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The evolution of the bitcoin economy

Author

Listed:
  • Paolo Tasca
  • Adam Hayes
  • Shaowen Liu

Abstract

Purpose - This paper aims to gather together the minimum units of users’ identity in the Bitcoin network (i.e. the individual Bitcoin addresses) and group them into representations of business entities, what we call “super clusters”. While these clusters can remain largely anonymous, the authors are able to ascribe many of them to particular business categories by analyzing some of their specific transaction patterns (TPs), as observed during the period from 2009 to 2015. The authors are then able to extract and create a map of the network of payment relationships among them, and analyze transaction behavior found in each business category. They conclude by identifying three marked regimes that have evolved as the Bitcoin economy has grown and matured: from an early prototype stage; to a second growth stage populated in large part with “sin” enterprise (i.e. gambling, black markets); to a third stage marked by a sharp progression away from “sin” and toward legitimate enterprises. Design/methodology/approach - Data mining. Findings - Four primary business categories are identified in the Bitcoin economy: miners, gambling services, black markets and exchanges. Common patterns of transaction behavior between the business categories and their users are a “one-day” holding period for bitcoin transactions is somewhat typical. That is, a one-day effect where traders, gamblers, black market participants and miners tend to cash out on a daily basis. There seems to be a strong preference to do business within the bitcoin economy in round lot amounts, whether it is more typical of traders exchanging for fiat money, gamblers placing bets or black market goods being bought and sold. Distinct patterns of transaction behavior among the business categories and their users are flows between traders and exchanges average just around 20 BTC, and traders buy or sell on average every 11 days. Meanwhile, gamblers wager just 0.5 BTC on average, but re-bet often within the same day. Three marked regimes have evolved, as the Bitcoin economy has grown and matured: from an early prototype stage, to a second growth stage populated in large part with “sin” enterprises (i.e. gambling, black markets), to a third stage marked by a sharp progression away from “sin” and toward legitimate enterprises. This evolution of the Bitcoin economy suggests a trend toward legitimate commerce. Originality/value - The authors propose a new theoretical framework that allows investigating and exploring the network of payment relationships in the Bitcoin economy. This study starts by gathering together the minimum units of Bitcoin identities (the individual addresses), and it goes forward in grouping them into approximations of business entities, what is called “super clusters”, by using tested techniques from the literature. A super cluster can be thought of as an approximation of a business entity in that it describes a number of individual addresses that are owned or controlled collectively by the same beneficial owner for some special economic purposes. The majority of these important clusters are initially unknown and uncategorized. The novelty of this study is given by the pure user group and the TP analyses, by means of which the authors are able to ascribe the super clusters into specific business categories and outline a map of the network of payment relationships among them.

Suggested Citation

  • Paolo Tasca & Adam Hayes & Shaowen Liu, 2018. "The evolution of the bitcoin economy," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 19(2), pages 94-126, March.
  • Handle: RePEc:eme:jrfpps:jrf-03-2017-0059
    DOI: 10.1108/JRF-03-2017-0059
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    Citations

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    Cited by:

    1. Sadawi, Alia Al & Madani, Batool & Saboor, Sara & Ndiaye, Malick & Abu-Lebdeh, Ghassan, 2021. "A comprehensive hierarchical blockchain system for carbon emission trading utilizing blockchain of things and smart contract," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    2. Cole, Benjamin M. & Dyhrberg, Anne H. & Foley, Sean & Svec, Jiri, 2022. "Can Bitcoin be Trusted? Quantifying the economic value of blockchain transactions," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    3. Juneman Abraham & Dian Utami Sutiksno & Nuning Kurniasih & Ari Warokka, 2019. "Acceptance and Penetration of Bitcoin: The Role of Psychological Distance and National Culture," SAGE Open, , vol. 9(3), pages 21582440198, July.
    4. Henry, Christopher S. & Huynh, Kim P. & Nicholls, Gradon, 2018. "Bitcoin awareness and usage in Canada," Journal of Digital Banking, Henry Stewart Publications, vol. 2(4), pages 311-337, May.
    5. Abeer ElBahrawy & Laura Alessandretti & Anne Kandler & Romualdo Pastor-Satorras & Andrea Baronchelli, 2017. "Evolutionary dynamics of the cryptocurrency market," Papers 1705.05334, arXiv.org, revised Nov 2017.
    6. Alberto Bracci & Jorn Boehnke & Abeer ElBahrawy & Nicola Perra & Alexander Teytelboym & Andrea Baronchelli, 2021. "Macroscopic properties of buyer-seller networks in online marketplaces," Papers 2112.09065, arXiv.org, revised Apr 2022.
    7. Cheng, Jiameng & Dai, Yanke, 2020. "Is bitcoin a channel of capital inflow? Evidence from carry trade activity," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 261-278.
    8. Christopher Henry & Kim Huynh & Gradon Nicholls, 2017. "Bitcoin Awareness and Usage in Canada," Staff Working Papers 17-56, Bank of Canada.
    9. Abhijit Chakraborty & Tetsuo Hatsuda & Yuichi Ikeda, 2022. "Projecting XRP price burst by correlation tensor spectra of transaction networks," Papers 2211.03002, arXiv.org, revised May 2023.
    10. Ying Chen & Paolo Giudici & Branka Hadji Misheva & Simon Trimborn, 2020. "Lead Behaviour in Bitcoin Markets," Risks, MDPI, vol. 8(1), pages 1-14, January.
    11. Karau, Sören, 2021. "Monetary policy and Bitcoin," Discussion Papers 41/2021, Deutsche Bundesbank.
    12. Silvia Bartolucci & Andrei Kirilenko, 2019. "A Model of the Optimal Selection of Crypto Assets," Papers 1906.09632, arXiv.org.
    13. Dan Amiram & Bjørn N. Jørgensen & Daniel Rabetti, 2022. "Coins for Bombs: The Predictive Ability of On‐Chain Transfers for Terrorist Attacks," Journal of Accounting Research, Wiley Blackwell, vol. 60(2), pages 427-466, May.
    14. Chen, Hao & Xu, Chao, 2022. "The impact of cryptocurrencies on China's carbon price variation during COVID-19: A quantile perspective," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    15. Klarin, Anton, 2020. "The decade-long cryptocurrencies and the blockchain rollercoaster: Mapping the intellectual structure and charting future directions," Research in International Business and Finance, Elsevier, vol. 51(C).

    More about this item

    Keywords

    Business analysis; Bitcoin; Network theory; Blockchain; Digital currencies; Payment traceability; E42; L14; O12; O35; P40;
    All these keywords.

    JEL classification:

    • E42 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Monetary Sytsems; Standards; Regimes; Government and the Monetary System
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • O35 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Social Innovation
    • P40 - Political Economy and Comparative Economic Systems - - Other Economic Systems - - - General

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