AD ALTA
JOURNAL OF INTERDISCIPLINARY RESEARCH
TAX GAP AS A TOOL FOR MEASURING VAT EVASION IN THE EU COUNTRIES
a
ALENA ANDREJOVSKÁ,
b
VERONIKA KONEČNÁ,
c
JANA
HAKALOVÁ
a b
Faculty of Economics, Department of Finance, Technical
University of Košice, Slovak Republic
c
email:
Faculty of economics, Department of Accounting and Taxes,
VSB – Technical University of Ostrava, Czech Republic
a
alena.andreovska@tuke.sk,
b
veronika.konecna@tuke.sk,
c
jana.hakalova@vsb.cz
Acknowledgement: This research was supported by VEGA project No. 1/0430/19
Investment decision-making of investors in the context of effective corporate taxation.
Abstract: VAT is one of the most decisive tax revenues sources in the EU Member
States. Due to financial frauds and insufficient tax system, there is a billion loss of
EUR every year in the European budget. The article deals with the impact of the tax
evasion on economies of the EU Member States. By applying the top-down approach,
we observed tax gaps as a quantifier of tax evasion from 2004 to 2017. The period
around the economic crisis in 2009 was examined in more detail, as there was a sharp
change in the evolution of tax gaps. We constructed a regression model, which
examined the relationship of the tax gap and VAT tax revenues to selected
determinants of tax evasion. The results showed that tax gaps in the Member States
have been growing every year. We also found that there is an increase in tax revenues,
but tax liabilities increase to greater extent.
Keywords: tax evasion, tax gap, tax transparency, tax collection efficiency.
1 Introduction
As each tax, value-added tax (VAT) is sensitive for tax evasion
and frauds. VAT mechanism allows to economic entities and
companies many unique ways for tax abuse. At the EU level,
there is a quite common discussed tax evasion and frauds in
recent times. The estimates of tax gaps represent gross indicators
of tax revenues loss. In recent decades, the national tax reports,
and international institutions, such as FISCALIS 2020 Project,
developed several methods for estimation of tax revenue loss.
FISCALIS 2020 is coordinated by the European Commission
and contains a group of projects for tax gaps analysis. The aim is
to gather knowledge and exchange experience with existing tax
gap estimates. To find a solution, it is crucial to increase
transparency and knowledge about these tax issues within the
wider public. Generally, tax frauds, especially VAT frauds,
cause a shock in all the economic sectors in a country. They
cause widespread damage to economic and social life, mainly
serious losses of state budgetary revenues. Due to the
consequence of tax frauds, there is insufficient funding of the
areas needed to ensure a standard level of service to citizens. Tax
frauds distorts healthy competition in the business sector and
leads to illegal activities in other forms of criminal activity.
2 Literature review
VAT belongs to indirect tax and represents the core of the entire
tax system. According to the Council Directive No.
2006/112/EC of November 28
th
, 2006 on the common system of
value-added tax, VAT shall be applied to all transactions carried
out in counter value by the taxable person. VAT system has also
some advocates and opponents. In general, there is a widely
accepted opinion that VAT makes it easier to increase revenue
for the state budgets, and thereby helps to improve the efficiency
of the tax system. However, this argument is true only for a
short-term view. VAT is no longer a privilege for rich countries
only. Keen & Lockwood (2010) points out the fact that the more
open countries, the less prone to VAT. The necessary and
sufficient condition for acceptance or the change in VAT is to
reduce the marginal cost of public spending. Measuring tax
evasion is a complex process that cannot be measured with
complete accuracy. However, different methods will give us
different estimates. Hutton (2017) states that the VAT evasion is
often quantified through tax gap. To measure VAT effectiveness,
it is used c-efficiency ratio VAT performance and VAT
compliance gap. Rubin (2011) characterized the VAT gap as a
difference between theoretical tax liability set by legislative and
real tax liability of gained revenues. Gemmel (2012) found out
that the tax gap shall be measured from the macro- and
microeconomic point of view. From the macroeconomic view,
tax gap methodology are top-down or indirect methods and
usually use economic aggregates in the whole economy. The
microeconomic methodology is the bottom-up (direct) approach
and uses more specific and individual data. The top-down
approach provides a complex assessment of all tax losses
through tax gap measurement. Louvot-Runavot (2011) claims
that the top-down approach is focused on providing one estimate
based on data independent from the tax authority. The top-down
method may potentially be beneficial mainly when operating
information of tax administration is inadequate or not sufficient,
and even possibly contaminated by governance issues. However,
if national accounts data is estimated or adjusted through taxes
(for example through using risk-based audit data to estimate tax
evasion and fraud), then it will worsen formal independence.
This method is usually less time-consuming and requires
relatively little resources, while the results can be considered as
complex and time-comparable, allowing to follow the trend over
time. On the other hand, it is limited by the fact that through this
approach can be estimated only sectors in macroeconomic
statistics, and the estimation quality is dependent on the
completeness of adjustments for the shadow economy in the
national accounts. Besides that, the foreign tax evasion aspects
(such as offshore procedure, bank deposits, or foreign assets)
cannot be classified based on national accounts data. Rodrigues
(2015) claims that the top-down approach is based on the
presumption that the data source to estimate the tax gap covers
the entire tax base. Therefore, data for tax gap estimation is
usually derived from macroeconomic models or national
accounts. National accounts describe a structure and
development of the economy within the country or geographic
area (for example the EU) and describe all production activities.
There is the European System of National and Regional
Accounts (ESA 2010) in the EU countries. As European
Commission (2013) states, ESA 2010 is the newest
internationally compatible EU accounting framework for a
systematic and detailed description of an economy. From
September 2014, the data transmission from the Member States
to Eurostat is following ESA 2010 rules. ESA 2010 encourages
the Member States to ensure accuracy, reliability, consistency,
and comparability of the accounts by planning and implementing
data revisions in line with the revision policies.
Toder (2007) states that the tax gap is the difference between the
amount of theoretical VAT liability and the number of actual
VAT revenues in the concerned country and year. The VAT gap
is not only a tool for measuring tax frauds. Since it can also
include VAT paid due to tax strategies or due to insolvency of
the taxpayer, quantifying the VAT gap helps realize its size and
trend as an indicator of potential VAT evasion. Also, there could
be evidence of a higher VAT gap if the tax authorities are not
working effectively enough. For this reason, the VAT gap is
sometimes used as a measure of the efficiency of tax collection
by tax authorities that are not affected by economic or VAT rate
changes. Increasing the size of the VAT gap may indicate either
tax evasion or low efficiency of tax collection, or both.
Therefore, politicians and tax administration should pay
adequate attention to these problems.
3 Material and research methods
This contribution aims to quantify VAT evasion, which is based
on the tax gap methodology. By applying the top-down
approach, we have quantified the tax gaps in all EU Member
States from 2004 to 2017. We have examined in more detail the
period of the economic crisis as there has been a significant
change in the tax gap development at that time. To analyze VAT
gap, we used regression analysis, and the data was structured as
panel data, retrieved from the Eurostat database (2018) for the
EU-28 Member States.
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