vat fraud in intra-eu trade - etsg · 2014-08-25 · vat fraud in intra-eu trade katerina gradeva...

VAT Fraud in Intra-EU Trade

Katerina GradevaGoethe University Frankfurt ∗

August 7, 2014

Abstract

After the introduction of the EU Single Market in 1993, VAT evasion in intra-Community trade has become a serious issue. Recently it has gained considerableattention from policy-makers. This study addresses empirically the issue of VATevasion in cross-border trade in the context of intra-EU trade flows from the EU-15to seven of the new Eastern European EU member states (Czech Republic, Esto-nia, Hungary, Latvia, Lithuania, Slovak Republic and Slovenia). It estimates theresponsiveness of the trade gap to changes in the VAT rate for the time period of2004-2009 at the six-digit product level, defining the trade gap as the differencebetween the value of exports to the seven new EU member states reported by theEU-15 and the value of imports declared in the Eastern European countries of thesame product flow. This is the first study to investigate the link between the tradegap and the level of the VAT rate. The empirical evidence shows that the trade gapis positively correlated with the VAT rate in three of the seven Eastern Europeancountries. Correcting for outliers and restricting the sample to large trade flowsleads to a positive and significant correlation in five countries. In the latter casesa one-percentage-point increase in the VAT rate is associated with a 0.6% up toaround 3% increase in the trade gap.

Keywords International Trade · VAT Evasion · European Union

JEL Codes H26 · K42

∗Department of Applied Econometrics and International Economic Policy, Goethe University. RuWPostbox 46, Gruneburgplatz 1, D-60323 Frankfurt am Main. E-mail: [email protected]

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1 Introduction

Value added tax (VAT) is one of the most important sources of government revenue.Thus, a pronounced evasion might cause substantial shortage in the provision of publicservices and hinder fair competition since it entails a higher tax burden on the honest tax-payers. In addition, tax fraud is a threat to the proper functioning of the European Union(EU) internal market (Borselli, 2008). According to current estimates of the EuropeanCommission, 18% of the total VAT tax base in the EU is evaded (European Commission,2013). While VAT evasion within one country has always been an issue for the nationaltax authorities, the case of VAT fraud in intra-EU trade flows has gained importancesince the introduction of the EU Single Market. The present study aims to contributeto the growing literature on the problem of VAT evasion in intra-EU trade. The topic iscurrently extensively debated within the EU, with the EU Commission taking a leadingrole and initiating action plans and additional procedures and instruments to combat thistype of fraud (EU Commission, 2012; Borselli, 2008). The subject is of high relevance alsowith respect to the recent Eastern EU enlargements and the potentially growing numberof member states in the future which leads to an increase in the volume of intra-EU tradeand thus, to a bigger scope of VAT evasion.

In general, VAT evasion might occur in every international trade flow. Each importerhas to pay the applied customs duties and VAT on the imported goods upon their arrivalat the destination border. Hence, even in the absence of tariffs, which is the case withtrade flows between countries that have a free trade agreement (FTA) or are members ofa customs union (such as the EU), importers have an incentive to misreport their tradein order to evade VAT. The EU presents a specific case because, since the introductionof the EU Single Market, it is particularly vulnerable to VAT fraud in trade flows acrossits member countries. Beginning in 1993, the EU Single Market has led to the completeabolishment of all customs procedures at the borders across EU member states (freemovement of goods) so that the VAT on intra-EU traded goods could not be collectedanymore at the border before entering the destination country. Instead, the so-called“transitional” VAT regime, incorporating the “destination principle” in taxation, wasestablished and is currently still applied (Baldwin, 2007; Keen and Smith, 2006). Thetransitional VAT regime implies that intra-EU trade is VAT-free; the importer receivesthe goods VAT-free from the exporter, charges the VAT in the importing country whenselling the products to the customers and remits the collected VAT to the national tax au-thorities. Thus, the transitional regime breaks the VAT chain at a very vulnerable stage;all intra-EU trade flows are transported VAT-free, which leaves potential for massiveVAT fraud (Baldwin, 2007; Keen and Smith, 2006). A prominent case of VAT evasion inintra-EU trade flows is the so-called “Missing Trader Intra-Community” (MTIC) fraud,which has gained increased attention from policy-makers and tax authorities in the recentyears. MTIC fraud presents the extreme case, where the importing firm does not justunderreport the correct value of its imports but rather disappears completely withouttransferring any VAT to the tax authorities, therefore the “missing trader”.

This study addresses empirically the issue of VAT evasion in cross-border trade basedon the case of intra-EU trade flows between the EU-151 and seven of the new EU member

1Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Nether-lands, Portugal, Spain, Sweden, United Kingdon (UK).

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states (The Czech Republic, Estonia, Hungary, Latvia, Lithuania, The Slovak Republicand Slovenia, hereafter referred to as EU-7) for the time period of 2004-2009. The tradegap (or “missing” trade) is defined as the difference in each product-specific trade flowbetween the declared export value in the country of origin (EU-15) and the reportedimport value in the destination country (EU-7). I will then estimate the relationshipbetween the trade gap and the level of the VAT rate in the importing (EU-7) country atthe six-digit product level. Thus, the empirical analysis will consider all levels of under-reporting of imports and not only the extreme case of MTIC fraud. In all EU-7 countriesa standard VAT rate is applied to the majority of products; however, a reduced VATrate exists for certain goods. The implementation of a reduced VAT rate, its level aswell as the standard VAT rate vary across six-digit products and over the specified timeperiod of 2004-2009. Currently, the standard VAT rate in the countries included in thesample ranges up to 27%. This is a substantial amount of taxes and thus potentially anincentive to underreport imports in order not to remit the collected VAT fully to the taxauthorities. Hence, the estimation strategy relies on the variation of the VAT rates acrossproducts over time to identify the responsiveness of the trade gap to changes in the VATrate.

Using the same empirical approach, various empirical studies have shown that highertariff rates are associated with a higher magnitude of missing trade, meaning that highercustoms duties are correlated with more misreporting of imports (Fisman and Wei, 2004;Javorcik and Narciso, 2008, 2013; Mishra, Subramanian, and Topalova, 2008; Jean andMitaritonna, 2010; Gradeva, 2014). Fisman and Wei (2004) estimate the responsivenessof the trade gap to a one-percentage-point increase in the tariff rate to be around 3%,whereas the other studies report a lower magnitude of the correlation between trade gapand tariff rate. Javorcik and Narciso (2008) investigate trade flows from Germany to tenEastern European countries (including six of the EU-7 countries) and report a positivecorrelation between the trade gap and the tariff rate; a one-percentage point increase inthe customs duty is associated with 0.4% to 1.7% increase in the trade gap. Gradeva(2014) examines the issue of tariff evasion in trade flows from the EU-15 to the ten East-ern European countries in the context of their EU accession in 2004 and 2007. The resultsof the analysis point towards a positive relationship between the trade gap and the tariffrate in the majority of countries, which is more pronounced when restricting the sampleto manufacturing products.

However, the potential correlation between the trade gap and the VAT rate in theimporting country has so far been neglected in research. With a general trend towardslower tariff rates and higher number of FTAs, VAT rates might play a key role in ex-plaining the presence of a trade gap. The present paper aims to fill this gap. This isthe first study, which examines whether higher VAT rates in the importing country areassociated with higher underreporting of imports. The pure existence of a discrepancybetween the export and import data of the same product-specific trade flow cannot be,however, interpreted as a sign of evasion because of possible measurement error in thetrade data due to timing, exchange rate or incorrect reporting issues. Hence, only asystematic correlation between the trade gap and the VAT rate will be interpreted as ev-idence for VAT evasion. Also, it is a standard procedure in international trade statisticsto report imports including the cost of freight and insurance additional to the value ofthe product. So, in the absence of evasion and measurement issues, the declared value of

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exports should be lower than the import value.

The results show that a positive correlation between the level of the VAT rate andthe trade gap exists in three of the seven countries in the sample, namely in Estonia,the Slovak Republic and Slovenia. The relationship ranges from a one-percentage pointincrease in the VAT rate associated with 1% increase in the trade gap in Slovenia to morethan 3% in Estonia and the Slovak Republic. The correlation is robust to correction foroutliers in the sample. Restricting the sample only to trade flows with a value which ishigher than 50,000 US dollars and correcting for outliers as ways to avoid measurementerror in the data leads to a significant relationship between the VAT rate and the tradegap, in addition to the other three countries, also in the Czech Republic and Hungary.

The study by Allingham and Sandmo (1972) is one of the first theoretical contribu-tions on the topic of tax evasion. According to their model, increasing the probability ofdetecting evasion and higher penalty rate lead to less tax evasion. However, the modelcannot predict unambiguously the effect of changes in the tax rate on tax evasion; therelationship depends on the risk aversion of taxpayers. Assuming decreasing absoluterisk aversion of the taxpayer, tax evasion becomes more profitable at the margin whenthe tax rate increases (substitution effect) but a higher tax rate reduces simultaneouslythe taxpayer’s wealth (income effect). Yitzhaki (1974) shows that when the penalty ratedepends on the evaded tax, and not on the undeclared income as in the original model byAllingham and Sandmo (1972), a higher tax rate leads to less evaded income (assumingdecreasing absolute risk aversion). Andreoni, Erard, and Feinstein (1998) discuss thepuzzling fact that taxpayers are by far more honest and actual tax compliance is higherthan the Allingham-Sandmo model predicts (evidence based on US tax data). The au-thors present evidence that tax moral, perception of fairness and satisfaction with theprovision of public goods might explain the behavior of taxpayers. Andreoni, Erard, andFeinstein (1998) and Slemrod and Yitzhaki (2002) review the various augmentations ofthe original Allingham-Sandmo model and conclude that the empirical evidence is ratherscarce and controversial, especially for other countries than the USA. In a more recentoverview Slemrod (2007) discusses in particular the topic of VAT evasion, which doesnot apply to the USA (no VAT implemented) but is of high relevance to other developedcountries as the EU member states.

Several studies and national tax authorities estimate the magnitude of VAT fraudusing a “top-down” approach based on national accounts data and input-output ta-bles (Reckon LLP, 2009; Woon Nam, Parsche, and Schaden, 2001; Gebauer, Nam, andParsche, 2005; Christie and Holzner, 2006; Agha and Haughton, 1996; HM Revenue &Customs, 2006, 2013). They apply a similar approach to estimate the “VAT gap”, thedifference between a theoretical VAT liability and the total VAT receipts. The theoreticalVAT liability is calculated on the basis of the categories of expenditure which contributeto the VAT base. The use of this top-down approach incorporates various assumptionsin order to estimate the theoretical VAT liability. These include estimating the propor-tion of intermediate consumption on which VAT is not recoverable (especially regardingthe financial, education and rental activities sectors), the size of adjustments needed forsmall businesses for which special tax schemes apply, and the correct matching of VATrates to the product groups, which sometimes might be influenced by the judgement ofthe authors themselves (Reckon LLP, 2009). However, very few of the studies reveal

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in detail the exact assumptions in the methodological part. So, although all of thememploy a similar top-down approach measuring the VAT gap, their results would not benecessarily comparable. It should be noted here that besides fraud the VAT gap might beevoked also by legal tax avoidance, unpaid VAT due to insolvencies, incompleteneess orinaccuracy of the national accounts data (Reckon LLP, 2009). In contrast to all studiesthat calculate the VAT gap, this paper examines only one possible source of VAT fraud,namely VAT evasion in intra-EU trade flows.

Measuring the VAT gap with a similar top-down approach as previously described,Agha and Haughton (1996) estimate the responsiveness of the VAT gap to the averagestandard VAT rate for a cross-section of 17 OECD countries for 1987. The results showthat a one-percentage-point increase in the average VAT rate is associated with a decreasein the tax compliance rate by 2.7 percentage points. The complexity of the applied VATscheme matters also for the evasion rate; an additional VAT rate lowers the compliancerate by 7.0 percentage points. This substantial effect should, however, be interpreted withcaution since the number of VAT rates per country is limited and the empirical specifica-tion of the study does not account for the size of the tax base of each VAT rate. Christieand Holzner (2006) come to a similar conclusion when estimating the correlation betweenthe VAT gap and the average weighted VAT rate for all current EU member states2 andTurkey for the time period from 2000 to 2003 in an empirical framework based on theAllingham-Sandmo model. Although the relationship is much lower, in their study ahigher average VAT rate is also associated with a lower tax compliance rate. In addition,the authors conclude that the quality of the legal system as well as the satisfaction withpublic services matter for the VAT compliance rate.

Reckon LLP (2009) estimates the VAT gap development in the EU member states(except Cyprus) for the period of 2000 to 2006 on behalf of the EU Commission (DGTaxation and Customs Union). The average VAT gap for the EU in this time periodranges from roughly 91 to 113 EUR billion, which represents 12% to 14% of the theo-retical VAT liability. The results of the study suggest that the VAT gap has decreasedsteadily in Slovenia (from 16% in 2000 to 4% in 2006) whereas the other EU-7 countriesdo not report a clear trend. The VAT gap in 2006 is measured to amount to 28% forthe Slovak Republic, 23% for Hungary, 22% for Latvia and Lithuania and 18% for theCzech Republic. The estimate for Estonia has increased from 12% in 2000 to 21% in2004 and decreased afterwards to 8% in 2006. The descriptive statistics of the VAT gapin the study by Reckon LLP (2009) do not show a direct connection to the developmentof the trade gap used in this study. While according to Reckon LLP (2009) Estonia andSlovenia have the lowest VAT gaps in 2005 and 2006 among the EU-7 countries, these aretwo of the countries with the highest trade gaps and a robust positive correlation betweenthe trade gap and the VAT rate. The empirical analysis of the study by Reckon LLP(2009) follows Christie and Holzner (2006) and examines the determinants of the VATgap over the pooled sample of all EU member states (except for Cyprus and Malta) forthe time period of 2000-2006. The study presents mixed evidence about the relationshipbetween the VAT gap and the standard VAT rate. The results contradict the findingsof Christie and Holzner (2006): the positive and significant correlation between the VAT

2Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France,Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland,Portugal, Romania, Slovak Republic, Slovenia, Spain, Sweden, UK.

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gap and the VAT rate turns to be negative once controlling for possible autocorrelationand heteroskedasticity. Thus, a higher VAT standard rate is associated with a smallerVAT gap, which is the predicted effect in the model by Yitzhaki (1974). The study pro-vides some evidence that the VAT gap decreases with a longer EU membership.

Woon Nam, Parsche, and Schaden (2001) calculate the VAT gap rates for ten of theEU member states for the years 1994, 1995 and 1996 (due to data issues for France, Italyand the UK, the estimates for these three countries are for the years 1991, 1992 and1993). The average ratio of VAT non-compliance over the respective three years rangesfrom 2.4% in the Netherlands to 34.5% in Italy. For Italy, Greece, Spain and Belgiumthe share of the VAT gap of the hypothetical VAT tax base amounts to around 20%or more while in the Netherlands, the UK, Denmark and Germany the average share isless than 5%. In a follow-up study Gebauer, Nam, and Parsche (2005) estimate the VATevasion ratio for Germany for each year between 1994 and 2001. Although not constantlyincreasing, the VAT non-compliance ratio is 9% higher in 2001 than in 1994 and amountsto 9.6% of the total VAT liability.

The UK tax authority, HM Revenue & Customs (HMRC), is one of the most activenational tax authorities in the fight against VAT evasion. For more than a decade ithas been issuing a report on “Measuring Indirect Tax Losses” (HM Revenue & Customs,2006). HMRC uses a top-down approach to estimate the share of the VAT gap out of thetheoretical VAT liability. Overall, for the financial years between 2001-2002 and 2011-2012, the VAT gap ranges between 10% and 16% of the total hypothetical liability, beingstable around 10.5% in the last two periods, 2010-2011 and 2011-2012 (HM Revenue &Customs, 2006, 2013). In a joint study of the HMRC and the Office for National StatisticsRuffles, Tily, Caplan, and Tudor (2003) investigate the extent of the MTIC fraud in theUK and its impact on trade statistics and balance of payments. However, the authorsdo not explain the methodology used to calculate the amount of MTIC fraud, referringto confidentiality issues. A massive MTIC fraud would bias the official trade statisticswith the other EU member states because the import data and the trade deficit wouldbe understated. Ruffles, Tily, Caplan, and Tudor (2003) apply their adjustment methodonly to certain transactions involving products that present an interest for fraudsters(mobile phones and computer components). The authors calculate the necessary adjust-ments for the effect of MTIC fraud on UK imports from the rest of the EU for the years1999-2002 and show that the impact of MTIC fraud has increased within the four-yearperiod: MTIC fraud amounted to 0.7% of the total imports from the EU in 1999 andaround 4.0% in 2002. Ruffles, Tily, Caplan, and Tudor (2003) argue that MTIC fraud ispartly responsible for the increasing asymmetries in the trade figures between EU mem-ber states. After 1993, when the EU Single Market was introduced and the opportunityfor massive MTIC fraud arose, the discrepancy between the UK import data and theexport figures of the other EU member countries to the UK has continuously increased.The present study builds on this finding since it examines the extent to which the levelof the VAT rate of a given product can explain the existence of a mismatch in the mirrortrade statistics.

Several studies offer empirical evidence on the topic of tax morale and tax evasionin the Eastern European EU countries based on survey data (Torgler, 2004, 2011; Tor-gler, Demir, Macintyre, and Schaffner, 2008; Hanousek and Palda, 2008; Gerxhani, 2004).

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High perception of corruption, high number of evaders and a malfunctioning tax admin-istration might lower the public trust in state officials and with it, the tax morale inthe society, which in turn leads to more tax evasion (Torgler, 2004, 2011; Torgler, Demir,Macintyre, and Schaffner, 2008). The empirical evidence from the EVS shows that duringthe accession period and the first years as EU members there has been some improve-ment in the tax morale in some countries (Gradeva, 2014). However, this phenomenonis not observed in all countries. Corruption and a high acceptance of bribes still remainimportant issues to tackle in these states.

Hereafter, the study is structured as follows: The next section describes in more detailthe specific features of the EU Single Market with regard to VAT collection and explainsthe reasons for the increased probability of VAT fraud in intra-EU trade flows after 1993.Section 3 reviews the data used in the empirical analysis and possible data quality issues.Section 4 presents the empirical strategy of the study. Section 5 discusses the results andthe last section offers conclusions.

2 The EU Single Market and VAT fraud schemes

Before the introduction of the EU Single Market in 1993 the EU states had enjoyedfull national VAT authority, which should have changed afterwards. However, the mem-ber countries could not agree upon a common VAT rate and a uniform VAT regime forthe whole EU. Hence, since the differences across the national legislation were too big, a“transitional” VAT regime has been adopted within the EU and is still implemented untilpresent day. Even though the VAT rates are not fully harmonized, the common EU VATsystem sets the general framework, which has to be applied in all member states in orderto ensure “neutrality in competition, such that within the territory of each Member Statesimilar goods and services bear the same tax burden,...” (The Council of the EuropeanUnion, 2006). With respect to the national VAT rates, the EU members and the EUCommission have agreed upon a minimum standard VAT rate of 15% and a minimumreduced VAT rate of 5% as well as the product categories for which a reduced VAT rateor exemptions from VAT can apply (The Council of the European Union, 2006). Theproduct categories, which can be taxed with a reduced VAT rate, include broadly definedfoodstuffs, pharmaceutical products, medical equipment and books.

Importers had presumably, already in the pre-1993 system, incentives to underreporttheir imports in order to evade VAT (tariffs had already been abolished on intra-EUtrade flows). However, after the introduction of the EU Single Market some of the keyfeatures of the VAT system have changed so that VAT evasion has become a bigger issuein intra-Community trade. After 1993, all border controls had been abolished so the VATon imported goods could no longer be collected before entering the destination country.Instead, now the importing firm receives the VAT on the imported products after sellingthem to its customers and has the obligation to remit the collected VAT to the nationaltax authorities. In addition, the “destination” principle, as in most international tradeflows, applies in business-to-business relations. This means that exports are VAT-freeso that the importing firm collects from its customers the VAT on the whole productionchain and not only on the own value added. The main argument for the destinationprinciple is that there are no incentives for delocation of industries to low-tax countries

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because all supplies are taxed with the same VAT rate, independent of whether they areproduced in the home country or imported (Baldwin, 2007). However, there are sev-eral major objections against the transitional VAT regime. First, the implementation ofdifferent VAT regulations for acquisitions from national or foreign suppliers leads to anasymmetry and high compliance costs. Second, the transitional regime breaks the VATchain and leaves opportunities for massive VAT fraud. Third, the transitional regime setsincentives for price arbitrage to cross-border shoppers; however, this issue is regarded asone of lesser importance (Baldwin, 2007).

VAT fraud can take place through different channels: underreported sales (“off thebooks” sales), no firm registration to the tax authorities (“ghost” firms), misclassificationof products in the case when a firm sells several goods taxed at different VAT rates, falseclaims for credit based on overstated VAT paid on inputs and imported products whichare not brought into tax (Keen and Smith, 2006). The latter mechanism of VAT fraudis of most interest for this study. Two simplified examples show the differences in theVAT collection between domestic production and a production chain which involve im-porting goods from other EU members and the incentives for VAT fraud in the latter case.

Figure 1 presents a very simplified example of domestic production and sale of cellphones in Slovenia, where currently a 20% VAT standard rate is applied. A supplier sellsinputs for cell phones with a value of 800,000 EUR to firm A and charges 160,000 EURVAT (20% of the value of the inputs). Thus, firm A pays in total 960,000 EUR (inputs’value plus VAT) to its supplier. Using the inputs Firm A produces cell phones and sellsthem to firm B for 1 million EUR, collecting additionally from company B VAT at theamount of 200,000 EUR. The net VAT liability of firm A to the Slovenian tax authoritiesis 40,000 EUR (200,000 EUR - 160,000 EUR) since each firm has to pay VAT only on itsown value added. Firm B buys the cell phones from firm A for 1.2 million EUR, includingVAT, and resells them to the final customer for 1.3 million EUR plus 260,000 EUR VAT.So, company B has to transfer 60,000 EUR to the tax authorities. That is the differencebetween the collected VAT on the sold products and the VAT that the company has paidalready for the products. In this case, the maximum VAT that company B can evade arethe 60,000 EUR VAT due (this would be the extreme case where firm B does not reportany disposals and sells all products “off the books”).

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Figure 1: VAT liability on domestically produced and sold products (the country ofSlovenia as an example).

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Figure 2 shows the case where the cell phones are not produced domestically but im-ported from another EU member state, in this case Austria, where the standard VAT rateis currently also 20%. The first step in the production is similar to the previous example,only it takes place abroad. The major difference is the disposal of the cell phones fromfirm A to firm B. Because firm A sells the cell phones now to a company abroad, it doesnot charge any VAT upon the 1 million EUR valued products. Instead, firm A sells thecell phones VAT-free to company B and receives from the Austrian tax authorities theVAT that it has already paid on its inputs (160,000 EUR). Firm B in Slovenia pays nowonly 1 million EUR for the cell phones (without the 200,000 EUR VAT as in Figure 1 )and resells them again for 1.3 million EUR plus 260,000 EUR VAT to the final customers.In this case, firm B owes the Slovenian tax authority 260,000 EUR since it has not madeany VAT payments in previous production stages which can be deducted (the importedproducts are VAT-free). Thus, the maximum VAT that firm B can now evade is the VATon the whole production chain in the amount of 260,000 EUR, which is substantiallyhigher than in the case shown in Figure 1.

Figure 2: VAT liability on foreign produced and domestically sold products.

The second example shows the increased opportunity of evading VAT in intra-EUflows after the introduction of the EU Single Market when the importing firm is itselfresponsible for remitting the collected VAT to the tax authorities. The widely discussedMTIC fraud is similar to a situation as in Figure 2 but instead of just underreporting itsimports firm B goes bankrupt (the missing trader) before transferring any VAT to thetax authorities. This would be the extreme case where firm B evades completely the VATon the whole production chain (Baldwin, 2007; Keen and Smith, 2006; Borselli, 2008).

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Another fraud scheme that has recently gained increasing attention among policy-makersis the so-called “carousel fraud” (Baldwin, 2007; Keen and Smith, 2006; Borselli, 2008).The carousel fraud includes a MTIC situation, where the importing firm (Firm B in Fig-ure 2) sells the goods to another firm, firm C, in Slovenia and goes bankrupt. Firm C, notnecessarily involved in the fraud scheme, buys the products from firm B and resells themto firm D in Slovenia. Firm D exports the products back to Austia or another EU coun-try, thus collecting the VAT that the missing trader (Firm B) should have remitted tothe Slovenian tax authorities. The products can be then circulated around several times,including also exporting to a non-EU member country which makes it more difficult tobe tracked and re-exporting the goods back to the EU, therefore “carousel fraud”. Inmost cases all firms are involved in the criminal acitivity but there can be also “honest”companies as “buffers” (for example firm C) in order to complicate the fraud scheme.Preferred products for these types of frauds are goods with high value but low weightlike computer chips or cell phones (Baldwin, 2007). This paper considers in the empiricalanalysis the trade gap, the difference between the export and import value of the sameproduct-specific trade flow. MTIC or carousel fraud schemes might be the reasons forthe existence of the trade gap but the asymmetry in the mirror trade statistics might becaused also by only partly evading VAT through underreporting of imports. Thus, it willnot be possible to differentiate in the empirical analysis across the different types of VATevasion.

3 Data description

The UN COMTRADE database of the United Nations Statistical Division, provided bythe WITS database, offers the information on bilateral trade flows between the EU-7 andthe EU-15 countries for the time period of 2004-2009. The UN COMTRADE databasecontains two figures belonging to the same trade flow: the value of a product that isdeclared in each EU-15 country to be exported to each of the EU-7 countries (hereafterreferred to as “exports”) and the reported import value of the same product in the EU-7countries (hereafter referred to as “imports”). Thus, each trade flow is registered twice,once when leaving the country of origin and secondly when arriving to the destinationcountry. The data are collected by the national agencies and then transmitted to theUnited Nations Statistical Division, which converts the values into US dollars, if neces-sary, to make the figures comparable across countries. Apart from the costs of freightand insurance, there should be no other difference between the export and import valueof the same trade flow. In international trade statistics, exports are reported as f.o.b.(free on board) and imports as c.i.f. (including the costs of insurance and freight). Thus,in the absence of measurement error or evasion the import value should be higher thanthe corresponding export value. Trade flows in the sample are declared according to theHarmonized Commodity Description and Coding System (HS) at the six-digit productlevel which is the highest available disaggregated level. The trade data are classified ac-cording to the initial HS product classification, HS 1988/92. One issue in the trade datafor Hungary concerns the implementation of a threshold of 1,000 US dollars per prod-uct category for a given year and partner country below which no imports are reported.Therefore, all exports to Hungary with a value below 1,000 US dollars will be excludedfrom the empirical analysis in order not to bias the results.

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As previously mentioned, since the introduction of the EU Single Market the intra-EUtrade data are collected not on the basis of customs declarations but through the Intra-stat system (European Council and European Parlament, 2004; European Commission,2004). Each firm, which is importing to/exporting from another company within the EU,has to declare its trade within the Intrastat system and the information is then submitteddirectly to the national statistical offices. The latter process the data and transmit it toother statistical databases. Small firms are the only exception from the regulation sincethey do not have to fill out the Instrastat declarations in order to have lower administra-tive burden. The threshold for defining the firms which do not have to comply with thegeneral rule is set each year and for each country in a way that the collected Intrastatdeclarations cover 97% of all exports and 95% of all imports (European Council and Eu-ropean Parlament, 2004). The national statistical offices gather information on the firmswhich remain below the threshold based on their VAT declarations and estimates fromprevious years.

There is no available database that offers information on the VAT rates at the six-digit product level for the EU member countries. The data in the present study aregathered with the help of the national VAT legislation of the EU-7 countries, which hasbeen in force in the time period of 2004-2009 (Czech Republic Government, 2004; EstoniaGovernment, 2010; Hungary Government, 2004, 2009, 2006; Latvia Government, 2010;Lithuania Government, 2006, 2009; Slovak Republic Government, 2008; Slovenia Govern-ment, 2002; EU Commission, 2014). The public availability of a translated version ofthe VAT laws is the reason why the sample does not include all Eastern European EUmembers.3 Some of the VAT laws define in a very detailed way the product codes whichare taxed with a reduced VAT rate (for example the Slovak Republic and Hungary). Forthe majority of the countries only the product description is available which has to bematched with the correct product codes. The matching is done as rigorously as possibleand equally for all countries, however, there is still potential for some errors in the VATdata. Product groups, where it is not possible to identify whether all goods included ina certain six-digit product category are taxed with the same VAT rate, are defined as“mixed” product codes and will be not considered in the empirical analysis. An examplefor such a “mixed” product is the six-digit product code 853180 “Other electronic soundor visual signalling apparatus”, which in the case of the Slovak Republic is taxed withthe standard VAT rate except when the final customers are persons with hearing and/orvisual disability, then the reduced VAT rate applies.

The VAT rates applied in the EU-7 countries in the sample period 2004-2009 areshown in Table 1. In the years when the VAT rate has changed during the year, the VATrate for the respective year is calculated as the weighted average of the two different ratesaccording to the number of months they have been applied. The implementation of areduced VAT rate is decided by the national government. The column “Reduced rate 1”of Table 1 reveals that all countries in the sample have applied at least one reduced rateduring the time period of 2004-2009, with Hungary and Lithuania being the exceptionswhere there has been also a second reduced rate (“Reduced rate 2”). There has been

3VAT data for Poland and Romania are missing. Bulgaria is not part of the sample because thestandard VAT rate of 20% has not been changed during the time period and no reduced rate has beenimplemented.

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at least one change in the VAT rates in each country with the only exception of Slove-nia where the VAT rates have remained the same. In the majority of countries (CzechRepublic, Estonia, Hungary and Latvia) both the standard and reduced VAT rates havechanged during the sample period, whereas in Lithuania only the standard rate and in theSlovak Republic only the reduced rate vary in the years between 2004 and 2009. Overall,the VAT rates show rather little variation, which should be considered when analyzingthe results of the empirical analysis.

Table 1: VAT rates between 2004 and 2009.

Country Standard rate Reduced rate 1 Reduced rate 2 Implementation period

Czech Republic 22 5 - 01.01.2004-30.04.2004Czech Republic 19 5 - 01.05.2004-31.12.2007Czech Republic 19 9 - 01.01.2008-31.12.2009Estonia 18 5 - 01.01.2004-31.12.2008Estonia 18 9 - 01.01.2009-30.06.2009Estonia 20 9 - 01.07.2009-31.12.2009Hungary 25 5 15 01.01.2004-31.12.2005Hungary 20 5 15 01.01.2006-31.08.2006Hungary 20 5 - 01.09.2006-30.06.2009Hungary 25 5 18 01.07.2009-31.12.2009Latvia 18 9 - 01.01.2004-30.04.2004Latvia 18 5 - 01.05.2004-31.12.2008Latvia 21 10 - 01.01.2009-31.12.2009Lithuania 18 5 9 01.01.2004-31.12.2008Lithuania 19 5 9 01.01.2009-31.08.2009Lithuania 21 5 9 01.09.2009-31.12.2009Slovak Republic 19 - - 01.01.2004-31.12.2006Slovak Republic 19 10 - 01.01.2007-31.12.2009Slovenia 20 8.5 - 01.01.2004-31.12.2009

Applied VAT rates in the EU-7 countries in the sample period 2004-2009.Source: EU Commission (2014)

4 Estimation strategy

Following the specification of Fisman and Wei (2004), the trade gap is defined for eachof the EU-7 countries separately as:

TradeGapcpt = lnExportscpt − lnImportscpt (1)

where c stands for the partner country (EU-15), p for a six-digit HS product code andt for year (2004-2009). Thus, the trade gap is equal to the difference in the log-value ofexports and the log-value of imports of the same product-specific trade flow. Accordingto Equation 1, the trade gap is calculated only for trade flows for which the export andthe import values are non-missing and non-zero. Equation 1 implies that in the absence

13

of evasion and measurement errors the trade gap should be negative since imports aredeclared including the costs of freight and insurance additionally to the export value.Therefore, the higher the costs of insurance and freight are, the higher the trade gapshould be in absolute terms.

Gradeva (2014) discusses in detail the reasons, other than evasion, for the existence ofa discrepancy between the export and import value of the same trade flow and the caseof asymmetries in mirror trade statistics within the EU in particular. Incorrect speci-fication of the exporting and importing firm, respectively of the countries of origin anddestination, is one of the most common mistakes in trade documents, especially in thecases of transit trade or trade involving export-processing zones (De Wulf, 1981; Yeats,1995). Another explanation for the trade gap is a mismatch in the timing informationfor exports which are dispatched at the end of a certain year but the imports arrive inthe beginning of the following year. Additionally, differences in the export and importvalues might arise due to different currencies and the fluctuations of their exchange ratesto the US dollar.

Ruffles, Tily, Caplan, and Tudor (2003), Loschky (2006), Koufen (2001) and Krockow(2007) consider the specific sources of the existing asymmetries in intra-EU trade flows.The authors see the main reasons in the incorrect identification of the product code andof the origin and destination country. Incorrect time mapping and exchange rate fluctu-ations also play a role. A specific issue of the implementation of the Intrastat system isthe exclusion for small firms. Since the thresholds for submitting regular Intrastat decla-rations vary across EU members and time, it is possible to have only one of the exportingand importing firms falling into the category below the threshold. Also, the national sta-tistical offices of the EU members do not apply the same method for estimating the tradeflows of firms below the reporting threshold which might lead to differences in the results.

Ruffles, Tily, Caplan, and Tudor (2003) and Loschky (2006) examine the develop-ment of the trade asymmetries for the UK and Germany respectively, particularly afterthe introduction of the EU Single Market and the change in the reporting system. WhileLoschky (2006) sees the German bilateral trade asymmetries with Italy, the UK and theCzech Republic descreasing after the replacement of the customs declarations with theIntrastat system, Ruffles, Tily, Caplan, and Tudor (2003) present evidence that the UKmissing trade with the other EU member states has been increasing since 1993. Loschky(2006) argues that the improvements in the trade data are caused by less corruption atthe customs since the importers no longer have any interaction with the customs officialsand submit their Intrastat declarations directly to the national statistical office. Anotherreason is a better coordination across the national statistical offices. On the other hand,Ruffles, Tily, Caplan, and Tudor (2003) attribute the higher UK trade gap with the otherEU members to the increased opportunities for VAT evasion in intra-EU trade flows,particularly in the form of MTIC or carousel fraud.

To conclude, one cannot interpret the pure existence of the trade gap as a proof ofVAT evasion in the trade flows between the EU-7 and the EU-15 countries because ofthe various possible data quality issues or of a discrepancy in the export and import datadue to a random measurement error. Thus, analyzing the development of the trade gapon the basis of descriptive statistics alone has a limited informative value with respect

14

to VAT evasion. It is not possible to disentangle the “real” trade gap from the noise inthe data. Therefore, the empirical analysis in this study is concentrated on the questionwhether there is a systematic correlation between the level of the VAT rate and the tradegap. Assuming that the measurement error is random with respect to the VAT rate, sucha systematic correlation may not exist in the cases where measurement error causes theexistence of a trade gap.

Defining the trade gap as Equation 1 does, the main specification in the empiricalanalysis, which is estimated for each EU-7 country separately, would be as follows :

lnExportscpt − lnImportscpt = TradeGapcpt = β0 + β1V ATpt + αt + γc + δp + εcpt (2)

where c stands for the partner country (EU-15), p for each six-digit HS product codeand t for year (2004-2009). Equation 2 estimates the responsiveness of the trade gap tochanges in the VAT rate for trade flows between the EU-7 and the EU-15 states for eachEU-7 country separately and tests whether there is a systematic and significant correla-tion between changes in the VAT rate and the trade gap. The estimated coefficient onthe VAT rate should be positive and significant if a higher VAT rate is associated withmore missing trade. The model exploits the variation of the VAT rate across products(standard vs. reduced VAT rate) and time within each EU-7 country. The VAT rateis the same for all products within the same product code, independently of the coun-try of origin so the VAT rate does not vary over the partner countries. The preferredspecification of the model includes year, partner country and product fixed effects. Theyear fixed effects control for particular changes in a certain year that might influence thetrade gap such as a reform in the administration or changes in the reporting. The part-ner and product fixed effects account for any partner country or product characteristicswhich are systematically correlated with the trade gap. Because the VAT rate does notchange regularly and there is little variation at the six-digit product level, the productfixed effects, which are included, will be at the four-digit level. Another possible spec-ification might include partner country-year fixed effects in order to control for specifictime trends of the partner countries. However, the results of this specification are similarto including separate year and partner country fixed effects, so they will be not presented.

Equation 2 assumes that the VAT rate changes exogeneously with respect to the tradegap. The level of the VAT rate is a government decision, thus endogenously set, and partof the tax system in a country. However, the VAT revenues are generated mostly throughthe domestic market and to a lesser extent through international trade. Therefore, it isunlikely that when considering a change in the VAT legislation the government wouldtake into account the trade gap at the six-digit product level.

5 Results

5.1 Descriptive statistics

The descriptive statistics of the trade gap for the products subject to a standard or re-duced VAT rate are shown in Table 2 (the table includes only the product codes for which

15

the VAT rate can be identified, thus excluding the mixed categories). These observationspresent the sample used in the empirical analysis afterwards. The mean and the mediantrade gap for the products with a standard VAT rate are negative only for Latvia andLithuania. Considering the products with a reduced VAT rate, the median trade gap isnegative for four countries, namely Estonia, Hungary, Lithuania and the Slovak Repub-lic. As Table 2 demonstrates, the trade gap (mean and median) is substantially higherfor Estonia, the Slovak Republic and Slovenia compared to the other countries in thesample. In the majority of countries the trade gap is on average smaller for the productstaxed with a reduced VAT rate. This observation supports the hypothesis that a higherVAT rate is associated with a higher trade gap. The last column of Table 2 shows thedifference in the mean trade gaps and it is, indeed, positive and significant for Estonia,Hungary, the Slovak Republic and Slovenia, meaning that the trade gap of the productstaxed with the standard VAT rate is significantly higher on average than the one of theproduct categories taxed with the reduced VAT rate. The only exception is Lithuania,where the difference in the mean values goes in the opposite direction.

Table 3 shows the descriptive statistics of the trade gap per EU-7 country for the twotypes of product codes, those with identified VAT rate and the mixed categories, whichare excluded from the empirical analysis. Considering the total number of observations,it is obvious that the mixed categories are only a small share of all product codes. Similarto the descriptive statistics of the trade gap for products taxed with the standard VATrate (Table 2) are the mean and the median of the trade gap in the sample without themixed product groups negative only for Latvia and Lithuania. The highest mean tradegap for both types of product groups is again reported for Estonia, the Slovak Republicand Slovenia; the median values are lower but still high, especially for Estonia and theSlovak Republic. The mixed categories offer potentially more opportunities to evade VATsince they include both products with a standard and reduced VAT rate but with thesame six-digit product code. The last column presents the difference in the means of thetrade gap between the two types of product categories. If the mixed product codes aremore prone to VAT evasion, this would mean that the difference in the means should benegative. The evidence is rather mixed; the difference is negative and highly significantin the cases of Estonia and the Slovak Republic (the countries with the highest tradegaps) but positive and significant for the Czech Republic and Hungary. It does not seemthat there is any clear pattern along this differentiation of product groups, at least onthe basis of the descriptive statistics.

5.2 Baseline results

Table 4 presents the baseline results of estimating Equation 2. The first panel of thetable includes only year fixed effects, the second one adds also partner country fixed ef-fects and the third panel contains all three types of fixed effects (year, partner countryand product at the four-digit level). The estimates respond to the inclusion of the part-ner country fixed effect, which points towards a systematic correlation between partnercountry characteristics and the trade gap. Therefore, the first panel will not be reviewedfurther and the discussion will concentrate on the second panel. The point estimates forEstonia and the Slovak Republic show that a one-percentage-point increase in the VATrate is associated with more than 3% increase in the trade gap, for the Slovak Republic

16

Tab

le2:

Des

crip

tive

stat

isti

cs.

Sta

ndar

dra

teR

educe

dra

te

Cou

ntr

yM

ean

Med

ian

Sta

ndar

dO

bse

rvat

ions

Mea

nM

edia

nSta

ndar

dO

bse

rvat

ions

Diff

eren

ce(1

)D

evia

tion

(2)

Dev

iati

onM

ean(1

)-

Mea

n(2

)

Cze

chR

epublic

0.13

60.

045

1.95

613

5,89

40.

147

0.01

91.

943

19,2

34-0

.009

Est

onia

0.38

30.

238

1.98

792

,791

-0.0

45-0

.007

2.11

51,

818

0.42

8***

Hunga

ry0.

060

0.05

01.

476

118,

061

-0.0

53-0

.013

1.36

15,

790

0.11

3***

Lat

via

-0.0

33-0

.013

1.66

691

,562

0.00

60.

021

1.80

71,

601

-0.0

39L

ithuan

ia-0

.153

-0.0

561.

650

104,

826

0.01

7-0

.041

1.64

82,

283

-0.1

70**

*Slo

vak

Rep

ublic

0.31

10.

131

2.20

810

2,49

70.

068

-0.0

022.

418

829

0.24

3***

Slo

venia

0.24

90.

092

1.92

510

2,60

50.

182

0.05

61.

882

13,2

720.

067*

**

Tra

de

gap

by

pro

du

cts

taxed

wit

ha

stan

dard

an

dre

du

ced

VA

Tra

te(o

nly

pro

du

ctw

ith

iden

tifi

edV

AT

rate

sco

nsi

der

ed).

Mea

nan

dm

edia

nta

riff

valu

esare

calc

ula

ted

for

each

cou

ntr

yan

dyea

r.T

est

for

equ

ality

of

mea

ns:

***p<

0.0

1,

**p<

0.0

5,

*p<

0.1

.

17

Tab

le3:

Des

crip

tive

stat

isti

cs(“

mix

ed”

vs.

“non

-mix

ed”

pro

duct

cate

gori

es).

Mix

ed=

0M

ixed

=1

Cou

ntr

yM

ean

Med

ian

Sta

ndar

dO

bse

rvat

ions

Mea

nM

edia

nSta

ndar

dO

bse

rvat

ions

Diff

eren

ce(1

)D

evia

tion

(2)

Dev

iati

onM

ean(1

)-

Mea

n(2

)

Cze

chR

epublic

0.13

70.

042

1.95

515

5,12

80.

075

0.03

91.

878

6,20

10.

062*

**E

ston

ia0.

375

0.23

21.

990

94,6

090.

467

0.31

12.

025

4,53

3-0

.092

***

Hunga

ry0.

055

0.04

61.

471

123,

588

-0.0

72-0

.017

1.38

05,

439

0.12

7***

Lat

via

-0.0

32-0

.012

1.66

993

,163

-0.0

69-0

.025

1.75

24,

193

0.03

7L

ithuan

ia-0

.150

-0.0

551.

650

107,

109

-0.1

40-0

.064

1.64

76,

733

-0.0

10Slo

vak

Rep

ublic

0.30

90.

131

2.21

010

3,32

60.

833

0.53

02.

259

149

-0.5

24**

*Slo

venia

0.24

20.

088

1.92

011

5,87

70.

273

0.12

82.

011

6,18

2-0

.031

Tra

de

gap

by

pro

du

ctca

tegori

es;

pro

du

ctco

des

wit

hid

enti

fied

VA

Tra

tes

are

pre

sente

din

the

firs

tfo

ur

colu

mn

s(M

ixed

=0),

those

wit

hm

ixed

VA

Tra

tes

inco

lum

ns

6-9

(Mix

ed=

1).

Mea

nan

dm

edia

nta

riff

valu

esare

calc

ula

ted

for

each

cou

ntr

yan

dyea

r.T

est

for

equ

ality

of

mea

ns:

***p<

0.0

1,

**p<

0.0

5,

*p<

0.1

.

18

the increase is almost 4%. For Slovenia, the response in the trade gap is of smaller mag-nitude, but also highly significant. The results presented in Table 4 are consistent withthe descriptive statistics from Table 2, which show that Estonia, the Slovak Republic andSlovenia are the countries with the highest trade gaps and thus potentially suffer mostfrom VAT evasion. Lithuania is an exception, where the correlation between the VATrate and the trade gap is negative and significant, meaning that an increase in the VATrate is associated with a decrease in the trade gap.

Table 4: Trade gap and VAT rate.

(1) (2) (3) (4) (5) (6) (7)

Year FE included

Czech Estonia Hungary Latvia Lithuania Slovak SloveniaRepublic Republic

V AT -0.001 0.034*** 0.004 -0.003 -0.013*** 0.042*** 0.006**(0.002) (0.009) (0.003) (0.007) (0.004) (0.012) (0.003)

Observations 155,128 94,609 123,588 93,163 107,109 103,326 115,877Adj. R2 0.001 0.002 0.007 0.004 0.001 0.004 0.000

Year FE and Partner country FE included


V AT 0.002 0.033*** 0.003 -0.001 -0.012*** 0.038*** 0.009***(0.002) (0.009) (0.003) (0.007) (0.004) (0.012) (0.003)


Year FE, Partner country FE and Product FE included


V AT -0.004 0.033** -0.004 -0.019 -0.006 0.038*** -0.017(0.010) (0.016) (0.003) (0.033) (0.008) (0.013) (0.018)


Note: *** p < 0.01, ** p < 0.05, * p < 0.1.First panel: All regressions include year fixed effects and a constant.Second panel: All regressions include year and partner country fixed effects and a constant.Third panel: All regressions include year, partner country and four-digit product fixed effects, and a constant.Standard errors, clustered at the six-digit product level, in parentheses.

As previously discussed, the theoretical and empirical literature on the topic of taxevasion show that the relationship between the level of tax rate and the rate of evasionis ambigious. Agha and Haughton (1996) estimate a decrease of 2.7 percentage points

19

in the VAT compliance rate as a response to a one-percentage-point increase in the VATrate and Christie and Holzner (2006) measure a decrease of 0.3 percentage points. How-ever, Yitzhaki (1974) and Reckon LLP (2009) provide theoretical and empirical evidencerespectively that an increase in the tax rate is associated with a decrease in the VATnon-compliance rate. The findings of Table 4 are therefore in line with the previousstudies since they show that across the EU-7 countries the direction of the correlationbetween the trade gap and the VAT rate is also ambigious. In addition, the magnitudeof the effect of the VAT rate on the trade gap varies substantially across the states; aone-percentage-point increase in the VAT rate is associated with 0.9% to 3.8% increasein the trade gap. Thus, the results reveal the importance of country heterogeneity in therelationship between the VAT rate and the trade gap.

The last panel of Table 4 presents the results when four-digit product fixed effects areincluded. As expected, the significance level of the estimates is lower since the variationof the VAT rate over time is limited at the six-digit product level. For Estonia and theSlovak Republic the correlation between the VAT rate and the trade gap remains in thesame magnitude as before. For Slovenia and Lithuania the relationship is no longer sig-nificant. A possible explanation for Slovenia is the fact that the VAT rates do not varyover time in the sample period so the variation in the VAT variable comes only fromdifferences in the VAT rates across products. Thus, once controlling for product fixedeffects at the four-digit level, the variation of the VAT rate is very limited which leadsmost likely to the change in the significance level.

5.3 Robustness checks

Equation 2 is also estimated weighted by the mean value of exports of each partnercountry-product code pair controlling for the relation between the missing trade andthe export value, which is assumed to be the “true” value of the trade flow. Table 5presents the results. Overall, the outcomes are very similar to the baseline results inTable 4. The only difference is the result for Hungary, for which the correlation betweenthe VAT rate and the trade gap is now significant at the 5%-level except when productfixed effects are included. The estimate for Hungary is similar in its magnitude to theoutcome for Slovenia, a one-percentage-point increase in the VAT rate is associated witharound 1% increase in the trade gap, and thus much lower than in the cases of Estoniaand the Slovak Republic. Estonia and the Slovak Republic remain the only countries, forwhich the coefficient on the VAT rate is still significant when adding product fixed effects.

Instead of a variable, capturing the level of the VAT rate, Equation 2 might be es-timated including a dummy variable, which indicates whether the product code belongsto the goods for which a standard VAT rate applies. Compared to a VAT variable inlevels, the dummy variable shows the difference in the trade gap between the productswhich are taxed with the standard VAT rate and those taxed with the reduced rate in-dependent of the exact level of the VAT rates. Table 6 shows the results. The findingsare consistent with the outcomes of Table 4. Products subject to the standard VAT ratehave a significantly higher trade gap than the goods taxed with the reduced VAT ratein Estonia, the Slovak Republic and Slovenia. The inverse relationship applies again forLithuania.

20

Table 5: Trade gap and VAT rate, weighted by exports.

(1) (2) (3) (4) (5) (6) (7)

Year FE included


V AT 0.000 0.035*** 0.007** -0.004 -0.011** 0.041*** 0.007**(0.002) (0.009) (0.003) (0.007) (0.004) (0.013) (0.003)




V AT 0.002 0.034*** 0.006** -0.001 -0.010** 0.038*** 0.010***(0.002) (0.009) (0.003) (0.007) (0.004) (0.013) (0.003)




V AT -0.000 0.037** -0.001 -0.018 -0.006 0.035*** -0.018(0.009) (0.018) (0.003) (0.037) (0.008) (0.013) (0.019)



21

Table 6: Trade gap and VAT rate, dummy variable for the standard VAT rate.

(1) (2) (3) (4) (5) (6) (7)

Year FE included


Standard V AT -0.009 0.427*** 0.037 -0.040 -0.174*** 0.377*** 0.068**(0.031) (0.113) (0.027) (0.086) (0.058) (0.109) (0.034)




Standard V AT 0.022 0.411*** 0.027 -0.014 -0.163*** 0.346*** 0.103***(0.030) (0.111) (0.027) (0.085) (0.058) (0.109) (0.034)




Standard V AT -0.299 0.449** -0.053* -0.239 -0.107 0.340*** -0.194(0.399) (0.207) (0.029) (0.426) (0.111) (0.117) (0.203)



5.4 Controlling for outliers

In all previous tables the estimates for Hungary are restricted only to trade flows with avalue higher than 1,000 US dollars. Table 7 presents the results if this sample restrictionis applied to all countries. The estimates are very similar in magnitude and significanceto the baseline results. Table 8 shows the results of estimating Equation 2 only for tradeflows with a higher value than 50,000 US dollars. The probability of measurement error islikely to be higher for trade flows of a smaller value and also the statistical offices controlpotentially more strictly trade flows with a higher value. Excluding all trade flows below

22

the threshold of 50,000 US dollars leads to dropping out a substantial share of observa-tions, more than 50% of the observations in the sample are left out. Table 8 shows thatthere is a positive and significant correlation between the VAT rate and the trade gapin five of the seven countries in the sample (Czech Republic, Estonia, Hungary, SlovakRepublic and Slovenia). The significant relationship remains also when partner countryfixed effects are added. Similar to the previous results, the magnitude is the highest forEstonia and the Slovak Republic, although lower than in Table 4. Again, when addingfour-digit product fixed effects the significance level decreases, only the estimates for Es-tonia and Hungary remain significant. Since the variation in the VAT rates is rather lowover time, this result is not surprising.

Table 7: Trade gap and VAT rate (Trade flows with value higher than 1,000 USD).

(1) (2) (3) (4) (5) (6) (7)

Year FE included


V AT 0.001 0.030*** 0.004 -0.005 -0.009** 0.033*** 0.009***(0.002) (0.008) (0.003) (0.006) (0.004) (0.012) (0.002)



Czech Estonia Hungary Latvia Lithuania Slovak Slovenia

V AT 0.002 0.028*** 0.003 -0.004 -0.008** 0.029** 0.011***(0.002) (0.008) (0.003) (0.006) (0.004) (0.012) (0.002)




V AT -0.012 0.042*** -0.004 -0.015 -0.006 0.024** -0.016(0.008) (0.013) (0.003) (0.025) (0.008) (0.011) (0.016)



In order to control for outliers, Equation 2 is also estimated dropping the top and

23

Table 8: Trade gap and VAT rate, trade flows with a value higher than 50,000USD.

(1) (2) (3) (4) (5) (6) (7)

Year FE included


V AT 0.005*** 0.026*** 0.008*** 0.002 0.003 0.027** 0.009***(0.002) (0.007) (0.002) (0.006) (0.003) (0.011) (0.002)




V AT 0.006*** 0.026*** 0.007*** 0.003 0.003 0.023** 0.010***(0.002) (0.007) (0.002) (0.006) (0.003) (0.011) (0.002)




V AT 0.003 0.038*** 0.008*** 0.001 -0.007 0.001 0.004(0.005) (0.007) (0.003) (0.017) (0.006) (0.009) (0.016)



24

bottom 1% or 10% of trade gap observations. Table 9 and Table 10 show the results with-out the 1% or 10% outliers of the trade gap, respectively. There is no difference betweenthe findings of Table 9 and the baseline results, except that dropping the 1% outliers inthe trade gap observations leads to a slightly lower magnitude of the significant coeffi-cients. The results of Table 10 are very similar to the ones of Table 8 implementing thethreshold of 50,000 US dollars, except that the share of the dropped observations is muchlower. The coefficient on the VAT rate is significant and positive for the Czech Republic,Estonia, the Slovak Republic and Slovenia when year and partner country fixed effectsare included (for Hungary only in the first panel). In the specification with product fixedeffects, the relationship between the VAT rate and the trade gap is significant for Estonia,Hungary and the Slovak Republic. The magnitude of the significant coefficients is againlower, particularly for Estonia and the Slovak Republic, although they still remain thehighest among the other countries in the sample.

Some product groups might be regarded as outlier cases because additional taxes suchas an excise tax or confidential restrictions apply for them. Excluding HS24 (tobacco),HS26 (ores), HS27 (mineral fuels and oils), HS84 (nuclear reactors), HS88 (aircraft andspacecraft), HS89 (ships, boats and floating structures) and HS93 (arms and ammuni-tion) based on these concerns does not change the baseline results.

Table 11 summarizes the results of the empirical analysis displaying the sign and thesignificance level of the coefficient on the VAT rate variable for each EU-7 country esti-mated in each of the empirical specifications with year and partner country fixed effectsincluded. The estimates are robust to changes in the specification and controlling foroutliers for three countries, namely Estonia, the Slovak Republic and Slovenia, and showa positive and highly significant correlation between the VAT rate and the trade gap.For the Czech Republic and Hungary the relationship is also positive, however, only intwo regressions it is significant. For the Czech Republic, an increase in the VAT rate isassociated with an increase in the trade gap only when the outliers in the trade gap dataunder the broader definitions (either excluding trade flows below 50,000 USD or 10% ofthe top and bottom trade gap observations) are left out from the sample. The results forLatvia are mostly negative, though never significant. Lithuania presents an outlier casesince in the majority of the specifications the coefficient on the VAT rate points towardsa negative and siginicant correlation between the VAT rate and the trade gap. Similarto the results of the empirical studies on the VAT gap and to the estimations on therelationship between the trade gap and the tariff rate the correlation between the tradegap and the VAT rate is not straightforward. Even though the majority of the results inthis study point towards a positive relationship between the trade gap and the VAT rate,the empirical analysis shows that the inverse relationship might also apply. Despite theevidence that VAT evasion in intra-Community trade is prevalent in many of the EU-7countries, the direction and the magnitude of the effect of the VAT rate on the trade gapseem to be dependent on country characteristics.

25

Table 9: Trade gap and VAT rate, controlling for outliers (without top and bottom 1% oftrade gap observations).

(1) (2) (3) (4) (5) (6) (7)

Year FE included


V AT 0.001 0.031*** 0.001 -0.005 -0.009** 0.034*** 0.006**(0.002) (0.008) (0.003) (0.006) (0.004) (0.011) (0.003)




V AT 0.002 0.030*** 0.001 -0.003 -0.009** 0.031*** 0.008***(0.002) (0.008) (0.003) (0.006) (0.004) (0.011) (0.003)




V AT -0.009 0.032*** -0.004 -0.013 -0.006 0.025*** -0.009(0.008) (0.012) (0.003) (0.026) (0.008) (0.010) (0.014)



26

Table 10: Trade gap and VAT rate, controlling for outliers (without top and bottom 10% oftrade gap observations).

(1) (2) (3) (4) (5) (6) (7)

Year FE included


V AT 0.004*** 0.015*** 0.003* -0.003 0.001 0.022*** 0.006***(0.001) (0.004) (0.001) (0.003) (0.002) (0.008) (0.001)




V AT 0.005*** 0.015*** 0.002 -0.003 0.001 0.020** 0.007***(0.001) (0.004) (0.001) (0.003) (0.002) (0.008) (0.001)




V AT -0.005 0.031*** 0.003* -0.007 -0.002 0.017*** -0.009(0.004) (0.007) (0.002) (0.011) (0.003) (0.006) (0.006)



27

Tab

le11

:Sum

mar

yof

the

resu

lts

wit

hye

aran

dpar

tner

countr

yfixed

effec

ts.

(1)

(2)

(3)

(4)

(5)

(6)

(7)

Cze

chE

ston

iaH

unga

ryL

atvia

Lit

huan

iaSlo

vak

Slo

venia

Rep

ublic

Rep

ublic

Bas

elin

e+

+**

*+

--*

**+

***

+**

*W

eigh

ted

by

exp

orts

++

***

+**

--*

*+

***

+**

*V

AT

dum

my

vari

able

++

***

+-

-***

+**

*+

***

Tra

de

abov

e1,

000

USD

++

***

+-

-**

+**

+**

*T

rade

abov

e50

,000

USD

+**

*+

***

+**

*+

++

**+

***

1%ou

tlie

rsof

trad

ega

pdro

pp

ed+

+**

*+

--*

*+

***

+**

*10

%ou

tlie

rsof

trad

ega

pdro

pp

ed+

***

+**

*+

-+

+**

+**

*

Note

:***p<

0.0

1,

**p<

0.0

5,

*p<

0.1

.S

um

mary

of

the

sign

an

dth

esi

gn

ifica

nce

level

of

the

coeffi

cien

tonVAT

base

don

all

pre

vio

us

esti

mati

on

sin

clu

din

gyea

ran

dp

art

ner

cou

ntr

yfi

xed

effec

ts.

28

6 Conclusion

Recent estimations and studies have suggested that VAT fraud has been increasing sincethe introduction of the EU Single Market in 1993. Intra-EU trade flows, in particular,have become more vulnerable to VAT fraud schemes since the change in the procedureof VAT collection in intra-Community trade. Policy-makers and the national tax admin-istration are aware of this issue and the threat that it imposes on the functioning of theSingle Market. However, until now, the empirical evidence has remained very scarce withregard to the relationship between the level of the VAT rate and the asymmetries in thebilateral trade flows between EU members. This is the first study to use an empiricalapproach employed in the literature on tariff evasion and to estimate the responsivenessof the missing trade between EU member states to changes in the VAT rate.

The study shows that there is a robust positive correlation between the level of theVAT rate and the trade gap for Estonia, the Slovak Republic and Slovenia. The rela-tionship is strongly pronounced for Estonia and the Slovak Republic. Depending on thespecification, a one-percentage-point increase in the VAT rate in these two countries isassociated with more than 3% increase in the trade gap. When restricting the sampleto trade flows with a higher value than 50,000 US dollars or dropping the top and bot-tom 10% outliers in the trade gap data, the correlation is positive and significant in fivecountries (Czech Republic, Estonia, Hungary, Slovak Republic and Slovenia), potentiallydue to better quality of the trade data and more correct estimates. This systematic cor-relation between the level of the VAT rate and the trade gap suggests that VAT evasionin intra-EU trade flows is a serious issue to tackle in many of the EU-7 countries. Theempirical evidence of the study indicates that the VAT rate, which has been so far ne-glected in the literature on the missing trade, is a relevant determinant of the mismatchin mirror trade statistics between the EU-15 and the EU-7 countries.

In addition, the results of the study provide evidence that the correlation betweenthe VAT rate and the trade gap varies substantially across the EU-7 countries so it isimportant to take into account the specific institutional and political environment of eachcountry. This finding points towards the fact how difficult it might be to overcome thedifferences in the national VAT laws and to agree upon a common VAT legislation for allEU members in the future. However, it is potentially because of these differences in thenational VAT legislation that the VAT fraud schemes exist to such an extent in intra-Community trade flows. Better coordination and exchange of data across the national taxauthorities might be effective, at least as a first step, to limit the scope of VAT evasion.Better availability of detailed data on VAT rates and their implementation would allowfor more extensive future research on the topic of VAT fraud.

29

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