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Metodika předpovědi digitální šedé ekonomiky

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dc.title Metodika předpovědi digitální šedé ekonomiky cs
dc.title The methodology of digital shadow economy estimation en
dc.contributor.author Gasparėnienė, Ligita
dc.contributor.author Bilan, Yuriy
dc.contributor.author Remeikienė, Rita
dc.contributor.author Ginevičius, Romualdas
dc.contributor.author Čepel, Martin
dc.relation.ispartof E a M: Ekonomie a Management
dc.identifier.issn 1212-3609 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2017
utb.relation.volume 20
utb.relation.issue 4
dc.citation.spage 20
dc.citation.epage 33
dc.type article
dc.language.iso en
dc.publisher Technical University of Liberec
dc.identifier.doi 10.15240/tul/001/2017-4-002
dc.relation.uri https://dspace.tul.cz/handle/15240/21376
dc.subject Causal variables en
dc.subject Digital shadow economy en
dc.subject Indicators of shadow economy en
dc.subject MIMIC model en
dc.subject Shadow economy en
dc.description.abstract The article introduces a new methodology of digital shadow economy estimation, which is based on the principles of the MIMIC method. This new methodology complements traditional methodologies of shadow economy estimation with such a component as digital shadow economy. Our analysis of the most popular today methods of shadow economic estimation proves that, despite some of its drawbacks, the MIMIC model can be treated as the most comprehensive and appropriate method for such calculations since it takes into account both causal and indicators of shadow economy. As the causal variables here, as applied to digital shadow economy, we use household access to the Internet and IT overall, the volume of non-cash payments and the use of most advanced fi nancial instruments. While as the indicators of the digital shadow economy spread we use: the volume of non-cash payments at online platforms, the frequency of cryptocurrency payments, and the cost of parcels to which customs duties have not been applied. For further empirical verifi cation of the model proposed here, numerical values of both causal variables and indicators would be necessary. Unfortunately, offi cial statistical sources are unable to provide such data in full volume, especially when it comes to cryptocurrencies and other informal payments. Thus, in our further research we plan to not only prove the practical applicability of the offered here model for estimations of digital shadow economy size as well as overall size of shadow economy on the examples of particular countries, but also to accumulate the necessary statistics for such calculations. © 2017, Technical University of Liberec. All rights reserved. en
utb.faculty Faculty of Management and Economics
dc.identifier.uri http://hdl.handle.net/10563/1007713
utb.identifier.obdid 43877299
utb.identifier.scopus 2-s2.0-85040239274
utb.identifier.wok 000419822200002
utb.source j-scopus
dc.date.accessioned 2018-02-26T10:20:00Z
dc.date.available 2018-02-26T10:20:00Z
dc.description.sponsorship MIP-15642, Lietuvos Mokslo Taryba
dc.description.sponsorship Research Council of Lithuania [MIP-15642]
dc.rights Attribution-NonCommercial 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc/4.0/
dc.rights.access openAccess
utb.contributor.internalauthor Bilan, Yuriy
utb.fulltext.affiliation Ligita Gasparėnienė, Yuriy Bilan, Rita Remeikienė, Romualdas Ginevičius, Martin Čepel Ligita Gasparėnienė, Dr. Mykolas Romeris University ligitagaspareniene@mruni.eu doc. Dr. Yuriy Bilan Research Associate Tomas Bata University in Zlin Faculty of Management and Economics Centre of Applied Economic Research yuriy_bilan@yahoo.co.uk Rita Remeikienė, Dr. Mykolas Romeris University rita.remeikiene@mruni.eu Prof. habil. dr. Romualdas Ginevičius Vilnius Gediminas Technical University romualdas.ginevicius@vgtu.lt Dr. Martin Čepel, PhD., MBA LIGS University LLC Honolulu cepel@benzinol.com
utb.fulltext.dates -
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utb.fulltext.sponsorship This work was supported by the Research Council of Lithuania (grant number MIP-15642).
utb.scopus.affiliation Mykolas Romeris University, Lithuania; Tomas Bata University in Zlin, Faculty of Management and Economics, Centre of Applied Economic Research, Czech Republic; Vilnius Gediminas Technical University, Lithuania; LIGS University LLC Honolulu, United States
utb.fulltext.projects MIP-15642
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