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dc.contributor.authorGasparėnienė, Ligita
dc.contributor.authorBilan, Yuriy
dc.contributor.authorRemeikienė, Rita
dc.contributor.authorGinevičius, Romualdas
dc.contributor.authorČepel, Martin
dc.date.accessioned2023-09-18T16:42:29Z
dc.date.available2023-09-18T16:42:29Z
dc.date.issued2017
dc.identifier.issn1212-3609
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/116200
dc.description.abstractThe 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 financial 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 verification of the model proposed here, numerical values of both causal variables and indicators would be necessary. Unfortunately, official 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.eng
dc.formatPDF
dc.format.extentp. 20-33
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbySocial Sciences Citation Index (Web of Science)
dc.relation.isreferencedbyEconLit
dc.relation.isreferencedbyINSPEC
dc.relation.isreferencedbyIBSS
dc.source.urihttps://repository.mruni.eu/handle/007/15508
dc.subjectVE05 - Socioekonominių sistemų universalaus tvarumo tyrimai / Universal sustainability research
dc.titleThe methodology of digital shadow economy estimation
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.accessRightsCC BY NC
dcterms.references57
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionMykolo Romerio universitetas
dc.contributor.institutionTomas Bata University in Zlin
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.institutionLIGS University LLC Honolulu
dc.contributor.facultyVerslo vadybos fakultetas / Faculty of Business Management
dc.subject.researchfieldS 004 - Ekonomika / Economics
dc.subject.ltspecializationsL103 - Įtrauki ir kūrybinga visuomenė / Inclusive and creative society
dc.subject.enShadow economy
dc.subject.endigital shadow economy
dc.subject.enindicators of shadow economy
dc.subject.encausal variables
dc.subject.enMIMIC model
dcterms.sourcetitleE & M Ekonomie a management
dc.description.issueiss. 4
dc.description.volumevol. 20
dc.publisher.nameTechnical University of Liberec
dc.publisher.cityLiberec
dc.identifier.doi85040239274
dc.identifier.doi000419822200002
dc.identifier.doi10.15240/tul/001/2017-4-002
dc.identifier.elaba25203150


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