Mokesčių sistemos įtaka šešėlinei ekonomikai

LTStraipsniu siekiama nustatyti veiksnius, kurie daro įtaką šešėlinės ekonomikos augimui. Pirmiausia, straipsnyje apibūdinama šešėlinė ekonomika ir identifikuojami ją sąlygojantys veiksniai. Tyrimui atlikti pasirinkti mokslinės literatūros ir koreliacinės analizės, patikimumo testų metodai. Apskaičiuoti rezultatai leido įvertinti, kad koreliacinį ryšį su šešėline ekonomika turi metinis grynasis uždarbis ir mokesčių našta. Atlikta daugialypės regresijos analizė parodė modelio tinkamumą ir leidžia statistiškai patikimai teigti, kad įvardyti nepriklausomi kintamieji daro įtaką šešėlinei ekonomikai. Svarbu tai, kad regresinė lygtis teigia, jog padidinus metinį grynąjį uždarbį, išvengti šešėlinės ekonomikos augimo nepavyks, nes nustatytas tiesioginis priklausomumas. Parinktas modelis interpretuoja, jog šešėlinės ekonomikos kitimus 79 proc. sąlygoja metinio grynojo uždarbio ir mokesčių naštos kitimas, kai kiti veiksniai yra pastovūs. Raktažodžiai: šešėlinė ekonomika, mokestinė našta, nepriklausomi kintamieji. [Iš leidinio]

ENThe shadow economy, beyond state regulation and no longer under tax control, is damaging the whole economy, the overall growth of the “good”. It is always very important to find out what factors affect the shadow economy. Then can be pursued reductions in the informal economy in order to reduce poverty, increase economic and social security, and improve revenue collection in the national budget. It is significant that income inequality, the extent of poverty, and the wedge between the most vulnerable groups become apparent during various economic downturns or pandemics: this indicates the need for new research into the factors influencing the shadow economy. Question arising: In order to find out which factors and causes have the greatest impact, it is necessary to examine the areas in which the shadow economy occurs. The research question is what factors influence the shadow economy. Objective: determinants of the shadow economy. The aim of this article is to find and evaluate the determinants of the shadow economy. To achieve the goal it is first necessary to describe the shadow economy and identify the factors that determine it, then to develop an appropriate method and perform calculations based on it. The methods chosen for the research are analysis of scientific literature, synthesis, correlation analysis, multiple regression analysis, and reliability tests. The calculated results allowed to estimate that the annual net earnings and the tax burden have a correlation relationship with the shadow economy. The performed multiple regression analysis showed the suitability of the model and allows to reliably state statistically that the identified independent variables affect the shadow economy. Importantly, the regression equation states that increasing the annual net earnings will not prevent the growth of the shadow economy because direct dependence has been established.It is also important that the chosen model interprets that 79% of the changes in the shadow economy are caused by the change in the annual net earnings and tax burden, when other factors are constant. Conclusions: 1. The shadow economy is characterized by such features as undeclared income, avoidance of income tax, value added tax and other taxes; circumvention of such established rules as minimum wage and maximum working hours. Factors that may affect the shadow economy are highlighted: excise duty rate on alcohol, excise duty rate on tobacco, corruption perception index, and household indebtedness. 2. The research methodology consists of a correlation analysis describing the relationship between independent variables and a dependent variable (SE) and a multi-regression analysis. Additional studies were used to assess the reliability of the multiple regression model: a multicollinearity test showing whether a relationship exists between the independent variables themselves; heteroskedasty analysis showing whether all assumptions for modeling are satisfied, whether there is no violation of normality, or whether there is a nonlinear relationship between independent variables; autocorrelation test for interdependence of residual errors; Bonferroni standardized residue test and Shapiro-Wilk normality test. 3. Calculations have shown that a statistically significant relationship exists between the independent variables and the size of the shadow economy. Multiple regression analysis and model reliability tests showed that the chosen model is statistically reliable and found that the size of the shadow economy is influenced by the excise rate on alcohol, the rate of excise duty on tobacco, the corruption perception index, and household indebtedness. As the size of the independent variables increases, so does the size of the shadow economy. Keywords: shadow economy, tax burden, independent variables. [From the publication]

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