European Financial Management, Vol. 23, No.

3, 2017, 519–542
doi: 10.1111/eufm.12118

Tax Havens, Tax Evasion and Tax

Information Exchange Agreements
in the OECD
David M. Kemme
Fogelman College of Business and Economics, University of Memphis, Memphis, TN, USA
E-mail: dmkemme@memphis.edu

Bhavik Parikh
Gerald Schwartz School of Business, St. Francis Xavier University, Antigonish, Nova Scotia,
Canada
E-mail: bparikh@stfx.ca

Tanja Steigner
School of Business, Emporia State University, Emporia, KS, USA
E-mail: tsteigne@emporia.edu

Abstract
Using data on Foreign Portfolio Investment (FPI), we find a positive relationship
between higher tax burden and OECD residents’ tax evasion, especially via tax
havens. Contrary to established investor preference for certain country
characteristics, we find they are less important to tax evaders who value privacy
and want to remain undetected by their home tax authorities. We find very limited
evidence that OECD Tax Information Exchange Agreements (TIEAS) reduce tax
evasion, controlling for other determinants of overall OECD FPI. Without the US
in the OECD sample, tax havens play a lesser role and OECD policies appear to
make a marginal impact.

Keywords: tax haven, tax evasion, foreign portfolio investment, tax information
exchange agreements, OECD
JEL classification: F38, G38, H26

We thank John Doukas and an anonymous referee for very helpful comments and
suggestions on an earlier draft.

© 2017 The Authors. European Financial Management Published by John Wiley & Sons Ltd
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and
reproduction in any medium, provided the original work is properly cited.
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520 David M. Kemme, Bhavik Parikh and Tanja Steigner

1. Introduction

With an estimated USD 190 billion per year in lost revenues, tax evasion via offshore tax
havens challenges tax authorities of many nations.1 We provide empirical evidence of
OECD country residents’ tax evasion using the concept of round tripping, i.e., when
OECD residents funnel money through an undeclared offshore account and,
unbeknownst to their local tax authorities, subsequently reinvest back into their home
country’s capital market posing as a foreign investor.2 Thus, as a result these OECD
residents (typically) pay a lower tax rate on their investment returns. For the period
2002–2013 we find that foreign portfolio investment (FPI) flows increase with tax
benefits from round tripping, which is an indirect measure of tax evasion.3 For the entire
OECD sample we also find that higher tax savings result in more FPI flows from tax
havens. This finding appears to be driven by US flows.
In addition to tax savings, what other factors might tax evaders value? We argue
that certain country characteristics make collaboration between tax authorities more
challenging, and are therefore desirable for evasion. Genuine investors want to
reduce information costs and prefer investing in close-by countries with which they
are familiar in terms of language, legal system and corruption oversight (Chan et al.,
2005; Gaston et al., 2005; Grinblatt and Keloharju, 2001; and Wei and Shleifer, 2000).
In the case of round tripping via tax havens, we find opposite results where FPI flows
are positively related to greater distance, different legal systems and greater
corruption. Different legal systems and higher potential corruption likely result in less
efficient information sharing and subsequent detection of tax evasion by the tax
authorities. This new finding adds to the existing literature by highlighting the tenacity
and persistence of tax evaders.
The Organisation for Economic Co-operation and Development (OECD) addressed
its members’ call for measures against harmful tax competition in its 1998 report,
Harmful Tax Competition: An Emerging Global Issue (OECD, 1998), with
recommendations for legislation, tax treaties and intensified international cooperation.4
Subsequently, the OECD developed a standard for Tax Information Exchange
Agreements (TIEAs), of which more than 800 were signed by 2013.5 In addition to
TIEAs, the Council of the European Union introduced information exchange for taxation
of interest income between member states in 2003 (Council Directive 2003/48/EC), and
the European Union Savings Tax Directive (STD) implemented in 2005 provided a
multilateral institutional means of collecting taxes and exchanging information

1
See Griffith (2015). Approximately half of the global flows of foreign direct investment are
routed through offshore financial centres (Palan et al., 2010; Palan and Nesvetailova, 2013),
and the accumulated private financial wealth in registered offshore tax havens was estimated
to be between USD 21 and USD 32 trillion in 2010 (Henry, 2012).
2
A more in-depth explanation of round tripping is provided in the Background section below.
3
See Hanlon et al. (2015).
4
See also Dermine (1996).
5
Oversight of Tax Co-operation and Information Exchange is currently facilitated by the
OECD’s Global Forum, consisting of 126 member jurisdictions and the European Union. See
http://www.oecd.org/tax/transparency and http://www.oecd.org/tax/exchange-of-tax-
information/.

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Tax Havens, Tax Evasion and Tax Information Exchange Agreements 521

regarding foreign deposit accounts.6 This directive supplements double taxation

avoidance agreements (DTAA), which have been in place since the 1950s and are
generally designed to encourage foreign investment (Barthel et al., 2010) and harmonise
tax rules between two countries (Dagan, 2009).7 DTAAs may contain tax information
sharing provisions between the treaty countries (Bacchetta and Espinosa, 2000).
While Rixen and Schwarz (2012) and Johannesen (2014), among others, examine the
STD and tax evasion via foreign bank deposit accounts, we focus on OECD countries’
tax evasion via capital market investments.8 Focusing on just the US, Hanlon et al.
(2015) examine capital market flows and find that tax evasion by US residents increases
when US tax rates increase, and decreases with the implementation of TIEAs. Given the
economic importance of the OECD, whose countries combined produce 63% of global
gross domestic product (GDP) and 75% of global trade,9 we provide empirical feedback
on tax evasion of OECD country residents and the efficacy of OECD policies. This is
important because compliance and enforcement costs are not trivial.10 We investigate the
deterrence of tax evasion for OECD residents following implementation of information
sharing agreements and compare the benefits of tax evasion to its risks. Similar to
Johannesen and Zucman (2014), we find mixed evidence for the effectiveness of TIEAs
between OECD countries and tax havens. Controlling for country characteristics beyond
size of economy, information sharing agreements do not deter FPI from tax havens.
Further, tax evasion via round tripping from tax havens persists even when TIEAs are
signed between OECD countries and tax havens. However, focusing only on OECD
countries excluding the US, TIEAs do reduce flows from tax havens and tax savings with
tax havens no longer induce round tripping. TIEAs appear effective for OECD countries
if the US is excluded from the sample.
We also examine other country-specific factors considered in the literature. We find
that, in general, FPI increases with the existence of double taxation avoidance
agreements and when the currency of the source country (equity origin) is stronger than
the currency in the host country (equity destination). In line with the literature, we further

6
Austria, Belgium and Luxembourg were exempted from automatic information exchange
due to ‘structural differences’. Instead, those countries were tasked to collect and transfer
withholding taxes. Belgium and Luxembourg discontinued their participation in 2010 and
2015, respectively (European Community, 2003). Also see Rixen and Schwarz (2012) and
Johannesen (2014).
7
In terms of what taxes are imposed and how tax revenues are distributed. In some cases tax
information exchange has been incorporated into these agreements.
8
Household offshore wealth may be in securities accounts holding bonds and equities (FPI)
or in bank deposits. We focus on FPI because it accounts for approximately 75% of the total
household offshore wealth, as of 2008 (Zucman, 2013, Table III, p. 1345).
9
See http://usoecd.usmission.gov/mission/overview.html.
10
Costs of compliance with tax evasion laws would be in the magnitude of costs of
compliance with anti-money laundering laws, such as the Foreign Account Tax Compliance
Act, and the Foreign Corrupt Practices Act in the US. These are estimated to be USD 10
billion per year for US banks (KPMG, 2015). Halliday et al. (2014) examine the IMF
programme on anti-money laundering and combating the financing of terrorism, which has
similar objectives as tax evasion efforts, and find that they have not been effective despite
their high costs. In addition, these laws raise the costs of legitimate transfers (Coats, 2016).

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522 David M. Kemme, Bhavik Parikh and Tanja Steigner

find that more developed countries attract more investments (Chan et al., 2005),
evidenced by more FPI flowing into countries with greater GDP (as a share of total
OECD GDP) and GDP per capita relative to the source country. Our results are robust for
the entire OECD sample, controlling for source country and year fixed effects, and for the
global financial crisis.
Section 2 of this paper provides background on tax evasion and hypotheses
development. Section 3 describes the data. Section 4 presents the model and empirical
analysis. Section 5 presents the empirical results, and section 6 concludes.

2. Background on Tax Evasion and Hypotheses

2.1. Background
Since individuals engaging in tax evasion naturally keep transaction information private
to avoid detection and prosecution, direct assessment of the magnitude and significance
of such tax evasion is difficult. Nonetheless, two recent studies of the EU Savings Tax
Directive (STD) provide valuable insights. The Directive focuses on interest earned on
foreign savings deposits and requires either automatic information exchange (rather than
on request) or tax withholding. Johannesen (2014) examines the impact of the STD on
Swiss bank deposits held by EU residents. Using non-EU residents as a benchmark, he
finds that deposits of EU members declined 30–40% immediately prior to the Directive’s
implementation. Individuals moved their deposits from Switzerland to other
jurisdictions not subject to the Directive. Rixen and Schwarz (2012) focus on investors
in four source countries (France, Italy, Sweden and Spain). They find that investors
adapted to the Directive well before it was implemented, and switching from debt to
equity products in the same country was more prevalent than moving portfolio capital to
other tax havens. However, countries that opted for tax information sharing rather than
withholding did experience an outflow. Notably, the response of investors in each of the
four countries was quite different. There were strong effects for French investors, less so
for those in Sweden and Spain, and virtually no response in Italy.
These results, while based on a few countries and only for deposit accounts,11 may be
indicative of a general phenomenon. Zucman (2013) offers an excellent discussion of
anomalies in the international investment position of balance of payments accounts and
provides aggregate estimates of ‘missing wealth’ due to tax evasion.12 We use Foreign
Portfolio Investment (FPI) flows from tax havens to assess round tripping in the OECD
as an indirect measure of tax evasion.13 The IMF (2004) defines round tripping as
channeling private local funds into foreign Special Purpose Entities and then reinvesting
those funds back into the local economy via direct investment; motivations for round
tripping include confidentiality and tax advantages. Therefore, local tax haven residents

11
STD does not apply to brokerage accounts or other assets held abroad.
12
He examines the External Wealth of Nations dataset constructed by Lane and Milesi-
Ferretti (2007), which covers 178 economies. Our dataset covers a later period.
13
See Hanlon et al. (2015) for the arguments regarding the importance and significance of
such flows and the underlying theory and identification strategy, which we employ. Also, see
Slemrod (2007) for an insightful review of tax evasion issues in general and Dharmapala
(2008) for a review of the literature on tax havens.

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Tax Havens, Tax Evasion and Tax Information Exchange Agreements 523

are not the primary source of capital inflows from these countries.14 Most countries
welcome foreign investments to support their economy, and they tax foreign investors at
a lower rate than domestic investors. The US, for example, frequently imposes a lower
dividend income tax on foreign investors and exempts them from taxes on capital gains
and interest income earned in the US,15 and other OECD countries provide similar
incentives to many foreign investors. Thus, when investors round trip, they evade taxes
by taking advantage of tax savings equal to the difference in taxes charged to local and
foreign investors.16 Although tax evasion is illegal, it is difficult for tax authorities to
identify tax evaders. Despite efforts by the OECD and others to establish information
sharing agreements between countries, such as Tax Information Exchange Agreements
(TIEAs) and Double Taxation Avoidance Agreements (DTAAs), information under
such agreements is typically shared only upon request by the inquiring country
(Barber, 2007).
Lost tax revenues are significant and cover a wide range of countries. For example,
Canadians for Tax Fairness reported that CAD 170 billion are held in ten offshore tax
havens.17 The UK Guardian revealed that more than 100 of Britain’s richest individuals
are protecting billions of pounds in undisclosed offshore accounts.18 And Italy is losing
91 billion Euros in tax revenues annually due to tax evasion (Reuters.com).19
Nonetheless, uncovering tax evasion schemes is no small task. According to US tax
authorities, ‘IRS Criminal Investigation coordinates its efforts with other countries to
counteract tax schemes, and money laundering. Worldwide, many countries have agreed
to adopt international tax standards on exchanging information and, as a result, the age of
bank secrecy might seem to be coming to an end’.20 However, this appears wildly
optimistic as the scale, determinants of evasion, and effectiveness of new information
exchanges are not yet well quantified or understood, and there is no shortage of media
reports of continuing tax evasion. Empirical evidence is scant and mixed. Hanlon et al.
(2015) report that the signing of TIEAs between the US and tax havens decreases

14
Again, approximately half of the global flows of foreign portfolio investment are routed
through offshore financial centres (Palan et al., 2010; Palan and Nesvetailova, 2013).
15
The US does not tax foreign investors, non-resident aliens, on capital gains and interest
income Internal Revenue Service (2016).
16
We focus on tax savings rather than the magnitudes of the home country tax rates as in
Johannesen (2014), who finds no correlation between the home tax rates of EU countries and
the size of the response to the Savings Tax Directive.
17
They have also noted that federal and provincial governments lose about CAD 8 billion per
year in tax revenues. See The Canadian Press (2014). Recently the Canadian Revenue
Agency took action against KPMG and HSBC for designing and implementing schemes
purposely to avoid taxes for over a thousand Canadians (see CBC News, 2015a, 2015b, inter
alia).
18
See Ball and Neate (2013).
19
In 2015 Italy signed a tax information sharing agreement with Switzerland, where Italians
stored much of their wealth Fonte and Trevelyan (2015). Italians who voluntarily disclosed
their Swiss holdings paid a penalty between 7 and 12% of their holdings, Logutenkova and
Vogeli (2015).
20
See IRS (2015), http://www.irs.gov/uac/International-Investigations-Criminal-Investigation-
(CI).

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524 David M. Kemme, Bhavik Parikh and Tanja Steigner

evasion, while Johannesen and Zucman (2014) find that TIEAs have only a modest
negative effect on tax evasion. To expand the literature and gain a deeper understanding
of international tax evasion and the effectiveness of information agreements, we now
turn to our specific hypotheses.

2.2. Hypotheses
Following Becker’s (1968) theory of crime, investors’ engagement in tax evasion
depends heavily on their perceived costs and benefits. The benefits of tax evasion can be
measured by tax savings to the investor. We focus on the difference between tax rates a
domestic investor pays on dividend income and tax rates a foreign investor pays
(via withholdings) on the same dividend income, since most countries offer lower
dividend income tax rates to foreign investors.21 As the differences in tax rates increase,
it becomes more beneficial for domestic investors to invest in their local capital market
by posing as a foreign investor via an offshore account. In other words, as tax savings via
round tripping schemes increase, investors might be more tempted to evade taxes. Such
tax evasion might be more pronounced when investors round trip via a tax haven with
greater levels of perceived privacy. We also control for other country specific variables
that affect FPI flows. Thus,
H1a: The relationship between tax savings and FPI flows, an indicator of round
tripping, is positive in general for OECD host countries.

H1b: The relationship between tax savings and FPI flows is also positive for OECD host
countries and even larger when FPI originates from tax haven source countries.22

In addition to tax savings, tax havens also offer protection from investors’ domestic
tax authorities due to lack of effective exchange of information and transparency
between countries (OECD, 1998). This lack of transparency originates predominately
with the laws and regulations of the tax havens (Hines and Rice, 1994), but might be
augmented by other country characteristics. Specifically, investors might be attracted to
countries that make communication with the home authorities more difficult. Previous
studies show that investors, in general, prefer geographic closeness (Grinblatt and
Keloharju, 2001) as well as countries that speak the same language (Aggarwal et al.,
2012; Grinblatt and Keloharju, 2001), share the same legal system (Guiso et al., 2009)

21
Instead of using tax rates on dividend income, Hanlon et al. (2015) focus on differences in
long-term capital gains tax rates. This required the collection of US long-term capital tax rates
by year applied to domestic investors. Since foreign investors do not pay any withholding
taxes on long-term capital gains in the US, the tax benefits of a foreign investor relative to a
US investor is easily computed. However, other OECD countries do impose withholding
taxes on foreign investors, and the required information to obtain tax savings is only available
for 2012; OECD (2002) and as confirmed by Mr. Michael Sharratt, OECD. For this reason,
we focus on the differences in tax rates on dividend income, which are available for the
countries and timeframe in our analysis.
22
Source countries are countries from where the foreign equity flows originate and host
countries are the final destination countries of the foreign equity flows.

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Tax Havens, Tax Evasion and Tax Information Exchange Agreements 525

and offer a strong governance system (Abdioglu et al., 2013). We contend that this is not
true for tax evaders as the benefits of tax evasion outweigh these desirable characteristics.
Tax havens are known for their strict privacy policies and therefore better protect the
evader from detection. Investors who engage in offshore tax evasion presumably value
privacy rather than proximity, or similarity in language, legal and governance system.
Thus, the hypotheses regarding country specific determinants may be summarised as:
H2: FPI into the OECD from tax haven source countries is positively related to
geographic distance (H2a), and negatively related to common language (H2b), identical
legal system (H2c), or control for corruption (our measure of governance) (H2d).

The possible negative consequences from engaging in unlawful practices are a clear
cost to be considered. Applying this logic to the situation of round tripping, we consider
the costs of setting up the legal structure as sunk costs, and the probability of being caught
and prosecuted as the costs of round tripping. The signing of an OECD incentivised tax
information exchange agreement (TIEA) between countries is a reasonable proxy for an
increase in enforcement efforts and thereby an increase in the probability of getting
caught evading home country taxes. TIEAs are bilateral agreements that allow
information sharing upon request for civil and legal tax purposes (OECD, 2002a).
Alternatively, information exchange can be also incorporated in DTAAs (OECD,
2002b). We focus on the effectiveness of such agreements as a deterrent to tax evasion
for OECD member investors.
Equity flows, in general, should increase when the host country has signed DTAAs
since those agreements simplify tax rules for foreign investors and reduce double
taxation. The genuine investor views DTAAs positively. However, we should not find
any positive relationship between DTAAs and information exchange agreements and
FPI if the equity originates from a tax haven. If TIEAs and DTAAs with tax havens have
no impact on FPI, we conclude that these agreements pose no real deterrent effect. On the
other hand, OECD efforts are effective if TIEAs and DTAAs with tax havens reduce FPI.
Thus,
H3: DTAAs, in general, are positively related to FPI (H3a). TIEA and DTAA
agreements with tax havens either have no impact on FPI if tax evaders are not
sufficiently deterred by OECD policy (H3b), or they have a negative impact if
OECD policy is effective (H3c).

Lastly, we directly test the interplay between benefits and costs in determining tax
evasion. If benefits outweigh costs, then the coefficient for the interaction between
TIEAs and tax savings is positive when the FPI originates from a tax haven. If the
costs outweigh the benefits, we expect the interaction term coefficient to be negative,
and if cost and benefit neutralise each other, the coefficient should be insignificant. We
effectively test whether round tripping exists even if a TIEA is signed with a tax
haven.
Thus, while policy-makers expect TIEAs to reduce round tripping we consider three
possibilities:
H4a: If the benefit from tax evasion outweighs the potential cost, the relationship
between FPI flows and the interaction between Tax Savings and TIEAs is positive
for OECD host countries when FPI originates from tax haven source countries.

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526 David M. Kemme, Bhavik Parikh and Tanja Steigner

H4b: If the benefit from tax evasion does not outweigh the potential costs, the
relationship between FPI flows and the interaction between Tax Savings and
TIEAs is negative for OECD host countries when FPI originates from tax haven
source countries.

H4c: If the benefit from tax evasion approximately equals its potential costs, the
relationship between FPI flows and the interaction between Tax Savings and
TIEAs is insignificant for OECD host countries when FPI originates from tax
haven source countries.

3. Data

Our final sample consists of 18,279 foreign portfolio investment flow (FPI) observations
from 160 source countries into 34 OECD host countries between 2002 and 2013.
Table A1 in the Appendix lists names of host and source countries, as well as tax havens.
We classify a country as a tax haven if it was included in the Harmful Tax Competition
report (OECD, 1998).23 Twenty-five of our source countries (16%) are considered tax
havens. We retain country pairs with at least three observations and equity flows of at
least USD 1 million.
Table A2 in the Appendix provides variable names, definitions and sources for all
variables. Our dependent variable is Log (FPI), the common logarithm of the foreign
portfolio investment a host country receives from each foreign source country in a given
year. We obtain foreign portfolio income (FPI) from the IMF Co-ordinated Portfolio
Flows Investment Survey Database (CPIS).
DTax Savings is the annual percentage change of tax savings computed for each
host-source country pair. Tax Savings is the difference between net dividend taxes and
the dividend withholding tax. Net dividend taxes are imposed by the host country on its
residents when a corporation declares dividends, and are based on corporate income
taxes and personal income taxes. Dividend withholding tax applies to foreign investors
and depends on whether a double taxation avoidance treaty exists or not. This variable is
computed for each host-source country pair for each year we observe this variable. We
obtain tax data from the American Enterprise Institute (AEI) International Tax Database
and KPMG Individual Tax Rate Survey.24
Distance is the geographic distance in kilometres (km) between two countries.
Common Language is a dummy variable equal to one if the source and host country speak
the same official language, and zero otherwise. The Distance parameter is obtained from
Mayer and Zignago (2011) and Common Language data are obtained from Melitz and
Toubal (2014). Legal systems for host countries and source countries are identified as
common law, civil law, Scandinavian law or German law (as in La Porta et al., 1998).
Identical Law System is a dummy variable equal to one if the host and source country
share the same legal system, and zero otherwise.
For Corruption, we use the Kaufmann et al. (2011) Worldwide Governance Index.
Specifically, we use Control of corruption, which captures perceptions of the extent to

23
Note, Hines and Rice (1994) also provide a similar list of tax havens.
24
To verify data accuracy, we compare similar tax rate data from other accounting firm
publications and find that our tax rates are consistent across these publications.

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Tax Havens, Tax Evasion and Tax Information Exchange Agreements 527

which public power is exercised for private gain, including both petty and grand forms of
corruption, as well as ‘capture’ of the state by elites and private interests.25 The values for
these indicators range from
2.5 (an indication of low control for corruption) to 2.5
(strong control for corruption), and are available annually in the World Bank database.
TIEAS is a dummy variable equal to one if the OECD source country has a TIEA
signed with a source country in a particular year and one year prior to signing, and zero
otherwise. The year prior to official signage is included in the signed group because
investors are already aware of upcoming new TIEAs when the agreement process is
started (Rixen and Schwarz, 2012). We obtain information on TIEAs from the OECD.26
DTAA is a dummy variable equal to one if the OECD host country has a double taxation
avoidance agreement signed with the source country, and zero otherwise. DTAA
information is obtained also from the OECD Exchange of Information Portal.27
We further control for the size of the economy since level of economic development
and population size also influence FPI. Numerous studies, e.g., Alfaro et al. (2004) and
Amaya and Rowland (2004), find foreign direct investments tend to move to large and
developed markets. We include Share of GDP, the host country’s GDP as a share of total
OECD GDP to measure the size of economy.28 We also control for the relative size
between source and host country. Relative GDP per Capita is the GDP per capita in the
host country relative to GDP per capita in the source country. GDP and population data
are obtained from the World Bank database.
Lastly, a country’s exchange rate also influences FPI. Prior literature shows that a
weaker US dollar is positively related to an increase in foreign direct investment into the
US.29 Non-US investors can reduce investment risk via international diversification, and
if the US currency is relatively cheap, the purchasing power of their home currency
allows them to purchase relatively more assets in the US. In our analysis, we expect that
FPI is positively related to relatively stronger currencies in the source countries. We
measure Relative Exchange Rate as host country exchange rate with respect to the US
dollar, relative to source country exchange rate with respect to the US dollar. Exchange
rate information is obtained from Thomson Reuters DataStream.

4. Model and Empirical Analysis

Our initial specifications to identify the round tripping effect are similar to Hanlon et al.
(2015). The main dependent variable is the equity flow from the source country to the
host country as measured by log (FPI). Since we are interested in the effects of the
OECD’s host country tax policy on equity flows to measure tax evasion, the main

25
See http://info.worldbank.org/governance/wgi/index.aspx#doc.
26
See http://www.oecd.org/tax/exchange-of-tax-information/taxinformationexchangeagree
mentstieas.htm.
27
See http://eoi-tax.org/jurisdictions/#default.
28
We considered several alternative measures of the size of the economy including log(GDP)
and log(GNI). These had very high variance inflation factors indicating multicolinearity with
other variables in the model. We also used host country’s GDP as a share of global GDP. Tthe
results are comparable to those we report.
29
See Froot and Stein (1991), Klein and Rosengren (1994) and Dewenter (1995) for the US,
and Johannesen (2014) for European countries.

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528 David M. Kemme, Bhavik Parikh and Tanja Steigner

independent variable for H1a is DTax Savings, and for H1b it is DTax Savings with tax
haven source countries. This interaction term is denoted as Source Tax Haven  DTax
Savings. We expect a positive sign for DTax Savings if round tripping exists (H1a), and a
positive sign for Source Tax Haven  DTax Savings if round tripping is more pervasive
via tax havens (H1b).
To test H2, Distance, Common Language, Identical Law System and Corruption are
the variables of interest when the equity flows originate from a tax haven. Therefore, we
interact each of these country characteristics with the source tax haven dummy variable.
The basic regression model, with additional variants reported below, is:

LogðFPIÞij;t ¼ b1 DTax Savingsi;t þ b2 Source Tax Havenj  DTax Savingsi;t

þ bK X i;j;t þ bL Source Tax Havenj  X i;j;t
þ Source Country Fixed Ef f ectsj þ Y ear Fixed Ef f ectst þ ei;j;t ð1Þ

All variables are defined as above and Xi,j,t is a vector of other determinants of FPI
flows (Share of GDP, Relative GDP per Capita, Relative Exchange Rate, Distance,
Common Language, Identical Law System and Corruption). bk and bL are vectors of the
corresponding coefficients of the variables in Xi,j. Here and henceforth, as indicated in
equation (1), we also add source country fixed effects and year fixed effects as a proxy for
unmeasured country and time characteristics and also to account for other potential
omitted variable bias.30 We estimate the model with source country and year fixed effects
and clustered standard errors to provide unbiased and consistent estimated standard
errors and appropriate coefficient test statistics.31
In addition to identifying the significant determinants of investment flows, we also
examine the impact of bilateral agreements on FPI in equation (2). We include DTAA to
test H3a, and we interact TIEA and DTAA with the source country tax haven dummy
variable to test H3b. Although Barber (2007), Sheppard (2009) and Kudrle (2008) are
sceptical of the usage of TIEAs as an effective mechanism of exchange of information
between a non-tax haven and a tax haven, Hanlon et al. (2015)32 find that TIEAs do
reduce FPI flows to the US from tax havens once they have been signed and ratified. We
add the interaction term TIEAS  Source Tax Haven  DTax Savings to test if benefits of
tax evasion are more pronounced than the associated costs (H4a), benefits are less
pronounced than costs (H4b), or if benefits and costs cancel each other out (H4c). The
dependent variable remains log (FPI). All other variables in equation (2) are as discussed
above. The basic regression equation is:

30
We considered including both source and host country fixed effects but this resulted in
significant multicollinearity problems. Since all host countries are OECD members and
thereby relatively homogeneous, we control for the fixed effects of the more heterogeneous
set of 160 source countries.
31
Clustered standard errors in the panel data setting yield unbiased and asymptotically (in the
number of cross sections) efficient standard errors (Peterson, 2009; Thompson, 2011). In a
previous version of this paper we also used Prais Winston and the results were similar.
32
Note that Hanlon et al. (2015) find significance for Tax Haven  TIEAS for their US source
country sample. However, since our source country sample is expanded to include all 34
OECD countries, there might be significant differences from country to country. We add
source country fixed effects to control for these and isolate the TIEAs impact.

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Tax Havens, Tax Evasion and Tax Information Exchange Agreements 529

LogðFPIÞij;t ¼ b1 TIEAS ij;t þ b2 Source Tax Havensj;t  TIEAS ij;t þ b3 DTAAij;t

þb2 Source Tax Havensj;t  DTAAij;t þ bK X i;j;t þ b5 DTax Savingsi;t
þb6 Source Tax Havensj;t  TIEAS ij;t  Tax Savingsi;t
þSource Country Ef f ectsj þ Y ear Fixed Ef f ectst þ ei;j;t ð2Þ

All variables and Xi,j,t are defined above and we use the same estimation technique.
5. Results

5.1. Round tripping and country characteristics

Table 1 reports the regression results for equation (1). The dependent variable is Log (FPI),
capturing equity flows from source country to host country. The primary variable of
interest for H1a is DTax Savings. If H1a holds and FPI increases with more tax savings,
then we expect this variable to have a positive coefficient. For H1b we focus on the
interaction between changes in tax savings and source country tax havens. If H1b holds
and FPI from tax havens increases with more tax savings, then we expect this interaction
term to have a positive coefficient. Specifications I-III in Table 1 indicate that the
coefficients for DTax Savings and the interaction term Source Tax Haven  DTax Savings
are consistently positive and statistically significant at the 5% or 1% level. This result
provides evidence for the existence of round tripping for OECD countries, i.e., investors
utilise offshore accounts for undetected reinvestment into the home capital market more
heavily as the home country’s tax burden increases. Round tripping is even more
pronounced via tax havens. Therefore, we find evidence supporting both H1a and H1b.
Further, Relative Exchange Rate is negatively related to FPI, and statistically significant
for all models. This result implies that, in general, the stronger the source country currency
relative to the host country, the more FPI flows into the host country. This makes sense as
the FPI becomes less expensive for the source country when its currency is stronger. Share
of GDP and Relative GDP per Capita are positive and statistically significant across all
specifications. Therefore, the larger the economy and the greater GDP per capita in the
host country relative to the source country, the higher is the level of FPI.
To expand our test for tax evasion and evaluate how important country characteristics
are for tax evaders, we examine the impact of Distance, Common Language, Identical
Law System and Corruption on the level of FPI. Confirming prior empirical studies,
Specifications II and III show that Distance is significantly negatively related to FPI
overall, while Common Language, Identical Law System and Corruption are
significantly positively related to FPI. However, Specification III shows that these
country characteristics are less important when equity flows originate from tax havens, as
Distance, Identical Law System and Corruption interacted with Source Tax Haven have
coefficients with the opposite sign and are statistically significant. We therefore confirm
H2a, H2c and H2d. For H2b, the interaction of Tax Haven and Common Language is not
statistically significant.33 These results provide new insights, clearly illustrating that tax
evaders differ from genuine investors by focusing on tax benefits, greater physical
distance, as well as legal differences and more corruption which makes collaboration
between tax authorities more challenging.
33
The variance inflation factors indicate our results are not due to multicollinearity.

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530 David M. Kemme, Bhavik Parikh and Tanja Steigner

Table 1
Regression analysis for round tripping

This table reports the analysis for round tripping. The dependent variable is the logarithm of equity flows
and our main independent variable is the interaction between source tax haven and percentage changes in
tax savings. Specification I presents the analysis for our base case, Specification II introduces important
shared macroeconomic variables between the host and the source country, and Specification III interacts
each of the control variables with source tax haven to distinguish features of source countries, which are
classified as tax haven and non-tax havens. All the variables are defined in Table A2 of the Appendix.
Estimation is with source fixed effects and year fixed effects. Standard errors are clustered by source
countries. Standard errors are in parentheses.  ,  ,  indicates statistical significance at 1%, 5% and 10%
level, respectively.

Variables I II III
 
D Tax Savings 0.0001 0.0001 0.0001
(0.000) (0.000) (0.000)
Source Tax Haven  D Tax Savings 0.0091 0.0095 0.0092
(0.004) (0.003) (0.003)
Relative Exchange Rate –0.0002 –0.0002 –0.0002
(0.000) (0.000) (0.000)
Share of GDP 11.4239 12.9199 13.0141
(0.172) (0.179) (0.178)
Relative GDP per Capita 0.0190 0.0096 0.0102
(0.001) (0.001) (0.001)
Distance (KM) –0.0120 –0.0125
(0.000) (0.000)
Common Language 0.7763 0.8267
(0.000) (0.137)
Identical Law System 0.4936 0.5882
(0.033) (0.035)
Corruption 1.4606 1.5061
(0.024) (0.026)
Source Tax Haven  Distance 0.0025
(0.001)
Source Tax Haven  Common Language 0.0232
(0.103)
Source Tax Haven  Identical Law System –0.6151
(0.098)
Source Tax Haven  Corruption –0.2243
(0.056)
Source Fixed Effects Yes Yes Yes
Year Fixed Effects Yes Yes Yes
No. of Observations 18,279 18,279 18,279
Adjusted R Square 0.9887 0.9915 0.9915

5.2. Tax information exchange agreements and double taxation avoidance agreements
Table 2 reports the results for equation (2) related to tax information exchange
agreements. For H3a, the results confirm that double taxation agreements between
countries are attractive for investors, in general, and therefore positively related to FPI.
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Tax Havens, Tax Evasion and Tax Information Exchange Agreements 531

Table 2
Regression Analysis for Tax Information Exchange Agreement (TIEAS) and Double Taxation
Avoidance Agreements (DTAA)

This table reports the analysis for effects of equity flows between host and source country due to the
signing of tax agreements between host and source countries. The dependent variable is the logarithm of
equity flows and our main independent variable is the interaction between Source Tax Haven and
TIEAS, and Source Tax Haven and DTAA. Specification I presents the analysis for our base case,
Specification II introduces some important shared macroeconomic variables between the host and the
source country, and Specification III adds the importance of round tripping and signing of TIEAs. All
variables are defined in Table A2 of the Appendix. Estimation is with source fixed effects and year fixed
effects. The standard errors are clustered by source countries. Standard errors are in parentheses.  ,  ,

indicates statistical significance at 1%, 5% and 10% level, respectively.

Variables I II III

TIEAS 1.5568 –0.1687 –0.1700
(0.135) (0.121) (0.120)
Source Tax Haven  TIEAS –1.0172 –0.2410 –0.2642
(0.182) (0.171) (0.171)
DTAA 0.4414 0.4349 0.4671
(0.154) (0.0498) (0.135)
Source Tax Haven  DTAA –0.0007 –0.0123 0.0009
(0.129) (0.111) (0.233)
Relative Exchange Rate –0.0016 –0.0001 –0.0009
(0.000) (0.000) (0.000)
Share of GDP 11.2577 13.0347 13.0347
(0.170) (0.177) (0.177)
Relative GDP per Capita 0.0195 0.0099 0.0098
(0.001) (0.000) (0.001)
Distance –0.0119 –0.0119
(0.000) (0.000)
Common Language 0.7499 0.7505
(0.436) (0.043)
Identical Law System 0.5107 0.5117
(0.114) (0.033)
Corruption 1.4923 1.4926
(0.023) (0.023)
TIEAS  Source Tax Haven  D Tax Savings 0.0238
(0.008)
D Tax Savings 0.0001
(0.000)
Source Tax Haven  D Tax Savings 0.0037
(0.005)
Source Fixed Effects Yes Yes Yes
Year Fixed Effects Yes Yes Yes
No. of Observations 18,276 18,276 18,276
Adjusted R Square 0.9888 0.9916 0.9922

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532 David M. Kemme, Bhavik Parikh and Tanja Steigner

Specification II, which is most similar to Hanlon et al.’s (2015), confirms their result
that FPI flows from tax havens decrease when TIEAs are signed. However, neither
TIEAs nor DTAAs influence FPI flows that originate from tax havens once we
control for other determinants of FPI flows. Therefore, our findings support H3b,
suggesting that information exchange agreements do not deter investors from evading
taxes. Similar to Johannesen and Zucman (2014), we find that OECD policy is not
effective.
Specification III allows us to test H4, where we examine the interplay between the
risk and benefit of tax evasion by adding the interaction term TIEAS  Source Tax
Haven  DTax Savings. We find that although the signing of TIEAs with tax havens
has no impact on FPI flows to OECD countries, this impact becomes significantly
positive when tax savings is included. The evidence therefore suggests that equity
flows from tax havens increase with greater tax savings even if TIEAs are signed with
tax havens. In support of H4a, we conclude that round tripping exists despite TIEAs,
and that investors therefore perceive potential gains from tax evasion to outweigh
potential costs from being caught.

5.3. Additional robustness checks

The US is an OECD member and prior research has indicated that there is round
tripping for US investors. To ensure that the US does not dominate the results in our
OECD host country sample, we repeat the regression analysis excluding the US from
the OECD host country sample in Tables 3 and 4. This isolates the effects of FPI into
the US to ensure that our findings are not influenced by the largest economy in the
OECD group. Table 3 indicates that round tripping exists for the remaining OECD
countries. In support of H1a the coefficient for DTax Savings continues to be positive
and statistically significant for all specifications. H1b, greater round tripping from tax
havens, is supported in specification I only. Once we control for other country
characteristics, in specifications II and III, round tripping via tax havens is no longer
more pronounced than round tripping for the overall sample. The preference for tax
havens, therefore, was mainly driven by the US as a host country. Also controlling for
other country variables, we still find support for H2c and H2d, indicating that different
legal systems and greater corruption increase FPI flows from tax havens. However,
distance no longer has a different impact on tax havens as was the case for the entire
sample.
With regard to TIEAs and DTAAs, Table 4 shows continued support for H3a, whereby
DTAAs increase FPI flows. Table 4 further provides evidence (10% level of
significance) that TIEAs reduce FPI flow from tax havens once we control for country
characteristics (specifications II and III). Therefore, the results provide evidence for H3b
that OECD policies might be effective for their member states when the US is excluded.
Also consistent with the earlier findings, when the US is excluded and controlling for
other determinants, we find no statistically significant effect of signing a TIEA on round
tripping. Without the US we still find evidence that supports H4b. TIEAs reduce FPI
flows from tax havens, and this result is not different even if the investor could benefit
from tax savings. We conclude, that the cost of detection must still be perceived to be
greater than the benefits from tax savings.
Since our sample includes the global recession years of 2008–2009, we want to
confirm that our results are not sensitive to the unique macroeconomic conditions of that

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Tax Havens, Tax Evasion and Tax Information Exchange Agreements 533

Table 3
Regression analysis for round tripping without US host country observations

This table reports the analysis for round tripping excluding the US as a host country. The dependent
variable is the logarithm of equity flows and our main independent variable is the interaction between
Source Tax Haven and D Tax Savings. Specification I presents the analysis for our base case.
Specification II introduces some important shared macroeconomic variables between the host and the
source country. And Specification III interacts each of the control variables with Source Tax Haven to
distinguish features of source countries, which are classified as tax havens and non-tax havens. All the
variables are defined in Table A2 of the Appendix. Estimation is with source fixed effects and year fixed
effects. The standard errors are clustered by source country. Standard errors are in parentheses.  ,  , 
indicate statistical significance at 1%, 5% and 10% levels, respectively.

Variables I II III
 
D Tax Savings 0.0001 0.0001 0.0001
(0.000) (0.000) (0.000)
Source Tax Haven  D Tax Savings 0.0058 0.0043 0.0040
(0.003) (0.003) (0.003)
Relative Exchange Rate –0.0016 –0.0001 –0.0001
(0.000) (0.000) (0.000)
Share of GDP 14.5662 18.2560 18.2972
(0.338) (0.302) (0.302)
Relative GDP per Capita 0.0214 0.0126 0.0131
(0.001) (0.001) (0.001)
Distance –0.0132 –0.0133
(0.000) (0.000)
Common Language 0.9924 1.0894
(0.044) (0.048)
Identical Law System 0.4918 0.5678
(0.033) (0.036)
Corruption 1.5178 1.5588
(0.022) (0.025)
Source Tax Haven  Distance 0.0006
(0.001)
Source Tax Haven  Common Language –0.16380
(0.107)
Source Tax Haven  Identical Law System –0.5079
(0.099)
Source Tax Haven  Corruption –0.2121
(0.054)
Source Fixed Effects Yes Yes Yes
Year Fixed Effects Yes Yes Yes
No. of Observations 17,215 17,215 17,215
Adjusted R Square 0.9887 0.9920 0.9920

period when there was a major selloff of equities. We re-estimate all specifications from
Tables 1 and 2 without these two years. Tables 5 and 6 report that our findings for round
tripping and TIEAs, respectively, remain valid.

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534 David M. Kemme, Bhavik Parikh and Tanja Steigner

Table 4
Regression analysis for Tax Information Exchange Agreement (TIEAS) and Double Taxation
Avoidance Agreements (DTAA) without US host country observations

This table reports the analysis for effects of equity flows between host and source country due to signing
of tax agreements between host and source countries. We remove observations pertaining to US as a
host country. The dependent variable is the logarithm of equity flows and our main independent variable
is the interaction between Source Tax Haven and TIEAS, and Source Tax Haven and DTAA.
Specification I presents the analysis for our base case, Specification II introduces some important shared
macroeconomic variables for the host and the source country, and Specification III introduces the
importance of round tripping and TIEAs. All variables are defined in Table A2 of the Appendix.
Estimation is with source fixed effects and year fixed effects. The standard errors are clustered by source
country. Standard errors are in parentheses.  ,  ,  indicates statistical significance at 1%, 5% and
10% levels, respectively.

Variables I II III

TIEAS 2.0160 0.1516 0.1509
(0.157) (0.125) (0.125)
Source Tax Haven  TIEAS –1.3824 –0.3035 –0.3134
(0.206) (0.175) (0.176)
DTAA 0.3333 0.3109 0.3108
(0.058) (0.050) (0.050)
Source Tax Haven  DTT 0.0771 0.0768 0.0764
(0.135) (0.115) (0.116)
Relative Exchange Rate –0.0016 –0.0001 –0.0001
(0.000) (0.000) (0.000)
Share of GDP 14.9496 18.1415 18.1346
(0.337) (0.461) (0.301)
Relative GDP per Capita 0.0222 0.0129 0.0129
(0.001) (0.001) (0.000)
Distance –0.0130 –0.0129
(0.000) (0.000)
Common Language 0.9648 0.9645
(0.044) (0.044)
Identical Law System 0.4900 0.4906
(0.034) (0.034)
Corruption 1.5325 1.5326
(0.023) (0.023)
TIEAS  Source Tax Haven  D Tax Savings 0.0087
(0.008)
D Tax Savings 0.0001
(0.000)
Source Tax Haven  D Tax Savings 0.0014
(0.005)
Source Fixed Effects Yes Yes Yes
Year Fixed Effects Yes Yes Yes
No. of Observations 17,212 17,212 17,212
Adjusted R Square 0.9889 0.9920 0.9920

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Tax Havens, Tax Evasion and Tax Information Exchange Agreements 535
Table 5
Robustness analysis for round tripping without recession year (2008 and 2009) data

This table reports the analysis for round tripping after removing observations belonging to global
recession years 2008 and 2009. The dependent variable is the logarithm of equity flows and our main
independent variable is the interaction between Source Tax Haven and D Tax Savings. Specification I
presents the analysis for our base case. Specification II introduces some important shared
macroeconomic variables between the host and the source country, and Specification III interacts
each of the control variables with Source Tax Haven to distinguish features with source countries,
which are classified as tax haven and non-tax haven. All variables are defined in Table A2 of the
Appendix. Estimation is with source fixed effects and year fixed effects. The standard errors are
clustered by source country. Standard errors are in parentheses.  ,  ,  indicates statistical
significance at 1%, 5% and 10% levels, respectively.

Variables I II III
 
D Tax Savings 0.0001 0.0001 0.0001
(0.000) (0.000) (0.000)
Source Tax Haven  D Tax Savings 0.0086 0.0098 0.0092
(0.004) (0.003) (0.003)
Relative Exchange Rate –0.0017 –0.0002 –0.0003
(0.000) (0.000) (0.000)
Share of GDP 11.3896 12.7918 12.8867
(0.188) (0.196) (0.195)
Relative GDP per Capita 0.0182 0.0090 0.0097
(0.001) (0.001) (0.001)
Distance –0.0121 –0.0125
(0.000) (0.001)
Common Language 0.7637 0.8237
(0.048) (0.053)
Identical Law System 0.4840 0.5762
(0.037) (0.039)
Corruption 1.4712 1.5225
(0.026) (0.029)
Source Tax Haven  Distance 0.0026
(0.001)
Source Tax Haven  Common Language –0.0182
(0.114)
Source Tax Haven  Identical Law System –0.5900
(0.109)
Source Tax Haven  Corruption –0.2560
(0.063)
Source Fixed Effects Yes Yes Yes
Year Fixed Effects Yes Yes Yes
No. of Observations 15,048 15,048 15,048
Adjusted R Square 0.9886 0.9914 0.9914

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536 David M. Kemme, Bhavik Parikh and Tanja Steigner

Table 6
Robustness analysis for Tax Information Exchange Agreement (TIEAS) and Double Taxation
Avoidance Agreement (DTAA) without recession year (2008 and 2009) data

This table reports the analysis for effects of equity flows between host and source country due to signing
of tax agreements between host and source countries. We remove the observations belonging to
year 2008 and 2009, which coincides with the global recession period. The dependent variable is the
logarithm of equity flows and our main independent variable is the interaction between Source Tax
Haven and TIEAS, and Source Tax Haven and DTAA. Specification I presents the analysis for our base
case, Specification II introduces some important shared macroeconomic variables between the host and
the source country, and Specification III introduces the importance of round tripping over signing of tax
agreements. All variables are defined in Table A2 of the Appendix. Estimation is with source fixed
effects and year fixed effects. The standard errors are clustered by source country. Standard errors are in
parentheses.  ,  ,  indicates statistical significance at 1%, 5% and 10% levels, respectively.

Variables I II III

TIEAS 1.5258 –0.1992 –0.2010
(0.150) (0.135) (0.135)
Source Tax Haven  TIEAS –1.0628 –0.2519 –0.2838
(0.203) (0.191) (0.192)
DTAA 0.4391 0.4250 0.4248
(0.062) (0.055) (0.055)
Source Tax Haven  DTAA 0.0117 0.0118 0.0108
(0.143) (0.123) (0.123)
Relative Exchange Rate –0.0017 –0.0002 –0.0002
(0.000) (0.000) (0.000)
Share of GDP 11.2302 12.9107 12.9154
(0.187) (0.194) (0.194)
Relative GDP per Capita 0.0188 0.0093 0.0092
(0.001) (0.001) (0.001)
Distance –0.0119 –0.0119
(0.000) (0.000)
Common Language 0.7381 0.7389
(0.114) (0.048)
Identical Law System 0.5008 0.5021
(0.037) (0.037)
Corruption 1.5030 1.5034
(0.026) (0.026)
TIEAS  Source Tax Haven  D Tax Savings 0.0188
(0.005)
D Tax Savings 0.0001
(0.000)
Source Tax Haven  D Tax Savings 0.0036
(0.005)
Source Fixed Effects Yes Yes Yes
Year Fixed Effects Yes Yes Yes
No. of Observations 15,045 15,045 15,045
Adjusted R Square 0.9887 0.9915 0.9915

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Tax Havens, Tax Evasion and Tax Information Exchange Agreements 537

6. Conclusion
Our findings add to both the tax haven and investments literature. We shed light on tax
havens and their significant role in foreign portfolio investment flows. Specifically,
we provide empirical evidence that OECD residents are more inclined to preserve
wealth when the amount of tax savings via round tripping increases. Round tripping
via a tax haven is even more pronounced. This result suggests that OECD residents
value the confidentiality of tax havens, as suggested by the IMF (2004), which makes
detection of the sheltered wealth by the home tax authorities more challenging.
Interestingly, once the US is removed from the OECD sample, the general round
tripping evidence persists but the effect of tax havens on round tripping is no longer
significant.
In line with the investment literature, we find that investors, in general, value close
proximity and similarity in language, legal systems and country governance when
investing overseas. While these country characteristics reduce costs for the genuine
investor, they are not desirable for tax evaders who want to increase the level of difficulty
of detection. We therefore find that distance, identical legal system and control of
corruption are significantly less important when foreign portfolio investment originates
from tax havens. Without the US flows, distance is no longer significant when FPI
originate from tax havens. However, the other country characteristics remain significant
even after excluding the US from the OECD sample.
We also investigate the effectiveness of OECD policy in preventing tax evasion. In
their battle against government revenue losses, the OECD is committed to compel
countries to sign Tax Information Exchange Agreements (TIEAs). TIEAs are
intended to overcome bank secrecy laws and other obstacles that prevent home tax
authorities from collecting information on law breaking residents. Alternatively, tax
information sharing may also be negotiated in double taxation avoidance agreements
(DTAAs). We find that, in general, investors value DTAAs, and more FPI flows into
the OECD when such agreements are signed. More importantly though, we show that
both TIEAs and DTAAs do not prevent tax evasion. The signing of either agreement
with a tax haven has no impact on overall OECD FPI flows. This potential
ineffectiveness of OECD policy is further illustrated when we examine the impact of
TIEAs on round tripping directly. We find that tax evaders continue to view tax saving
benefits as more rewarding than the potential costs of detection. However, once the
US is removed from the OECD sample, we find weak evidence (10% level of
significance) that OECD policies might be effective for the rest of the OECD, as
signing of TIEAs is now related to less FPI flows from tax havens even if tax saving
benefits exist.7
Our findings remain valid and are robust controlling for country and year fixed effects,
cross-sectional source country correlation, as well as potential effects of the global
financial crisis.
Our results suggest that varying tax policies, which yield significant tax savings for
capital income based on host country domicile, provide strong incentives for tax evasion
via tax havens. These incentives remain so large that policies designed to thwart evasion,
such as TIEAs, have little effect on deterrence. Even without the US in the sample,
benefits of TIEAs are only marginally significant. Given the limited effectiveness and
potentially significant compliance costs the natural course would be to harmonise tax
policies to eliminate the tax savings from such behaviour.

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538 David M. Kemme, Bhavik Parikh and Tanja Steigner

Appendix

Table A1
Host countries, source countries and tax haven countries in our sample
Host Countries Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark,
Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland,
Israel, Italy, Japan, South Korea, Luxembourg, Mexico, Netherlands,
New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia,
Spain, Sweden, Switzerland, Turkey, United Kingdom, United States
Source Countries Afghanistan, Albania, Algeria, Andorra, Angola, Anguilla, Antigua and
Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas,
Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Bermuda,
Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Bulgaria, Burkina
Faso, Cape Verde, Cambodia, Cameroon, Canada, Cayman Islands,
Chile, Hong Kong, China, Colombia, Democratic Republic of Congo,
Republic of Congo, Costa Rica, Cote d’Ivoire, Croatia, Curacao,
Cyprus, Czech Republic, Denmark, Dominica, Dominican Republic,
Ecuador, Egypt, El Salvador, Equator Guinea, Estonia, Ethiopia,
Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece,
Grenada, Guatemala, Guinea, Guinea – Bissau, Guyana, Hungary,
Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica,
Japan, Jordan, Kazakhstan, Kenya, South Korea, Kuwait, Republic of
Kyrgyz, Laos, Latvia, Lebanon, Liberia, Libya, Lithuania, Luxembourg,
Macedonia, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta,
Mauritania, Mauritius, Mexico, Moldova, Mongolia, Montenegro,
Morocco, Mozambique, Namibia, Nepal, Netherlands, New Zealand,
Nicaragua, Niger, Nigeria, Norway, Oman, Pakistan, Panama, Papua
New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Puerto
Rico, Qatar, Romania, Russia Federation, Rwanda, Saudi Arabia,
Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovak Republic,
Slovenia, South Africa, Spain, Sri Lanka, St Kitts and Nevis, St Vincent
and Grenadines, Swaziland, Sweden, Switzerland, Taiwan, Tanzania,
Thailand, Togo, Trinidad and Tobago, Tunisia, Turkey, Uganda,
Ukraine, United Arab Emirates, United Kingdom, United States,
Uruguay, Uzbekistan, Venezuela, Vietnam, Yemen, Zambia, Zimbabwe
Tax Havens Anguilla, Antigua and Barbuda, Bahamas, Bahrain, Barbados, Belize,
Bermuda, Cayman Islands, Hong Kong, Cyprus, Dominica, Grenada,
Ireland, Jordan, Lebanon, Liberia, Luxembourg, Maldives, Mauritius,
Panama, Seychelles, Singapore, St. Kitts and Nevis, St. Vincent and
Grenadines, Switzerland

Table A2
Description of Variables and Sources

Variable Description Source

Ln (Equity Flows) Logarithm of equity flow from source IMF (2014)
country, which is the country of origin,
to a host country, which is the intended
destination. It is in millions of USD.

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Tax Havens, Tax Evasion and Tax Information Exchange Agreements 539

Table A2
Continued

Variable Description Source

Tax Savings The difference between the host country OECD, AEI, KPMG,
net dividend taxes and dividend Deloitte
withholding taxes which is applicable to
foreign investors based on whether a
double taxation treaty exists or not.
DTax Savings The percentage change in tax savings over
the previous year.
TIEAS Tax Information Exchange Agreement OECD
(TIEAs) dummy taking the value 1 when
an agreement exists between host and
source country. It also takes the value 1
in the year prior to signing of the
agreement.
DTAA Double taxation avoidance agreement OECD
dummy taking the value 1 when an
agreement exists, and 0 otherwise.
Common Language Dummy variable taking the value 1 when Melitz and Toubal (2014)
both host and source countries share a
common language, and 0 otherwise.
Identical Law Dummy variable taking the value 1 when La Porta et al. (1998)
System both host and source countries follow a
similar law system; common law, civil
law, Scandinavian law or German law.
Distance Distance between two capital cities or two Mayer and Zignago (2011)
financial centres measured in km.
Relative Exchange The ratio of host country exchange rate Thomson Reuters
Rate measured in dollars to source country Datastream
exchange rate measured in dollars.
Relative GDP per The ratio of GDP per capita of host country Worldbank
Capita over the GDP per capita of source
country.
Share of GDP The ratio of host country GDP to total GDP Worldbank
of all OECD economies
Corruption Extent to which elites and private interests Kaufmann et al. (2011)
exercise public power for private gain,
including both petty and grand forms of
corruption, as well as ‘capture’ of the state.
The score ranges between 2.5 and
2.5.
Source Tax Haven Dummy variable taking the value of 1 if Hines and Rice (1994) and
country of origination of flows is Harmful Tax Competition
considered a tax haven, and 0 otherwise. report (OECD, 1998)

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540 David M. Kemme, Bhavik Parikh and Tanja Steigner

References

Abdioglu, N., Khurshed, A., and Stathopoulos K., ‘Foreign institutional investment: Is governance
quality at home important?’ Journal of International Money and Finance, Vol. 32, 2013, pp. 916–40.
Aggarwal, R., Kearney, C. and Lucey, B. ‘Gravity and culture in foreign portfolio investment’. Journal
of Banking & Finance, Vol. 36, 2012, pp. 525–38.
Alfaro, L., Chanda, A., Kalemli-Ozcan, S. and Sayek, S., ‘FDI and economic growth: the role of local
financial markets’, Journal of International Economics, Vol. 64, 2004, pp. 89–112.
Amaya, C. A. and Rowland, P., Determinants of Investment Flows into Emerging Markets, Working
Paper No. 313 (Banco de la Republica de Colombia).
Becker, G. S., ‘Crime and punishment: An economic approach’, Journal of Political Economy, Vol. 76
1968, pp. 169–217.
Ball, J. and Neate, R., ‘100 of UK’s richest people concealing billions in offshore tax havens’, The
Guardian, 2013. Available online at: http://www.theguardian.com/politics/2013/may/09/100-
richest-uk-billions-offshore-tax-havens.
Bacchetta, P. and Paz Espinosa, M-P., ‘Exchange of information clauses in international taxes’,
International Tax and Public Finance, Vol. 7, 2000, pp. 275–93.
Barthel, F., Busse, M. and Neumayer, E., ‘The impact of double taxation treaties on foreign direct
investment: Evidence from large dyadic panel data’, Contemporary Economic Policy, Vol. 28, 2010,
pp. 366–77.
Barber, H., 2007, Tax Havens Today: The Benefits and Pitfalls of Banking and Investing Offshore (New
Jersey, John Wiley & Sons, Inc, 2007).
CBC News, ‘KPMG Offshore ‘Sham’ Deceived Tax Authorities, CRA Alleges’, CBC News, 9
September 2015. Available online at: http://www.cbc.ca/news/business/kpmg-offshore-sham-
deceived-tax-authorities-cra-alleges-1.3209838. Last accessed: 15 December 2015.
CBC News, ‘UK Arrests 4 KPMG Executives on Tax Evasion Charges’, CBC News, 27 November
2015. Available online at: http://www.cbc.ca/news/business/kpmg-tax-evasion-charges-1.3339719
Last accessed: 15 December 2015.
Chan, K., Covrig, V. and Ng, L., ‘What determines the domestic bias and foreign bias? Evidence from
mutual fund equity allocations worldwide’, The Journal of Finance, Vol. 60, 2005, pp. 1495–534.
Coats, W., ‘Operation Choke Point’, Cayman Financial Review. 24 May 2016. Available online at:
http://www.caymanfinancialreview.com/2016/05/24/operation-choke-point/
Council Directive 2003/48/EC, ‘Proposal for a council directive amending directive 2003/48/EC on
taxation of savings income in the form of interest payments’, 2003. Available online at: http://eur-lex.
europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52015PC0129
Dagan, T., ‘Just harmonization’, UBCL Review, Vol. 42, 2009, p. 331.
Dermine, J., ‘European banking integration, ten years after’, European Financial Management, 1996,
Vol. 2, 331–53.
Dewenter, K. L., ‘Do exchange rate changes drive foreign direct investment?’ Journal of Business, Vol.
68, 1995, pp. 405–33.
Dharmapala, D., (2008) ‘What problems and opportunities are created by tax havens?’ Oxford Review
of Economic Policy, Vol. 24, 2008, pp. 661–79.
European Community, ‘Council directive 2003/48/EC of 3 June 2003 on taxation of savings income in
the form of interest payments’, Official Journal, Vol. L, 2003, pp. 38–48.
Fonte G., Mackenzie, J. and Trevelyan, M., Italy, Switzerland Near Accord On Tax Information
Sharing, Reuters, 15 January 2015. Available online at: http://uk.reuters.com/article/uk-italy-swiss-
tax-idUKKBN0KO1UI20150115
Froot, K. A., and Stein, J. C., ‘Exchange rates and foreign direct investment: an imperfect capital
markets approach’, The Quarterly Journal of Economics, Vol. 106, 1991, pp. 1191–217.
Gaston Gelos, R. and Wei, S. J., ‘Transparency and international portfolio holdings’, Journal of
Finance, Vol. 60, 2005, pp. 2987–3020.

© 2017 The Authors. European Financial Management Published by John Wiley & Sons Ltd
 1468036x, 2017, 3, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/eufm.12118 by Le Centre National, Wiley Online Library on [20/09/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
Tax Havens, Tax Evasion and Tax Information Exchange Agreements 541

Griffith, J., Financing for Development: Key Challenges for Policy Makers (European Network of Debt
and Development (Eurodad), 2015). Available online at: http://www.eurodad.org/files/pdf/1546457-
financing-for-development-key-challenges-for-policy-makers.pdf
Grinblatt, M. and Keloharju, M., ‘How distance, language, and culture influence stockholdings and
trades’, Journal of Finance, Vol. 56, 2001, pp. 1053–73.
Guiso, L. Sapienza, P. and Zingales, L., ‘Cultural biases in economic exchange’, Quarterly Journal of
Economics, Vol. 124, 2009, pp. 1095–131.
Halliday, T., Levi, M. and Reuter, P., Global Surveillance of Dirty Money: Assessing Assessments of
Regimes to Control Money Laundering and Combat the Financing of Terrorism (Center for Law and
Globalization, American Bar Foundation and University of Illinois College of Law, 2014).
Hanlon, M., Maydew, E. L. and Thornock, J. R., (2015) ‘Taking the long way home: US tax evasion and
offshore investments in US equity and debt markets’, The Journal of Finance, Vol. 70, 2015, pp.
257–87.
Henry, J. S., ‘The Price of Offshore Revisited’, Tax Justice Network, 2012. Available online at: http://
www.taxjustice.net/cms/upload/pdf/Price_of_Offshore_Revisited_120722.Pdf.
Hines, Jr., J. and Rice, E., ‘Fiscal paradise: Foreign tax havens and American business’, Quarterly
Journal of Economics, 1994, Vol. 109, pp. 149–82.
IMF Committee on Blance of Payments Statistics and OECD workshop on International Investment
Statistics, Round Tripping (Washington, DC: IMF, 2004). Available online at: https://www.imf.org/
External/NP/sta/bop/pdf/diteg13.pdf (Last accessed: 16 May 2016).
IMF, Revision of the Balance of Payments Manual, Fifth Edition (Washington, DC: IMF, 2014).
Internal Revenue Service, Federal Income Tax Withholding and Reporting on Other Kinds of U.S.
Source Income Paid to Nonresident Aliens. (Washington, DC: IRS, 2016). Available online at:
https://www.irs.gov/individuals/international-taxpayers/federal-income-tax-withholding-and-
reporting-on-other-kinds-of-u-s-source-income-paid-to-nonresident-aliens.
Internal Revenue Service, International Investigations - Criminal Investigation (Washington, DC: IRS,
2015). Available online at: https://www.irs.gov/uac/International-Investigations-Criminal-
Investigation-(CI).
Johannesen, N., (2014) ‘Tax evasion and Swiss bank deposits’, Journal of Public Economics, Vol. 111,
2014, pp. 46–62.
Johannesen, N. and Zucman, G., (2014). ‘The end of bank secrecy? An evaluation of the G20 tax haven
crackdown’, American Economic Journal: Economic Policy, Vol. 6, 2011, pp. 65–91.
Kaufmann, D., Aart K. and Mastruzzi, M., ‘The worldwide governance indicators: Methodology and
analytical issues’, Hague Journal on the Rule of Law, Vol. 3, 2011, pp. 220–46.
Klein, M. W. and Rosengren, E., ‘The real exchange rate and foreign direct investment in the United
States: Relative wealth vs. relative wage effects’, Journal of International Economics, Vol. 36, 1994,
pp. 373–89.
KPMG, Anti-bribery and corruption:Rising to the challenge in the age of globalization, KPMG
International Cooperative, 2015. Available online at: https://home.kpmg.com/content/dam/kpmg/
pdf/2016/06/tr-anti-bribery-corruption-survey-2015.pdfc
Kudrle, R. T., ‘The OECD’s harmful tax competition initiative and the tax havens: from bombshell to
damp squib’, Global Economy Journal, Vol. 8, 2008, pp. 1–23.
Lane, P. and Milesi-Ferretti, G., ‘The external wealth of nations mark II: Revised and extended
estimates of foreign assets and liabilities, 1970–2004’, Journal of International Economics. Vol. 73,
2007, pp. 223–50.
La Porta, R., Lopez-de-Silanes, F., Shleifer, A. and Vishny, R. W., ‘Law and finance’, Journal of
Political Economy, Vol. 106, 1998, pp. 1113–55.
Logutenkova, E. and Vogeli, J., Swiss Banks Try to Keep Italian Clients After Tax Deal, Bloomberg, 25
February 2015. Available online at: http://www.bloomberg.com/news/articles/2015-02-25/swiss-
banks-try-to-keep-italian-clients-after-tax-deal-is-signed.
Mayer, T. and Zignago, S., ‘Notes on CEPII’s distances measures: the GeoDist Database’, CEPII
Working Paper 2011–25, 2011.

© 2017 The Authors. European Financial Management Published by John Wiley & Sons Ltd
 1468036x, 2017, 3, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/eufm.12118 by Le Centre National, Wiley Online Library on [20/09/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
542 David M. Kemme, Bhavik Parikh and Tanja Steigner

Melitz, J., and Toubal, F., ‘Native language, spoken language, transition and trade’, Journal of
International Economics, Vol. 92-2, 2014, pp. 351–63.
Organisation for Economic Co-operation and Development, Harmful Tax Competition: An Emerging
Global Issue (Paris: OECD, 1998).
OECD, Agreement on the Exchange of Information on Tax Matters (Paris: OECD, 2002a). Available
online at: https://www.oecd.org/ctp/harmful/2082215.pdf. Last accessed: 28 June 2016.
OECD, Tax Transparency 2015, Report on Progress (Paris: OECD, 2002b). Available online at: .
http://www.oecd.org/tax/transparency/global-forum-annual-report-2015.pdf. Last accessed: 28 June
2016.
OECD, Exchange of Information portal (Paris: OECD, 2002). Available online at: http://www.oecd.
org/tax/exchange-of-tax-information/. Last accessed: 17 December 2015.
Palan, R. and Nesvetailova, A., ‘The governance of black holes of the world economy: Shadow banking
and offshore finance’, CITYPERC Working Paper Series No. 2013/03 (City University London,
2013). Available online at: http://papers.ssrn.com/sol3/papers.cfm?abstract_id¼2216795.
Palan, R., Murphy, R. and Chavagneux, C., Tax Havens: How Globalization Really Works (Ithaca:
Cornell University Press, 2010).
Peterson, M. A., ‘Estimating standard errors in finance panel data sets: Comparing approaches’, Review
of Financial Studies, Vol. 22, 2009, pp. 435–80.
Rixen, T. and Schwarz, P., ‘How effective is the European Union’s savings tax directive? Evidence
from four EU member states’, Journal of Common Market Studies, Vol. 50, 2012, pp. 151–68.
Sheppard, L., ‘Don’t ask, don’t tell, Part 4: Ineffectual information sharing’, Tax Notes, 2009, pp.
1411–18.
Slemrod, J., ‘Cheating ourselves: the economics of tax evasion’, Journal of Economic Perspectives,
Vol. 21, 2007, pp. 25–48.
The Canadian Press, Canadian Money Stowed In Tax Havens Reaches Record $170 Billion. (Montreal,
The Canadian Press, 2014). Available online at: http://www.huffingtonpost.ca/2014/05/02/
canadians-use-of-tax-havens_n_5253902.html
Thompson, S. B., ‘Simple formulas for standard errors that cluster by both firm and time’, Journal of
Financial Economics, Vol. 99, 2011, pp. 1–10.
Wei, S. J. and Shleifer, A., ‘Local corruption and global capital flows’, Brookings Papers on Economic
Activity, Vol. 31, 2000, pp. 303–46.
Zucman, G., ‘The missing wealth of nations: Are Europe and the U.S. net debtors or net creditors?’
Quarterly Journal of Economics, Vol. 128, 2013, pp. 1321–64.

© 2017 The Authors. European Financial Management Published by John Wiley & Sons Ltd