Evaluation of the level of shadow economy in Lithuanian regions
The article addresses a topical issue which is extremely relevant in crisis periods – evaluation of the level of the shadow economy in all Lithuanian regions. By applying the MIMIC modelling, three equations were developed for three different periods: economic upturn, economic downturn (crisis) and...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Vilnius Gediminas Technical University
2021-10-01
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| Series: | Journal of Business Economics and Management |
| Subjects: | |
| Online Access: | https://journals.vgtu.lt/index.php/JBEM/article/view/15405 |
| _version_ | 1818985685284028416 |
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| author | Rita Remeikienė Ligita Gasparėnienė Özlem Yorulmaz Martin Schieg Andrius Stasiukynas |
| author_facet | Rita Remeikienė Ligita Gasparėnienė Özlem Yorulmaz Martin Schieg Andrius Stasiukynas |
| author_sort | Rita Remeikienė |
| collection | DOAJ |
| description | The article addresses a topical issue which is extremely relevant in crisis periods – evaluation of the level of the shadow economy in all Lithuanian regions. By applying the MIMIC modelling, three equations were developed for three different periods: economic upturn, economic downturn (crisis) and economic recovery. The number of immigrants, employment rate and population’s density were identified as the major shadow economy determinants in Lithuanian regions. The determinants identified are unique in the case of Lithuania because they reveal that the labour market (employment rate, the number of immigrants) and population’s density are the key factors that show how municipalities address the issues of the shadow economy. 10 municipalities with respectively high or low levels of the shadow economy were ranked for each period under consideration. The maps developed for different periods illustrate the general trends of the evolution of the shadow economy. This is the first study that estimates the size of the shadow economy in 60 municipalities (a small regional division) with different economic periods taken into account. Scientific novelty manifests through consideration of the regional shadow economy and proving significance of the labour market and immigration in reducing regional disparities. |
| first_indexed | 2024-12-20T18:38:49Z |
| format | Article |
| id | doaj.art-7bb576927ceb4bc2ac9676a6da06d9be |
| institution | Directory Open Access Journal |
| issn | 1611-1699 2029-4433 |
| language | English |
| last_indexed | 2024-12-20T18:38:49Z |
| publishDate | 2021-10-01 |
| publisher | Vilnius Gediminas Technical University |
| record_format | Article |
| series | Journal of Business Economics and Management |
| spelling | doaj.art-7bb576927ceb4bc2ac9676a6da06d9be2022-12-21T19:29:52ZengVilnius Gediminas Technical UniversityJournal of Business Economics and Management1611-16992029-44332021-10-012251360137710.3846/jbem.2021.1540515405Evaluation of the level of shadow economy in Lithuanian regionsRita Remeikienė0Ligita Gasparėnienė1Özlem Yorulmaz2Martin Schieg3Andrius Stasiukynas4Law Faculty, Vilnius University, Vilnius, LithuaniaLaw Faculty, Vilnius University, Vilnius, LithuaniaDepartment of Econometrics, Faculty of Economics, Istanbul University, Istanbul, TurkeyTechnical University of Munich, Munich, GermanyBusiness School, Kazimieras Simonavičius University, Vilnius, LithuaniaThe article addresses a topical issue which is extremely relevant in crisis periods – evaluation of the level of the shadow economy in all Lithuanian regions. By applying the MIMIC modelling, three equations were developed for three different periods: economic upturn, economic downturn (crisis) and economic recovery. The number of immigrants, employment rate and population’s density were identified as the major shadow economy determinants in Lithuanian regions. The determinants identified are unique in the case of Lithuania because they reveal that the labour market (employment rate, the number of immigrants) and population’s density are the key factors that show how municipalities address the issues of the shadow economy. 10 municipalities with respectively high or low levels of the shadow economy were ranked for each period under consideration. The maps developed for different periods illustrate the general trends of the evolution of the shadow economy. This is the first study that estimates the size of the shadow economy in 60 municipalities (a small regional division) with different economic periods taken into account. Scientific novelty manifests through consideration of the regional shadow economy and proving significance of the labour market and immigration in reducing regional disparities.https://journals.vgtu.lt/index.php/JBEM/article/view/15405region shadow economythe level of shadow economy in municipalitiesmimic modellithuanian regionsmunicipalitiesdeterminants of shadow economy |
| spellingShingle | Rita Remeikienė Ligita Gasparėnienė Özlem Yorulmaz Martin Schieg Andrius Stasiukynas Evaluation of the level of shadow economy in Lithuanian regions Journal of Business Economics and Management region shadow economy the level of shadow economy in municipalities mimic model lithuanian regions municipalities determinants of shadow economy |
| title | Evaluation of the level of shadow economy in Lithuanian regions |
| title_full | Evaluation of the level of shadow economy in Lithuanian regions |
| title_fullStr | Evaluation of the level of shadow economy in Lithuanian regions |
| title_full_unstemmed | Evaluation of the level of shadow economy in Lithuanian regions |
| title_short | Evaluation of the level of shadow economy in Lithuanian regions |
| title_sort | evaluation of the level of shadow economy in lithuanian regions |
| topic | region shadow economy the level of shadow economy in municipalities mimic model lithuanian regions municipalities determinants of shadow economy |
| url | https://journals.vgtu.lt/index.php/JBEM/article/view/15405 |
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