Generolo Jono Žemaičio Lietuvos karo akademija

The study presents a multidimensional comparative analysis of two dependent variables: the number of passengers transported by air in 28 European countries and the price of one barrel of crude oil in dollars. The conducted analysis shows that in the historical data concerning the identical periods (months) in both tested series, dependencies can be found. This allowed for the construction of a zero-one multiple regression model in order to confirm the impact of the number of passengers travelling by air on the price of one barrel of crude oil and describe this phenomenon with an analytical function.

The article analyses and summarizes the various author’s approach to value-added tax (hereinafter - VAT), its role in the tax system and the impact of VAT revenue on the state budget. The article considers the features of VAT, its positive and negative characteristics, discusses the aspects of implementation of tax function, and identifies the revenue collection determinants examined in literature. The impact of VAT revenues on the European Union (hereinafter - EU) Member States (hereinafter - MS) budgets, and the dynamics of the standard VAT rate and income from VAT collection efficiency is analysed. Having selected four EU Member States (Bulgaria, Italy, Ireland and Lithuania), the method of pair correlation is used to evaluate the economic and VAT describing factors affecting the revenue from VAT collection in these countries. The most correlating factors in each of the selected countries were used to create multiple regression models. After discussing the situation of VAT in the EU, the article analyses the dynamics of the revenue from VAT part in the state budget income. It examines the changes of revenue from VAT, the causes that determined a (non) enforcement of the plan of the revenue from VAT, the efficiency of the collection of revenue from VAT and its reasons analysing the case of Lithuania. In order to identify the factors that determined the revenue from the collection of VAT in Lithuania in the period 2005-2015, three multiple regression models were se up, analysed and summarized.