| Abstract [eng] |
The main objective of this Master's thesis is to identify, assess and compare the factors determining the VAT gap in the EU and Lithuania. The work consists of three main parts: the analysis of literature, the research and its results, conclusion and recommendations. The literature analysis part describes VAT and its system and explains the concept of the value added tax gap. Finally, a literature review identifies the determinants of the value added gap identified in other authors' studies. The second part of the paper justifies the study and describes the main stages of the research: the subject and the period under study are discussed, the variables are identified and the hyphotesis are formulated, and finally, the research methods are selected and described. The third part of the thesis describes, displays, analyses and systematises the results obtained in the course of the study by analysing the statistical data on the value added tax gap and its determinants, then using correlation analysis to identify the factors that have a significant statistical relationship with the value added tax gap, and lastly, using the selected significant variables to perform a regression analysis to assess the factors that determine the VAT gap. The assessment of the determinants of the VAT gap in the EU and Lithuania shows that the VAT gap in the EU and Lithuania is influenced by different factors, and no common factors were found in both territories. Out of the 6 factors selected, only one was significant in the EU context - government efficiency, while in the Lithuanian context 2 out of 6 factors were significant - corruption index and inflation. These results show that it is not very useful to analyse the EU as a single territorial unit, as not all EU countries are at the same economic and social level, which may distort the results, and it is therefore recommended that the VAT gap factors are assessed for individual EU countries or regions instead. Moreover, the regression models of the VAT gap and its determinants have shown that the models explain the variations in the VAT gap over the period analysed with a high degree of accuracy. The EU regression model with one dependent variable explains about 91% of the variation in the VAT gap in the EU, while the Lithuanian regression model with 2 dependent variables explains about 96% of the variation in the VAT gap in Lithuania. |
