IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-03888337.html
   My bibliography  Save this paper

Demand elasticities of Bitcoin and Ethereum

Author

Listed:
  • Akanksha Jalan

    (ESC Rennes School of Business - ESC [Rennes] - ESC Rennes School of Business)

  • Roman Matkovskyy

    (ESC Rennes School of Business - ESC [Rennes] - ESC Rennes School of Business)

  • Andrew Urquhart

    (Henley Business School [University of Reading] - UOR - University of Reading)

Abstract

In this paper we analyze dynamic demand elasticity for Bitcoin and Ethereum in terms of price, transaction fees, and energy usage. We find that while both BTC and ETH have significantly positive price elasticities, transaction fee elasticity is negative and positive for BTC and ETH respectively, indicating differences in potential uses for these cryptocurrencies.

Suggested Citation

  • Akanksha Jalan & Roman Matkovskyy & Andrew Urquhart, 2022. "Demand elasticities of Bitcoin and Ethereum," Post-Print hal-03888337, HAL.
    • Handle: RePEc:hal:journl:hal-03888337
    DOI: 10.1016/j.econlet.2022.110877
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Helmut Lütkepohl & Fang Xu, 2012. "The role of the log transformation in forecasting economic variables," Empirical Economics, Springer, vol. 42(3), pages 619-638, June.
    2. Joshua D. Angrist & Òscar Jordà & Guido M. Kuersteiner, 2018. "Semiparametric Estimates of Monetary Policy Effects: String Theory Revisited," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(3), pages 371-387, July.
    3. Yarovaya, Larisa & Matkovskyy, Roman & Jalan, Akanksha, 2021. "The effects of a “black swan” event (COVID-19) on herding behavior in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    4. Newey, Whitney K & West, Kenneth D, 1987. "Hypothesis Testing with Efficient Method of Moments Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 777-787, October.
    5. Atanasov, Vladimir & Merrick, John, 2011. "Financial asset demand is elastic: Evidence from new issues of Federal Home Loan Bank debt," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3225-3239.
    6. James H. Stock & Mark W. Watson, 2018. "Identification and Estimation of Dynamic Causal Effects in Macroeconomics Using External Instruments," Economic Journal, Royal Economic Society, vol. 128(610), pages 917-948, May.
    7. Jalan, Akanksha & Matkovskyy, Roman & Potì, Valerio, 2022. "Shall the winning last? A study of recent bubbles and persistence," Finance Research Letters, Elsevier, vol. 45(C).
    8. Yarovaya, Larisa & Zięba, Damian, 2022. "Intraday volume-return nexus in cryptocurrency markets: Novel evidence from cryptocurrency classification," Research in International Business and Finance, Elsevier, vol. 60(C).
    9. Lutz Kilian & Yun Jung Kim, 2011. "How Reliable Are Local Projection Estimators of Impulse Responses?," The Review of Economics and Statistics, MIT Press, vol. 93(4), pages 1460-1466, November.
    10. Baur, Dirk G. & Hong, KiHoon & Lee, Adrian D., 2018. "Bitcoin: Medium of exchange or speculative assets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 54(C), pages 177-189.
    11. José Luis Montiel Olea & Mikkel Plagborg‐Møller, 2021. "Local Projection Inference Is Simpler and More Robust Than You Think," Econometrica, Econometric Society, vol. 89(4), pages 1789-1823, July.
    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. Sheng, Xin & Marfatia, Hardik A. & Gupta, Rangan & Ji, Qiang, 2023. "The non-linear response of US state-level tradable and non-tradable inflation to oil shocks: The role of oil-dependence," Research in International Business and Finance, Elsevier, vol. 64(C).
    2. Kaixing Huang, 2024. "Fertility and long‐term economic growth," Economic Inquiry, Western Economic Association International, vol. 62(3), pages 1152-1171, July.
    3. Endong Wang, 2024. "Structural counterfactual analysis in macroeconomics: theory and inference," Papers 2409.09577, arXiv.org.
    4. Bruns, Martin & Lütkepohl, Helmut, 2022. "Comparison of local projection estimators for proxy vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    5. Elstner, Steffen & Grimme, Christian & Kecht, Valentin & Lehmann, Robert, 2022. "The diffusion of technological progress in ICT," European Economic Review, Elsevier, vol. 149(C).
    6. Ruhollah Eskandari & Morteza Zamanian, 2023. "Heterogeneous responses to corporate marginal tax rates: Evidence from small and large firms," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(7), pages 1018-1047, November.
    7. Brianti, Marco & Cormun, Vito, 2023. "Expectation-Driven Boom-Bust Cycles," Working Papers 2023-4, University of Alberta, Department of Economics.
    8. Pablo Aguilar Perez, 2024. "Global Spillovers of US Monetary Policy: New Insights from the Remittance Channel," EconomiX Working Papers 2024-27, University of Paris Nanterre, EconomiX.
    9. Robert Adamek & Stephan Smeekes & Ines Wilms, 2024. "Local projection inference in high dimensions," The Econometrics Journal, Royal Economic Society, vol. 27(3), pages 323-342.
    10. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    11. De Santis, Roberto A. & Tornese, Tommaso, 2024. "US monetary policy is more powerful in low economic growth regimes," Working Paper Series 2919, European Central Bank.
    12. Robert Adamek & Stephan Smeekes & Ines Wilms, 2024. "Local projection inference in high dimensions," The Econometrics Journal, Royal Economic Society, vol. 27(3), pages 323-342.
    13. Karau, Sören, 2021. "Monetary policy and Bitcoin," Discussion Papers 41/2021, Deutsche Bundesbank.
    14. Sarah Arndt & Zeno Enders, 2023. "The Transmission of Supply Shocks in Different Inflation Regimes," CESifo Working Paper Series 10839, CESifo.
    15. repec:hal:spmain:info:hdl:2441/74362fq3f99s299n07e84dlcib is not listed on IDEAS
    16. Atsushi Inoue & `Oscar Jord`a & Guido M. Kuersteiner, 2023. "Inference for Local Projections," Papers 2306.03073, arXiv.org, revised Aug 2024.
    17. Cloyne, James & Jordà , Òscar & Taylor, Alan M., 2023. "State-Dependent Local Projections: Understanding Impulse Response Heterogeneity," CEPR Discussion Papers 17903, C.E.P.R. Discussion Papers.
    18. François-Éric Racicot & Raymond Théoret, 2022. "Tracking market and non-traditional sources of risks in procyclical and countercyclical hedge fund strategies under extreme scenarios: a nonlinear VAR approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-56, December.
    19. Oscar Jorda & Alan Taylor & Sanjay Singh, 2019. "The Long-Run Effects of Monetary Policy," 2019 Meeting Papers 1307, Society for Economic Dynamics.
    20. Pierre L. Siklos, 2020. "Looking into the Rear-View Mirror: Lessons from Japan for the Eurozone and the U.S?," IMES Discussion Paper Series 20-E-02, Institute for Monetary and Economic Studies, Bank of Japan.
    21. Martin Bruns & Helmut Lütkepohl, 2023. "An Alternative Bootstrap for Proxy Vector Autoregressions," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1857-1882, December.

    More about this item

    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:hal:journl:hal-03888337. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.