Evaluation of the Level of Shadow Economy in Lithuanian Regions

Remeikienė, Rita; Gasparėnienė, Ligita; Yorulmaz, Özlem; Schieg, Martin; Stasiukynas, Andrius

doi:10.3846/jbem.2021.15405

Cited by 5 publications

(2 citation statements)

References 27 publications

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“…One of the most influential inhibitors of the country's economic development is the shadow economy. According to the results of the structural analysis of the shadow sector of the economy, money is often the object of manipulation by participants in shadow operations (Safuan et al, 2021;Remeikienė et al, 2021;Fedajev et al, 2022;Buszko, 2022). Increasingly, economic entities direct their efforts to distort their financial, accounting or tax reporting in the direction of reducing the declared amount of income, hiding part of the results of their activities.…”

Section: Figure 1 the Number Of Searches For The Term "Financial Pote...mentioning

confidence: 99%

Modeling the Impact of Shadow Financial Transactions on the Country’s Financial Potential

Tiutiunyk

Kozhushko

2022

FMIR

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The article summarizes the arguments and counterarguments within the scientific debate on the issue of raising the level of the country’s financial potential. The main goal of the conducted research is to model the impact of shadow operations on the level of the country’s financial potential. Analysis of the dynamics of publication activity on issues of the shadow economy and financial potential in publications indexed by the Scopus and Web of Science databases, bibliometric analysis of the connection between the concept of the shadow economy and other economic categories made it possible to identify theories that are most closely related to this concept: theory innovative management, theory of liberalization, theory of political economy, institutional theory. The urgency of solving this scientific problem lies in the fact that in the conditions of a protracted economic crisis and active military operations on the territory of Ukraine, significant volumes of shadow operations negatively affect the attractiveness of the country from the side of international partners, the level of its financial stability, the ability to withstand economic and political risks. Methods of dynamic analysis, Erlang’s formula, methods of regression analysis became the methodical toolkit of the conducted research, the period of the study was 2008-2021. The article presents the results of an empirical analysis of the financial potential of Ukraine, which showed a gradual increase in its level until 2021. At the same time, the forecast values of the level of financial potential in 2022 indicate its significant reduction and the need to implement a set of measures aimed at maintaining the macroeconomic stability of the country and its financial independence. The study empirically confirms and theoretically proves that the main drivers of the shadowing of the economy include: a low level of material or criminal responsibility for these actions, an excessive level of tax burden, the inability of the government to monitor the compliance of economic entities with existing norms and laws in the country. The results of the conducted research can be useful for public administration bodies in the context of improving the policy of countering shadowing of the economy as a component of increasing the country’s financial potential.

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Section: Figure 1 the Number Of Searches For The Term "Financial Pote...mentioning

confidence: 99%

Modeling the Impact of Shadow Financial Transactions on the Country’s Financial Potential

Tiutiunyk

Kozhushko

2022

FMIR

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“…The phenomenon of the shadow economy relates to the constant analysis of its emergence drivers and the search for mechanisms to counteract it (Bozhenko, 2021;Orlov et al, 2021;Remeikienė & Gasparėnienė, 2021;Remeikienė et al, 2021;Tran, 2022). Nowadays, there is no unified understanding of the role of the shadow economy in the functioning of the economy and ensuring its stability.…”

Section: Literature Reviewmentioning

confidence: 99%

Foreign direct investment and shadow economy: One-way effect or multiple-way causality?

Tiutiunyk¹,

Cieśliński²,

Zolkover³

et al. 2022

Journal of International Studies

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The article examines the relationship between the size of the shadow economy and indicators of the investment market development. Net inflow of foreign direct investments, volume of net investments in non-financial assets, volumes of portfolio investments, and net outflow of foreign direct investment were used as parameters characterizing the development of the investment market. The dependence between the indicators was analyzed using the regression equation, Shapiro-Wilk test. Research results demonstrate that the increase in the inflow and outflow of foreign direct investments leads to an increase in the size of the shadow economy without a time lag in Ukraine, Poland, Slovenia, Romania, Croatia, Lithuania, Latvia, Estonia, and with a time lag of 1 year in Slovakia and Hungary. The largest impact on the size of the shadow economy is made by the volume of inflow and outflow of direct foreign investments, while the volume of portfolio investments has a less significant effect. Consequently, it was concluded that the processes of inflow and outflow of direct foreign investments require enhanced control by specialized state executive bodies given the scale of their potential destabilizing impact on the macroeconomic stability of the country.

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Can the digital economy development limit the size of the informal economy? A nonlinear analysis based on China's provincial panel data

Lv,

Li,

Zhu

et al. 2024

Economic Analysis and Policy

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Evaluation of the Level of Shadow Economy in Lithuanian Regions

Cited by 5 publications

References 27 publications

Modeling the Impact of Shadow Financial Transactions on the Country’s Financial Potential

Modeling the Impact of Shadow Financial Transactions on the Country’s Financial Potential

Foreign direct investment and shadow economy: One-way effect or multiple-way causality?

Can the digital economy development limit the size of the informal economy? A nonlinear analysis based on China's provincial panel data

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