IDEAS home Printed from https://ideas.repec.org/a/eee/ecanpo/v67y2020icp273-291.html
   My bibliography  Save this article

What predicts the legal status of cryptocurrencies?

Author

Listed:
  • Stolbov, Mikhail
  • Shchepeleva, Maria

Abstract

The paper aims to identify pivotal predictors of cryptocurrency legal status in a sample of 134 countries, which includes jurisdictions where cryptocurrencies are legal as well as implicitly or explicitly banned. By applying the Bayesian model averaging (BMA) for logit models and sparse group least absolute shrinkage and selection operator (LASSO) to 26 candidate predictors, we find that higher values of voice and accountability index, capturing governance quality, increase the likelihood of free cryptocurrency circulation, whereas an enhanced access to electricity, conducive to intense cryptocurrency mining, produces the opposite effect. The latter may arise from the fact that regulators perceive an increased access to electricity as an early warning signal of excessive and, thus, speculative cryptocurrency activities in the future, thereby imposing preemptive regulatory restrictions. A battery of robustness checks confirm the relevance of voice and accountability index as well as access to electricity, also revealing digital adoption index, which promotes cryptocurrency legality, as their closest contender in terms of variable importance. Governments need to take into account the identified factors when shaping their regulatory stance on cryptocurrencies.

Suggested Citation

  • Stolbov, Mikhail & Shchepeleva, Maria, 2020. "What predicts the legal status of cryptocurrencies?," Economic Analysis and Policy, Elsevier, vol. 67(C), pages 273-291.
  • Handle: RePEc:eee:ecanpo:v:67:y:2020:i:c:p:273-291
    DOI: 10.1016/j.eap.2020.07.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0313592620304057
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eap.2020.07.011?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Lorenzo Caprio & Silvia Rigamonti & Andrea Signori, 2020. "Legal origin, financial development, and innovation: evidence from large public and private firms in the U.S. and Europe," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 24(4), pages 905-925, December.
    2. Raphael Auer, 2019. "Embedded supervision: how to build regulation into blockchain finance," BIS Working Papers 811, Bank for International Settlements.
    3. Andrei Shleifer & Florencio Lopez-de-Silanes & Rafael La Porta, 2008. "The Economic Consequences of Legal Origins," Journal of Economic Literature, American Economic Association, vol. 46(2), pages 285-332, June.
    4. Kowalewski, Oskar & Pisany, Paweł, 2023. "The rise of fintech: A cross-country perspective," Technovation, Elsevier, vol. 122(C).
    5. Iftekhar Hasan & Roman Horvath & Jan Mares, 2018. "What Type of Finance Matters for Growth? Bayesian Model Averaging Evidence," The World Bank Economic Review, World Bank, vol. 32(2), pages 383-409.
    6. Helmut Stix, 2021. "Ownership and purchase intention of crypto-assets: survey results," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(1), pages 65-99, February.
    7. Krüger, Jens J. & Rhiel, Mathias, 2016. "Determinants of ICT Infrastructure: A Cross-Country Statistical Analysis," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 83988, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    8. Vincent, Martin & Hansen, Niels Richard, 2014. "Sparse group lasso and high dimensional multinomial classification," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 771-786.
    9. Oana Peia, 2017. "Banking Crises and Investments in Innovation," Working Papers 201727, School of Economics, University College Dublin.
    10. Phuc Canh, Nguyen & Trung Thong, Nguyen, 2020. "Nexus between financialisation and natural resources rents: Empirical evidence in a global sample," Resources Policy, Elsevier, vol. 66(C).
    11. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "High-Dimensional Methods and Inference on Structural and Treatment Effects," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 29-50, Spring.
    12. Howard Bodenhorn & David Cuberes, 2010. "Financial development and city growth: Evidence from Northeastern American cities, 1790-1870," Working Papers 2010/35, Institut d'Economia de Barcelona (IEB).
    13. Roland Bénabou & Davide Ticchi & Andrea Vindigni, 2015. "Religion and Innovation," American Economic Review, American Economic Association, vol. 105(5), pages 346-351, May.
    14. Simplice A. Asongu & Jacinta C. Nwachukwu, 2019. "ICT, Financial Sector Development and Financial Access," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(2), pages 465-490, June.
    15. Mr. Luc Laeven & Mr. Fabian Valencia, 2018. "Systemic Banking Crises Revisited," IMF Working Papers 2018/206, International Monetary Fund.
    16. Dan Huang & Dong Lu & Jin-hui Luo, 2016. "Corporate innovation and innovation efficiency: does religion matter?," Nankai Business Review International, Emerald Group Publishing Limited, vol. 7(2), pages 150-191, June.
    17. Simplice A. Asongu & Nicholas Biekpe, 2017. "Government quality determinants of ICT adoption in sub-Saharan Africa," Netnomics, Springer, vol. 18(2), pages 107-130, December.
    18. Susan Athey & Guido W. Imbens, 2019. "Machine Learning Methods That Economists Should Know About," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 685-725, August.
    19. Shanaev, Savva & Sharma, Satish & Ghimire, Binam & Shuraeva, Arina, 2020. "Taming the blockchain beast? Regulatory implications for the cryptocurrency Market," Research in International Business and Finance, Elsevier, vol. 51(C).
    20. Ji, Yaling, 2020. "Religiosity and the adoption of formal financial services," Economic Modelling, Elsevier, vol. 89(C), pages 378-396.
    21. Fassio, Claudio & Montobbio, Fabio & Venturini, Alessandra, 2019. "Skilled migration and innovation in European industries," Research Policy, Elsevier, vol. 48(3), pages 706-718.
    22. Armin Falk & Anke Becker & Thomas Dohmen & Benjamin Enke & David B. Huffman & Uwe Sunde, 2017. "Global Evidence on Economic Preferences," NBER Working Papers 23943, National Bureau of Economic Research, Inc.
    23. Howard Bodenhorn & David Cuberes, 2010. "Financial Development and City Growth: Evidence from Northeastern American Cities, 1790-1870," NBER Working Papers 15997, National Bureau of Economic Research, Inc.
    24. Lee, Sangwon & Nam, Yoonjae & Lee, Seonmi & Son, Hyunjung, 2016. "Determinants of ICT innovations: A cross-country empirical study," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 71-77.
    25. Kim, Dong-Hyeon & Lin, Shu-Chin & Suen, Yu-Bo, 2010. "Dynamic effects of trade openness on financial development," Economic Modelling, Elsevier, vol. 27(1), pages 254-261, January.
    26. Krüger, Jens J. & Rhiel, Mathias, 2016. "Determinants of ICT infrastructure: A cross-country statistical analysis," Darmstadt Discussion Papers in Economics 228, Darmstadt University of Technology, Department of Law and Economics.
    27. Jon Frost, 2020. "The economic forces driving FinTech adoption across countries," Working Papers 663, DNB.
    28. Christian Haddad & Lars Hornuf, 2019. "The emergence of the global fintech market: economic and technological determinants," Small Business Economics, Springer, vol. 53(1), pages 81-105, June.
    29. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    30. Armin Falk & Anke Becker & Thomas Dohmen & Benjamin Enke & David Huffman & Uwe Sunde, 2018. "Global Evidence on Economic Preferences," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(4), pages 1645-1692.
    31. James R. Brown & Gustav Martinsson & Bruce C. Petersen, 2013. "Law, Stock Markets, and Innovation," Journal of Finance, American Finance Association, vol. 68(4), pages 1517-1549, August.
    32. Muhammad Shahbaz & Mita Bhattacharya & Mantu Kumar Mahalik, 2018. "Financial development, industrialization, the role of institutions and government: a comparative analysis between India and China," Applied Economics, Taylor & Francis Journals, vol. 50(17), pages 1952-1977, April.
    33. Raphael Auer & Stijn Claessens, 2018. "Regulating cryptocurrencies: assessing market reactions," BIS Quarterly Review, Bank for International Settlements, September.
    34. Arin, K. Peren & Braunfels, Elias, 2018. "The resource curse revisited: A Bayesian model averaging approach," Energy Economics, Elsevier, vol. 70(C), pages 170-178.
    35. Ashraf, Badar Nadeem, 2018. "Do trade and financial openness matter for financial development? Bank-level evidence from emerging market economies," Research in International Business and Finance, Elsevier, vol. 44(C), pages 434-458.
    36. Rainer Böhme & Nicolas Christin & Benjamin Edelman & Tyler Moore, 2015. "Bitcoin: Economics, Technology, and Governance," Journal of Economic Perspectives, American Economic Association, vol. 29(2), pages 213-238, Spring.
    37. Özlem Sayılır & Murat Doğan & Nahifa Said Soud, 2018. "Financial development and governance relationships," Applied Economics Letters, Taylor & Francis Journals, vol. 25(20), pages 1466-1470, November.
    38. Pick, James B. & Sarkar, Avijit & Johnson, Jeremy, 2015. "United States digital divide: State level analysis of spatial clustering and multivariate determinants of ICT utilization," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 16-32.
    39. Christopher Henry & Kim Huynh & Gradon Nicholls & Mitchell Nicholson, 2019. "2018 Bitcoin Omnibus Survey: Awareness and Usage," Discussion Papers 2019-10, Bank of Canada.
    40. Lorenzo Bencivelli & Massimiliano Marcellino & Gianluca Moretti, 2017. "Forecasting economic activity by Bayesian bridge model averaging," Empirical Economics, Springer, vol. 53(1), pages 21-40, August.
    41. Metzger, Martina & Riedler, Tim & Pédussel Wu, Jennifer, 2019. "Migrant remittances: Alternative money transfer channels," IPE Working Papers 127/2019, Berlin School of Economics and Law, Institute for International Political Economy (IPE).
    42. Erumban, Abdul Azeez & de Jong, Simon B., 2006. "Cross-country differences in ICT adoption: A consequence of Culture?," Journal of World Business, Elsevier, vol. 41(4), pages 302-314, December.
    43. Athey, Susan & Imbens, Guido W., 2019. "Machine Learning Methods Economists Should Know About," Research Papers 3776, Stanford University, Graduate School of Business.
    44. Siong Law & W. Azman-Saini, 2012. "Institutional quality, governance, and financial development," Economics of Governance, Springer, vol. 13(3), pages 217-236, September.
    45. Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
    46. Sean Foley & Jonathan R Karlsen & Tālis J Putniņš, 2019. "Sex, Drugs, and Bitcoin: How Much Illegal Activity Is Financed through Cryptocurrencies?," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 1798-1853.
    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. Aziz N. Berdiev & Rajeev K. Goel & James W. Saunoris, 2024. "Global cryptocurrency use, corruption, and the shadow economy: New insights into the underlying linkages," American Journal of Economics and Sociology, Wiley Blackwell, vol. 83(3), pages 609-629, May.
    2. Auer, Raphael & Farag, Marc & Lewrick, Ulf & Orazem, Lovrenc & Zoss, Markus, 2023. "Banking in the shadow of Bitcoin? The institutional adoption of cryptocurrencies," CEPR Discussion Papers 18331, C.E.P.R. Discussion Papers.
    3. Raphael Auer & Marc Farag & Ulf Lewrick & Lovrenc Orazem & Markus Zoss, 2022. "Banking in the shadow of Bitcoin? The institutional adoption of cryptocurrencies," BIS Working Papers 1013, Bank for International Settlements.
    4. Gonzálvez-Gallego, Nicolás & Pérez-Cárceles, María Concepción, 2021. "Cryptocurrencies and illicit practices: The role of governance," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 203-212.
    5. Goel, Rajeev K. & Mazhar, Ummad, 2024. "Cryptocurrency use and tax collections: Direct and indirect channels of influence," Journal of Financial Stability, Elsevier, vol. 72(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. Muhammad Atif Khan & Muhammad Asif Khan & Kishwar Ali & József Popp & Judit Oláh, 2020. "Natural Resource Rent and Finance: The Moderation Role of Institutions," Sustainability, MDPI, vol. 12(9), pages 1-23, May.
    2. Svetlana Abramova & Rainer Böhme & Helmut Elsinger & Helmut Stix & Martin Summer, 2022. "What can CBDC designers learn from asking potential users? Results from a survey of Austrian residents (Svetlana Abramova, Rainer Böhme, Helmut Elsinger, Helmut Stix, Martin Summer)," Working Papers 241, Oesterreichische Nationalbank (Austrian Central Bank).
    3. Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Machine-Learning Approach," Economics working papers 2021-08, Department of Economics, Johannes Kepler University Linz, Austria.
    4. Byron Botha & Rulof Burger & Kevin Kotzé & Neil Rankin & Daan Steenkamp, 2023. "Big data forecasting of South African inflation," Empirical Economics, Springer, vol. 65(1), pages 149-188, July.
    5. Shanaev, Savva & Sharma, Satish & Ghimire, Binam & Shuraeva, Arina, 2020. "Taming the blockchain beast? Regulatory implications for the cryptocurrency Market," Research in International Business and Finance, Elsevier, vol. 51(C).
    6. Tatiana de Macedo Nogueira Lima, 2022. "Documento de Trabalho 03/2022 - Aprendizado de máquina e antitruste," Documentos de Trabalho 2022030, Conselho Administrativo de Defesa Econômica (Cade), Departamento de Estudos Econômicos.
    7. Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Causal Machine-Learning Approach," Papers 2103.10251, arXiv.org, revised Sep 2021.
    8. Sebastian Galiani & Juan Pantano, 2021. "Structural Models: Inception and Frontier," NBER Working Papers 28698, National Bureau of Economic Research, Inc.
    9. Akash Malhotra, 2021. "A hybrid econometric–machine learning approach for relative importance analysis: prioritizing food policy," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 549-581, September.
    10. Sophie-Charlotte Klose & Johannes Lederer, 2020. "A Pipeline for Variable Selection and False Discovery Rate Control With an Application in Labor Economics," Papers 2006.12296, arXiv.org, revised Jun 2020.
    11. Ay, Jean-Sauveur & Le Gallo, Julie, 2021. "The Signaling Values of Nested Wine Names," Working Papers 321851, American Association of Wine Economists.
    12. Hanna Halaburda & Guillaume Haeringer & Joshua Gans & Neil Gandal, 2022. "The Microeconomics of Cryptocurrencies," Journal of Economic Literature, American Economic Association, vol. 60(3), pages 971-1013, September.
    13. Muhammad Shahbaz & Hrushikesh Mallick & Mantu Kumar Mahalik & Shawkat Hammoudeh, 2018. "Is globalization detrimental to financial development? Further evidence from a very large emerging economy with significant orientation towards policies," Applied Economics, Taylor & Francis Journals, vol. 50(6), pages 574-595, February.
    14. Barzin,Samira & Avner,Paolo & Maruyama Rentschler,Jun Erik & O’Clery,Neave, 2022. "Where Are All the Jobs ? A Machine Learning Approach for High Resolution Urban Employment Prediction inDeveloping Countries," Policy Research Working Paper Series 9979, The World Bank.
    15. Daniela Balutel & Christopher Henry & Jorge Vásquez & Marcel Voia, 2022. "Bitcoin adoption and beliefs in Canada," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(4), pages 1729-1761, November.
    16. Raphael Auer, 2019. "Beyond the doomsday economics of "proof-of-work" in cryptocurrencies," BIS Working Papers 765, Bank for International Settlements.
    17. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    18. Turati, Riccardo, 2024. "Network Abroad and Culture: Global Individual-Level Evidence," GLO Discussion Paper Series 1488, Global Labor Organization (GLO).
    19. Gonzálvez-Gallego, Nicolás & Pérez-Cárceles, María Concepción, 2021. "Cryptocurrencies and illicit practices: The role of governance," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 203-212.
    20. Mona Aghdaee & Bonny Parkinson & Kompal Sinha & Yuanyuan Gu & Rajan Sharma & Emma Olin & Henry Cutler, 2022. "An examination of machine learning to map non‐preference based patient reported outcome measures to health state utility values," Health Economics, John Wiley & Sons, Ltd., vol. 31(8), pages 1525-1557, August.

    More about this item

    Keywords

    Cryptocurrency; Legal status; Bayesian model averaging; Sparse group LASSO model; Random forest;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

    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:eee:ecanpo:v:67:y:2020:i:c:p:273-291. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/economic-analysis-and-policy .

    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.