Determinants of VAT Gap

According to Poniatowski & Bonch-Osmolovskiy & Śmietanka, 2020, there is a fundamental problem of ineffective tax collection, especially from a VAT point of view, in the EU. It is a challenge to assess the scale of tax evasion, which probably explains the lack of data published so far. As a result, the study of tax non-compliance determinants is no longer novel in the economic literature. The majority of the literature on such factors focuses solely on personal income taxes, voluntary tax compliance, and deterrence effects. This focus is related to data availability. A limited number of studies looking at such cross-country variations focus on interpreting dynamics in tax revenue (e.g., Aizenman and Jinjarak, 2018) or have a qualitative nature (e.g., Keen and Smith, 2007). Then, as more data sequences become available over a while long enough to cover economic ups and downs, they become more accessible. As a result, the finding provides an opportunity to conduct econometric analyses looking at the determinants of tax non-compliance from a new perspective.

Some researchers such as Barbone et al. (2013), Zídková (2017), Lešnik et al. (2018), Poniatowski et al. (2018 and 2019), Szczypińska (2019), and Carfora et al. (2020) have already used panel data for their VAT gap studies. European Commission's VAT Gap Studies, which were published in 2013, 2014, 2015, 2016, 2017, 2018, and 2019 have categorised variables such as:

15

- One of the categories of tax policy characteristics demonstrates how various tax administration efforts are linked to the VAT gap in each country. The amount spent on tax administration concerning GDP is insufficient to cover how effectively the funds are used. Furthermore, the IT expenditure variable is expected to determine the impact of development processes implemented in administrative procedures. Similarly, the administrative effectiveness variable refers to the tax administration's independence from political pressures and the quality of policy formulation and implementation.

- Another category is macroeconomic variables, which aim to explain cyclical conditions as they affect taxpayer behaviour. For example, consider unemployment, GDP per capita.

- Other variables describe the economy's sectoral and corporate structure. In particular, it is emphasised the retail sector, which could be the key for the shadow economy and tax evasion, and the other labour-intensive industries such as real estate, construction, industry, telecommunications, and art. This model also considers the structure of companies based on employment size and the relative size of the shadow economy.

- Since the variability of tax fraud, a significant component of the VAT Gap, may be linked to particular factors that are not included in the list of covariates.

Three methods are used to estimate the scope of the fraud. As one of the possible indicators of fraud, international trade is immediate changes in intra-Community purchase figures, which would indicate an increasing scale of Missing Trader Intra-Community (MTIC) fraud.

According to the estimation results, GDP growth, general government surplus, IT expenditure, trade at risk, and the shares of the agriculture, communication services, and financial sectors are statistically significant at the 5% level of significance.

Furthermore, GDP, the general government balance, the share of IT expenditure in total tax administration expenditure, or the percentage of risky goods imports in GDP all have a positive relationship with the VAT Gap (Poniatowski & Bonch-Osmolovskiy & Śmietanka, 2020).

16

In another study (Zídková & Pavel, 2016), GDP, standard VAT rate, and the difference between reduced rate, the share of household consumption in GDP are analysed with a regression analysis. According to the results, the research revealed that the rise within the ratio of VAT revenue to GDP causes a discount in the VAT gap. Further findings were that if the standard VAT rate and the difference between the standard and reduced VAT rate increase, the VAT gap grows. These findings were an exciting result with a different result compared to the previously mentioned literature. According to Szczypińska, the number of VAT rates or their spread is no longer a vital determinant of the VAT gap, implying that the Council's proposal to limit the use of reduced VAT rates is difficult to justify. The reform of the tax system indicating a reduction in VAT rates, or their spread may or may not contribute to a reduction in the VAT gap. Agha and Haughton (1996) explained the same issue, stating that the standard VAT rate increases the VAT gap, as discovered and predicted by tax theory. According to Agha and Haughton's approach, the higher the VAT rate, the lower compliance with tax obligations. Similarly, the number of tax rates has a negative impact on VAT payments.

In contrast, VAT revenue increases with the length of the country's VAT operation, and smaller countries have lower levels of tax evasion. As a result of this theory, the reason is that a higher tax burden would most likely discourage people from complying with VAT. At a specific tax rate, the amount of tax saved would be large enough to outweigh the risk of punishment in the event of detection by a tax audit. Finally, the control variable – the share of household consumption in GDP – is causing the VAT gap to widen.

In another Zídková study was examining the determinants of the VAT gap. Although the VAT gap is no longer only precipitated through tax evasion, it is an indicator of this, following the application of a regression analysis of potential variables explaining the VAT gap in the 24-EU Member States in two selected years between 2002 and 2006. Data on the VAT gap was once available; two factors common for each examined year affecting the VAT gap in the surveyed states were discovered. Namely, the final consumption of households and nonprofit organisations in each state has a positive effect on the VAT gap and the share of VAT in GDP, lowering the VAT gap.

17

Furthermore, it was determined that the various identified variables that would provide an explanation for the measurement of the VAT gap were the share of the shadow economy and the standard VAT rate, which had a positive impact, and GDP per capita, the percentage of intra-community trade, final consumption of restaurant and hotel service, and the variety of VAT rates, which had a negative impact (Zídková, 2014).

Kasnauskiene & Krimisieraite (2015) examined the VAT gap in Lithuania, one of the biggest in the EU, to figure out what determinants restrict the country’s ability to mobilise revenue with the aid of the useof the MIMIC model method. According to their MIMIC model method results, two factors familiar with government consumption expenditure and inflation statistically affect the VAT gap in the long run.

This factor on the VAT gap is influenced by changes in general government consumption expenditure and, as a result, changes in inflation. Accordingly, the expansion of changes in overall government consumption expenditure determines the growth of the VAT gap. Because most of these expenditures were allocated to social protection in absolute terms, the authors believe that increasing sponsorship to the current sector determines that people with low income are less interested in working because the profit from work is insufficient to become active labour market participants. Such people spend less money on consumption, which is reducing the opportunity for business growth. In the long run, the VAT gap growth can be explained by changes in inflation growth. Individuals are forced to seek additional sources of income through other means, such as engaging in illegal activities, hiding income, and thus avoiding tax compliance to maintain a minimum equal level of consumption. In the short run, however, the two determinants, inflation and household deposits, have a statistically significant influence on the gap. The short-run results show that only two of the five causal variables statistically impact the VAT gap: inflation and household deposits. When there is an increase in inflation, the VAT gap widens. As a result, it is significant to ensure price stability in the country to maintain at least the equal stage of the VAT gap. It reduces the VAT gap as well as consumer purchasing power fluctuations.

18

According to CASE, 2012, the expected influence of the Corruption Perception Index (CPI) was negative on the VAT gap, which means that the increasing value of the corruption index (positive perception of corruption) reduces tax evasion. In terms of the results of this index within the European Union, the Nordic countries have the highest values for an average of twelve years. Finland has a value of approximately 9,51, followed by Denmark with an average value of 9,46 and Sweden with a mean value of 9,24. Conversely, the lowest measured value was reached by Romania with an average score of 3,23, Bulgaria with a value of around 3,82, and Latvia with an average score of 4,17 (Majerová, 2016).