IDEAS home Printed from https://ideas.repec.org/p/bca/bocawp/22-2.html
   My bibliography  Save this paper

What Drives Bitcoin Fees? Using Segwit to Assess Bitcoin's Long-Run Sustainability

Author

Listed:
  • Colin Brown
  • Jonathan Chiu
  • Thorsten Koeppl

Abstract

Can Bitcoin remain tamper proof in the long run? We use block-level data from the Bitcoin blockchain to estimate the impact of congestion and the USD price on fee rates. The introduction and adoption of the Segwit protocol allows us to identify an aggregate demand curve for bitcoin transactions. We find that Segwit has reduced fee revenue by about 70%. Fee revenue could be maximized at a block size of about 0.6 MB when Segwit adoption remains at current levels. At this block size, maximum fee revenue would be equivalent to 1/8 of the current average block reward. Hence, large sustained price increases are required to keep mining rewards constant in the long run.

Suggested Citation

  • Colin Brown & Jonathan Chiu & Thorsten Koeppl, 2022. "What Drives Bitcoin Fees? Using Segwit to Assess Bitcoin's Long-Run Sustainability," Staff Working Papers 22-2, Bank of Canada.
  • Handle: RePEc:bca:bocawp:22-2
    as

    Download full text from publisher

    File URL: https://www.bankofcanada.ca/wp-content/uploads/2022/01/swp2022-2.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    2. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    3. 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.
    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. Matteo Mogliani, 2010. "Residual-based tests for cointegration and multiple deterministic structural breaks: A Monte Carlo study," Working Papers halshs-00564897, HAL.
    2. Stephen G Cecchetti & Alfonso Flores-Lagunes & Stefan Krause, 2005. "Assessing the Sources of Changes in the Volatility of Real Growth," RBA Annual Conference Volume (Discontinued), in: Christopher Kent & David Norman (ed.),The Changing Nature of the Business Cycle, Reserve Bank of Australia.
    3. Pierre Perron & Yohei Yamamoto, 2022. "Structural change tests under heteroskedasticity: Joint estimation versus two‐steps methods," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 389-411, May.
    4. Ibrahim Ahamada & Jamel Jouini & Mohamed Boutahar, 2004. "Detecting multiple breaks in time series covariance structure: a non-parametric approach based on the evolutionary spectral density," Applied Economics, Taylor & Francis Journals, vol. 36(10), pages 1095-1101.
    5. Kim, Dukpa & Oka, Tatsushi & Estrada, Francisco & Perron, Pierre, 2020. "Inference related to common breaks in a multivariate system with joined segmented trends with applications to global and hemispheric temperatures," Journal of Econometrics, Elsevier, vol. 214(1), pages 130-152.
    6. Gadea, Maria Dolores & Sabate, Marcela & Serrano, Jose Maria, 2004. "Structural breaks and their trace in the memory: Inflation rate series in the long-run," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(2), pages 117-134, April.
    7. Mohitosh Kejriwal & Pierre Perron, 2010. "A sequential procedure to determine the number of breaks in trend with an integrated or stationary noise component," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(5), pages 305-328, September.
    8. Tortorice, Daniel L., 2014. "Credit Constraints, Learning, And Aggregate Consumption Volatility," Macroeconomic Dynamics, Cambridge University Press, vol. 18(2), pages 338-368, March.
    9. Jesús Clemente & María Dolores Gadea & Antonio Montañés & Marcelo Reyes, 2017. "Structural Breaks, Inflation and Interest Rates: Evidence from the G7 Countries," Econometrics, MDPI, vol. 5(1), pages 1-17, February.
    10. Chen Fuqi & Nkurunziza Sévérien, 2014. "Constrained inference in multiple regression with structural changes," Statistics & Risk Modeling, De Gruyter, vol. 31(3-4), pages 1-21, December.
    11. Zeileis, Achim, 2004. "Econometric Computing with HC and HAC Covariance Matrix Estimators," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 11(i10).
    12. , & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," CEPR Discussion Papers 16357, C.E.P.R. Discussion Papers.
    13. Perron, Pierre, 2020. "L'estimation de modèles avec changements structurels multiples," L'Actualité Economique, Société Canadienne de Science Economique, vol. 96(4), pages 789-837, Décembre.
    14. Seong Yeon Chang & Pierre Perron, 2016. "Inference on a Structural Break in Trend with Fractionally Integrated Errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(4), pages 555-574, July.
    15. Oka, Tatsushi & Perron, Pierre, 2018. "Testing for common breaks in a multiple equations system," Journal of Econometrics, Elsevier, vol. 204(1), pages 66-85.
    16. Hui Hong & Zhicun Bian & Chien-Chiang Lee, 2021. "COVID-19 and instability of stock market performance: evidence from the U.S," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-18, December.
    17. González-Álvarez, María A. & Montañés, Antonio, 2023. "CO2 emissions, energy consumption, and economic growth: Determining the stability of the 3E relationship," Economic Modelling, Elsevier, vol. 121(C).
    18. Kejriwal, Mohitosh & Perron, Pierre, 2010. "Testing for Multiple Structural Changes in Cointegrated Regression Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(4), pages 503-522.
    19. Pierre Perron & Yohei Yamamoto, 2016. "On the Usefulness or Lack Thereof of Optimality Criteria for Structural Change Tests," Econometric Reviews, Taylor & Francis Journals, vol. 35(5), pages 782-844, May.
    20. Erasmo Papagni & Amedeo Lepore & Emanuele Felice & Anna Laura Baraldi & Maria Rosaria Alfano, 2018. "Public Investment and Growth Accelerations: The Case of Southern Italy, 1951-1995," EERI Research Paper Series EERI RP 2018/10, Economics and Econometrics Research Institute (EERI), Brussels.

    More about this item

    Keywords

    Digital currencies and fintech; Payment clearing and settlement systems;

    JEL classification:

    • E42 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Monetary Sytsems; Standards; Regimes; Government and the Monetary System
    • G2 - Financial Economics - - Financial Institutions and Services

    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:bca:bocawp:22-2. 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/bocgvca.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.