:i:0:p:631-52 is not listed on IDEAS
    27. 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.
    28. 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.
    29. 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.
    30. 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.
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