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Knocking on Tax Haven’s Door:
Multinational Firms and Transfer Pricing ∗
Ronald B. Davies1, Julien Martin2, Mathieu Parenti3, and Farid Toubal4
1Department of Economics, University College Dublin, Ireland
2Department of Economics, Université du Québec à Montréal, Canada
3CORE - IRES, Université Catholique de Louvain, Belgium
4Ecole Normale Supérieure de Cachan, Paris School of Economics and CEPII, France
December 2014
Abstract
This paper analyzes the transfer pricing of multinational firms. We show that
intra-firm prices may systematically deviate from arm’s length prices for two motives:
pricing to market and tax avoidance. Using French firm-level data on arm’s length and
intra-firm export prices, we find that the sensitivity of intra-firm prices to foreign taxes
is reinforced once we control for pricing-to-market determinants. Most importantly, we
find no evidence of tax avoidance if we disregard tax haven destinations. Tax avoidance
through transfer pricing is economically sizable. The bulk of this loss is driven by the
exports of 450 firms to ten tax havens.
Keywords: Transfer pricing; Tax haven; Pricing to market
JEL classification: F23, H25, H25, H32
∗We wish to thank Andrew Bernard, Kristian Behrens, Robert Cline, Paola Conconi, Anca Cristea,
Meredith Crowley, Lorraine Eden, Peter Egger, Lionel Fontagné, James Hines, Lindsay Oldenski, Bernard
Sinclair-Desgagné, Nicholas Sly, and seminar participants at CEPII, the "competitiveness and corporate
taxation: impact on multinationals’ activities" conference (Banque de France) , 2014 EEIT Conference (U.
Oregon), ETSG, HEC Montréal, Midwest Meeting (Kansas U.), the "National Institutions in a Globalized
World" workshop (Lille), Higher School of Economics in Saint Petersburg, UQAM, and ULB for helpful
comments. Financial support was provided by the iCODE Institute (Idex Paris-Saclay) and the FRQSC
grant 2015-NP-182781.
0
1 Introduction
A wealth of empirical evidence finds that, within a multinational enterprise (MNE), reported
profits vary systematically with local corporate tax rates.1This may be due to several types
of efforts within the firm, including transfer pricing. From the perspective of tax authorities,
internal transactions between related parties should be valued at the market price: this is
the arm’s length principle (see OECD 2012, for details). That said, as described in OECD
(2010) there are numerous ways of determining the arm’s length price, including the use of
comparable prices, and cost-plus methods, among others. Thus, the flexibility in these rules
allows firms to choose transfer pricing methodologies which support the use of internal prices
which shift profits from high- to low-tax countries.2This is in addition to the potential for
outright tax evasion via transfer pricing.
Direct empirical evidence of tax-induced transfer pricing however is scarce. Identify-
ing such a strategy faces two major difficulties. While multinationals’ exports are directly
observable, detailed information on the prices of products and their modes of transaction –
whether it is arm’s length or intra-firm – is generally not available. Moreover, it is impossible
to observe the counterfactual arm’s length prices of an intra-firm transaction (see Diewert
et al. 2006, for details). Since the arm’s length price is not observed, tax authorities have to
fix the market price, which raises obvious definitional and methodological issues.
In this paper, we overcome both difficulties. We observe the export prices under each
mode (arm’s length or intra-firm) at the level of firms, countries, and products. Our econo-
metric methodology moreover allows us to compare the intra-firm price with its corresponding
arm’s length price. We show that the bulk of tax avoidance comes from a few large firms
through exports to a relatively limited number of "tax havens", where the baseline estimates
find that intra-firm prices are on average 11% lower than arm’s length prices.3This suggests
that, by targeting enforcement efforts, tax authorities may be able to mitigate transfer pric-
ing and raise tax revenues, while keeping enforcement costs low. The granular dimension
of tax avoidance should facilitate the implementation of such global enforcement as the one
proposed by Zucman (2014).
In order to frame our empirics, we first develop a theoretical model on the determinants
of arm’s length and intra-firm prices. The model goes beyond the traditional theoretical
literature as it takes both tax-induced transfer pricing and pricing-to-market strategies into
account. The latter has been receiving increasing attention in the field of international trade.4
1See Fuest et al. (2003) for a survey on the impact of taxation on real MNE activity.
2An OECD survey of tax authorities reaches the conclusion that "tax administrations see transfer pricing
as one of the most significant tax risks they have to manage” (OECD 2012, p.15). Gresik (2001) provides a
survey with an emphasis on the transfer pricing literature. A recent meta-analysis by Heckemeyer & Overesch
(2013) shows that transfer pricing and licensing are two important means of shifting profits abroad. Recent
theoretical contributions on tax-induced transfer pricing include Behrens et al. (2009), Bernard et al. (2006),
and Keuschnigg & Devereux (2013) which provides a recent model of non-tax-induced transfer pricing, one
motivated instead by manipulating managerial incentives. Diewert et al. (2006) gives an overview of the
different rationales for manipulating internal prices.
3About 25 firms accounts for 50% of intra-firm trade with the tax havens in our sample.
4Examples include Bastos & Silva (2010), Manova & Zhang (2012), and Martin (2012).
1
The model shows that an exporting MNE finds it optimal to deviate from the arm’s length
prices when it exports to countries with a different level of taxes than its home country. The
wedge between the intra-firm price and the arm’s length price is a decreasing function of the
host tax. We also show that arm’s length and intra-firm prices are likely to have a different
sensitivity to transport costs, tariffs, and GDP per capita, i.e. variables governing pricing
to market. This result suggests that one should be mindful of this difference in sensitivity
in the empirical analysis. If one of these variables is significantly correlated with the level of
corporate tax rates (something which is true in our data), not allowing coefficients to differ
across pricing modes would bias the estimated coefficients.
On the empirical side, we rely on a unique dataset that has detailed information on the
intra-firm and arm’s length quantities and prices of exported products at the firm-level for
almost all French firms exporting in 1999. France is a useful country for this exercise as it
exempts foreign income from taxation. Compared with the U.S. and other countries where
foreign tax credits and deferral complicate a firm’s tax planning problem, the relatively
streamlined French system provides a cleaner mapping between tax differences and firm
incentives.5Our identification strategy makes use of a set of triadic fixed effects at the level
of the firm, product and mode of transaction to control for unobservable determinants of
prices specific to firms, products and mode (such as firm productivity). The use of triadic
fixed effects allows us to study the gap between arm’s length prices and intra-firm prices
which are driven by the characteristics of the destination country. More specifically, we
interact an intra-firm trade dummy with a measure of destination countries’ corporate taxes
to examine whether differences in intra-firm and arm’s length prices can be accounted for by
the tax differentials across countries. In addition, we control for several pricing-to-market
variables identified as important in the trade literature (income, distance, and tariffs) and
allow the sensitivity to these variables to differ across modes.
In line with the main theoretical prediction, our estimates suggest that export prices drop
with the destination corporate tax rate only for intra-firm transactions. This result is robust
once we control for pricing to market. We then show that the effect of taxes is non-linear.
Transfer pricing is essentially directed to countries with very low tax rates. Interestingly,
low taxes are not the entire story. The bulk of tax avoidance is attributable to the transfer
pricing of exports to tax havens. Tax havens not only have low corporate tax rates, but
they also provide an overall tax environment that seems to facilitate profit shifting through
transfer pricing.6For the ten tax havens in our sample, these additional factors may well
differ from one to the other. For example, Ireland and Luxembourg came under fire from
the European Commission in 2014 for offering firm-specific tax advantages which amounted
to state support. In addition, in our sample, Ireland’s "double Irish" system, which allows
firms to be incorporated but not tax residents was in full effect (a policy which is due to
be phased out beginning in 2015). Switzerland, meanwhile, is well known for its reticence
to provide information to other tax authorities, a factor which may aid in tax avoidance.
5Bernard et al. (2006) provide a detailed discussion of the complexity of the U.S. tax system.
6Gumpert et al. (2011) provide a discussion of this in the context of an exemption-granting country like
France.
2
Cyprus had a similar policy up to 2013, when, as part of the bailout it received during the
financial crisis, it reversed its policy. Thus, while the phrase "tax haven" is burdened by a
negative connotation implying secrecy and lax policy enforcement, we use it with a broader
meaning covering a variety of firm-friendly tax policies. Extending our investigation finds
that profit shifting through transfer pricing is primarily done by large multinational firms.
A simple exercise suggests that the tax losses driven by the profit shifting of multinational
firms to the ten tax havens in our sample amounts to about 1% of total corporate tax revenues
in France. We further show that 450 MNEs account for over 90% of intra-firm exports to
these ten tax havens, implying that a large share of transfer pricing may be curbed by
focusing enforcement on a small number of firms.
Although there is a large literature on the impact of international tax differences on the
location of profits and firms, the results of which are suggestive of transfer pricing, there
is very little evidence of the impact of taxes on transfer prices themselves.7Bartelsman
& Beetsma (2003) use aggregated data on value added across manufacturing sectors in the
OECD. They estimate a value added function depending on corporate tax rates and other
factors, finding results suggestive of profit shifting via transfer pricing. Clausing (2003) uses
price indices for U.S. exports and imports which include separate indices for intra- and extra-
firm prices, finding a strong and significant impact of taxes consistent with transfer pricing.
Using an approximation of intra-firm trade from firm-level balance sheet data, Overesch
(2006) finds that the value of German MNEs’ intra-firm trade varies with the difference
between the German tax rate and that of the foreign parent/affiliate’s location. However,
his analysis does not compare the price to an arm’s length price. As the arm’s length price
may also vary with the overseas tax, his result could be due to pricing to market instead
of transfer pricing.8Two interesting papers, Vicard (2014) and Cristea & Nguyen (2014),
exploit the panel dimension of firm-level data on French and Danish firms respectively. Both
papers tend to provide evidence of transfer pricing. However, they do not observe intra-firm
and arm’s length prices, but assume intra-firm prices for transactions with countries where
a related party is located. As mentioned by Ramondo et al. (2011) and Atalay et al. (2014),
most firms with an affiliate in a country do not trade with this affiliate. Furthermore, a firm
that exports a product to its affiliates might also well export another product to a third
firm in the same country. In our sample of firm-country pairs where we observe positive
intra-firm trade, the share of intra-firm trade in a firms’ total trade is below 40% for one
fourth of observations. Our empirical tests rely on precise firm-level data on intra-firm and
arm’s length prices.
Finally, our paper is related to the work of Bernard et al. (2006) who examine how
internal prices depend on taxes and tariffs using U.S. firm-level data. Similarly to the papers
mentioned above and to our own results, their estimates are consistent with transfer pricing.
We depart from this paper along three dimensions. First, and most importantly, we consider
7For a recent discussion of the former, see Huizinga & Laeven (2008). Dharmapala & Riedel (2013)
discuss the impact of taxes on firm financing.
8Using firm-product level data, Swenson (2001) finds that prices react to taxes and tariffs, however, she
is unable to distinguish between intra-firm and arm’s length transactions and thus, again, it is not clear
whether this is linked to transfer pricing or pricing to market.
3
the tax haven status as well as tax rates. Since our estimates indicate that internal and arm’s
length prices deviate most when the destination is a tax haven, this is critical. Second, we
examine whether all multinational firms are likely to use transfer pricing to shift profits
abroad.9Our findings indicate that the intensity of profit shifting is systematically greater
for larger firms. Lastly, our methodology is different: we use French rather than U.S. data,
we run price regressions including firm-product-mode fixed effects rather than working with
price gaps, and we allow intra-firm and arm’s length prices to differ for other reasons than
fiscal motives. By using French rather than U.S. data, we avoid the complications in taxation
introduced by the U.S. foreign tax credit system. The price regression with individual fixed
effects offers a flexible framework to measure whether intra-firm and arm’s length prices
differ. Finally, accounting for differences in pricing to market between pure exporters and
intra-firm exporters is consistent with the theory, and not doing so may bias the results.
The rest of the paper is organized as follows. In Section 2, we present the theoretical
model and its predictions for the empirical analysis. In Section 3, we carefully present
the data and the estimation sample construction. In Section 4, we present the baseline
estimation, extend the results, and provide a quantification exercise estimating the revenue
loss for France due to transfer pricing. We conclude in Section 5.
2 Model
We present a simple model that illustrates how taxes and other factors, such as trade costs
or market size, influence the pricing strategies of a firm. The firm produces an intermediate
good in its home country at a constant marginal cost cand sells it to its overseas affiliate
at a free-on-board price pH
M N E . For sake of simplicity, we assume the domestic and foreign
sales to be separable.10 We assume that exports incur an ad-valorem cost τvpH
MNE such as
tariff or insurance and a specific cost τf, such as the cost of shipping.11 These trade costs
are specific to the destination market. We assume the production of the final good to be
costless. The foreign consumer price is denoted by pF
M N E .
For the determination of the price for the intermediate, we use the popular "concealment
cost" approach to modeling transfer pricing.12,13 In this, the transfer price pH
MNE can differ
from the price, pHthat would be set by a firm selling to an unaffiliated party, but this incurs
9Bernard et al. (2006) show that the price wedge between intra-firm and arm’s length transactions depends
on the size of exporters and the differentiation of products. However, they do not study whether the
sensitivity of the price wedge to corporate taxes depends on these characteristics.
10The final good is not imported back to the domestic country.
11See for instance Goldberg & Campa (2010) or Berman et al. (2012).
12This approach was initiated by Kant (1988) and forms the predominate method of modeling transfer
pricing in theory (eg. Haufler & Schjelderup 2000) and the empirics (eg. Huizinga & Laeven 2008).
13Ernst & Young (2012) suggest that prices is one of the issues which receive "the greatest scrutiny” while
volumes are not mentioned (p63). However, one can show that our results hold if the tax authority puts
enough weight on price deviations relative to the volume that is exported. Specifically, if one assumes that
the concealment cost function is ϕpH
MNE −pHdpF
MNEα+Fwith α≥0and ϕ(z) = z2, our results
hold if and only if α < 1/2.
4
a cost ΦpH
MNE −pHwhere Φis defined as follows:
Φ(x) := (ϕ(x) + Fif x6= 0
0if x= 0
where ϕ(.)is the variable component of this cost which is continuously differentiable, convex,
and such that ϕ(0) = ϕ0(0) = 0 with ϕ0(x)>0. Last, we assume that ϕ(.)is an even function
ϕ(x) = ϕ(−x)∀x∈Rso that the concealment cost depends upon the price gap only. This
concealment cost is generally interpreted in transfer pricing models as the cost of hiring
accountants to "cook the books” and/or as the fines that the firm would pay if it were
caught. We allow these costs to entail a fixed cost Fand a variable cost ϕ(.)which increases
marginally with the price wedge. Note that this might vary across countries; for example,
if a tax haven makes this concealment relatively easy, then this could reduce the total and
marginal cost for a given x. The arm’s length price is taken as given by the firm and Φis the
tax-deductible cost that occurs in the home country. As an alternative, we could derive this
function along the lines of Becker & Davies (2014) where, rather than illicit tax avoidance,
firms choose their transfer pricing methodologies from a range of legal alternatives. As they
show, even when firms are audited with certainty, rendering concealment pointless, their
ability to affect government-approved transfer pricing via the choice of methodology results
in similar predictions regarding transfer pricing and taxes. However, given the complexity
of that model relative to our aims, we maintain the current approach due to its relative
transparency.
Both countries levy taxes on a territorial basis, where the home tax is THand the foreign
tax is TF. This is consistent with the tax-exemption rule for the income earned abroad by
French MNEs.
This results in profits given by:
πMNE =1−THpH
MNE −cdhpF
M N E i−ΦhpH
MNE −pH∗i (1)
+ (1 −TF)pF
MNE −(1 + τv)pH
MNE +τfdhpF
M N E i
The price pH∗, is the arm’s length price of a firm selling the product to a third party. In
order to determine this price, one needs to observe two firms with identical characteristics
that serve the same market with different modes (eg. the mode is randomly assigned to
each firm). We cannot observe this as counterfactual in the data. This simple model takes
into account that the arm’s length price is itself a function of market characteristics. This
means that our definition of transfer pricing disentangles variations in market power across
countries (through variations in pH∗) from variations in transfer pricing pH
MNE −pH∗.
Profits are maximized by choosing the transfer price pH
MNE and the price of the final good
pF
M N E . Assuming that F= 0 and defining the relative effective tax on foreign-earned profits
by tF=TF−TH
1−TH, the maximization of (2) results in a first order condition for the transfer
5
price of
1−1−tF(1 + τv)dhpF
M N E i=ϕ0hpH
MNE −pH∗i(2)
where the second-order condition in pH
MNE is implied by the convexity of ϕfor any prices
pH∗and pF
M N E . Since ϕ() is even, we have that ϕ0(x) = −ϕ0(−x)∀x∈R. Using that
ϕ0(0) = 0, the above equation implies that the direction of profit shifting is determined by
the sign of the left-hand side. Assuming that T ≡ 1−tF(1 + τv)>1implies that a firm
sets pH∗
MNE < pH∗in order to shift profits to the foreign country. This happens whenever
the corporate tax abroad is lower than at home (tF<0). This is a standard result in the
transfer pricing literature. We shall stress that the multiplicative trade costs (e.g. tariffs)
are also a motive for transfer pricing and that the two effects interact with one another. We
summarize this result in the following proposition:
Proposition 2.1. The level of corporate taxes and multiplicative trade costs determine the
direction of the deviation of intra-firm prices from arm’s length prices. Free-on-board intra-
firm prices are lower than arm’s length prices in destinations with lower corporate taxes or
high tariffs.
Equation (2) shows that the price gap is also positively correlated with the volume
dhpF
M N E ithat is exported. This occurs because, although a non-zero price wedge increases
per-unit after-tax profits, the marginal concealment cost is independent of quantity. The
deviation from the arm’s length price is increasing in firm size, presuming, consistent with
the data, that larger firms export more. The first order condition in equation (2) holds for
any value of c. Therefore, the transfer pricing strategies of multinationals with different
marginal costs differ if they ship different volumes dhpF
M N E i.
Proposition 2.2. Large volumes of intra-firm trade come with large deviations of intra-firm
prices with respect to arm’s length prices.
Remark 1 (inaction band): The above propositions show that a multinational firm
finds it optimal to shift profits abroad when F= 0 and taxes differ even marginally. The
fixed component in the concealment cost function however, implies that there is an inaction
band. In other words, we should not expect firms to shift profits abroad when the corporate
tax (tariff) differential is small.
Note that (2) does not necessarily imply that the magnitude of transfer pricing increases
in the tax differential. To see this, consider the first order condition for the final good’s
price:
pH
MNE −c+ (1 −tF)pF
MNE −((1 + τv)pH
MNE +τf)d0hpF
M N E i+ (1 −tF)dhpF
M N E i= 0
(3)
We assume, as is standard, that the demand is not "too convex" to guarantee that the
second-order condition holds. Rearranging equation (3) leads to the following system of
6
equations which define pH∗
MNE and pF∗
M N E :
(1 − T )dhpF∗
M N E i=ϕ0hpH∗
MNE −pH∗i(4)
pF∗
MNE =1
1− E−1[pF∗
M N E ]"(T − 1) pH∗
MNE +c
1−tF+τf#where E[z] = −d0[z]z
d[z](5)
Now, let us assume that tF<0and τv= 0. We find T= 1 −tF>1which implies, by
proposition 1, that pH∗
MNE < pH∗. In this simple example, we see that a change in tFhas two
opposing effects on internal prices. First, equation (4) shows that a decrease in tFleads to a
decrease in pH∗
MNE keeping pF∗
MNE constant, i.e. more transfer pricing. This change is larger
when the output is large and the penalty function is not "too convex”. However, equation (5)
shows that, as the drop in the foreign tax lowers after-tax costs, the firm will adjust pF∗
M N E ,
and hence the output, when changing pH∗
M N E . The magnitude of this adjustment depends
crucially on the demand price-elasticity E[pF∗
M N E ]and on how much the firm passes onto its
final price changes in its free-on-board price.
There is therefore no reason to expect that a decrease in tF(and thus an increase in T)
impacts monotonically the price gap. It is standard however to dismiss the output adjust-
ment (see Cristea & Nguyen (2014) for a detailed discussion and simulations under iso-elastic
demand). Equation (5) offers an additional rationale to this assumption if we assume that
dE
dz >0. This restriction is verified if demand is more elastic at high prices which is both
intuitive and a commonly used assumption in models of monopolistic competition with vari-
able mark-ups. In this event, a relative change in the free-on-board price leads to a smaller
relative change in the final price and thereby a lower change in output. We thus find it
reasonable to expect that, as is commonly assumed in the transfer pricing literature, the
price gap increases in T. While a within-market comparison of the price gap between multi-
nationals and arm’s length exporters would not be evidence of transfer pricing, the theory
suggests to identify transfer pricing by comparing the price-gap across different markets.
We now turn to the importance of market characteristics. Although the firm takes the
arm’s length price pHas given, this too is determined as a function of local characteristics
since, as is well established, the free-on-board price of exports will vary with destination
specifics. Thus, in order to accurately compare the differences between intra- and extra-firm
prices and how they vary with destination characteristics, it is necessary to consider the
relative responses of pH
MNE and pH. We show below that even under the commonly used
assumption of CES preferences, market characteristics may impact differently pH
MNE and
pH.
The profits of a pure exporter, which both produces the intermediate and converts it into
the final good at home, can be written as:
max
pHπ=pH−cdh(1 + τv)pH+τfi(6)
where the final consumer pays the cost-including-freight price (1 + τv)pH+τf. With
7
iso-elastic demand, the demand curve can be written as:
dh(1 + τv)pH+τfi=A(1 + τv)pH+τf−η(7)
where Ais a demand shifter which depends on the market structure and ηis the constant
price-elasticity of demand.14
In order to maximize profits, the exporter sets a free-on-board price equal to:
pH∗=η
η−1 c+τf
η(1 + τv)!(8)
which is increasing in trade costs whenever τf>0. Since transport costs increase with
distance, fob prices are expected to increase with distance as found by Bastos & Silva (2010),
Manova & Zhang (2012), Martin (2012). Since distribution costs are an increasing function of
foreign wages, we expect fob prices to increase with GDP per capita as found by Simonovska
(2010). Thus, exporters price to market, resulting in an arm’s length price that varies by
destination. Note, however, that as all revenues and costs are incurred at home, this price
is independent of taxes.
Returning to the MNE’s first order conditions, with iso-elastic demand, (4) and (5)
become:
(1 − T )ApF∗
M N E −η=ϕ0"pH∗
MNE −η
η−1 c+τf
η(1 + τv)!# (9)
pF∗
MNE =η
η−1"(T − 1) pH∗
MNE +c
1−tF+τf#(10)
which determine both pH∗
MNE and pF∗
MNE implicitely as functions of τf. Clearly, the elas-
ticity of pH∗
MNE with respect to τfis generally different from the elasticity of pH∗and without
more structure on the model, one cannot infer whether the price gap is magnified or reduced
when, for example, distance or GDP per capita increases.
Remark 2: The sensitivity of arm’s length and intra-firm prices with respect to distance
and GDP per capita generally differs.
Thus, the size of the price wedge will vary according to destinations. Failure to account
for this can potentially result in misleading estimates of the impact of taxes on the difference
between intra-and extra-firm prices.
This theoretic exercise yields a set of predictions for us to take to the data. First, a higher
destination tax should lower the intra-firm price but have no effect on arm’s length prices.
Second, prices should be an increasing function of specific trade costs (such as distance)
and destination income but a declining function of ad valorem trade costs (such as tariffs).
Finally, there should in general be differences in the impacts of these three variables on arm’s
14In a CES model of monopolistic competition, this constant is y
P1−ηwhere ystands for income, Pis a
price-index of all varieties supplied in the market and ηcan be interpreted as the elasticity of substitution
between varieties.
8
length prices and transfer prices. In the next section, we describe the data and methodology
used to test these predictions.
3 Data and identification strategy
3.1 Data description
To investigate the factors driving transfer pricing, we use detailed information on intra-firm
and arm’s length export prices for a set of French firms in 1999. In order to construct our
estimation sample, using a unique firm identifier, we combined three datasets that have
detailed information on firm-level exports values and quantities of 8-digit product categories
by destination, data on MNE status, and information on whether a transaction is intra-firm
or arm’s length. We merge these datasets with information on country-level characteristics
such as the level of corporate tax rate, distance, tariff or per-capita income.
Firm-level data. Our first dataset comes from the French Customs which reports the
free-on-board values and quantities of exports by firm, 8-digit CN product category, and
destination. We use the value and the quantity of firms’ export of a given product (CN8)
to a given destination in order to construct the destination and firm-specific free-on-board
unit values (our proxy for the price) a firm charges for that good in a given market.
This dataset, however, does not provide information on the mode of exports, that is,
whether a transaction is intra-firm or at arm’s length. We obtain this information from a
confidential 1999 survey of MNEs in France (both French and foreign-owned) which comes
from the INSEE.15 The survey was addressed to all such MNEs with trade worth more than
one million euros and covers firms providing 87% of the French total industrial product ex-
ports.16 The INSEE survey provides a detailed geographical breakdown of French MNEs’
export values and quantities at product level (HS4) and their exporting modes – through
outside suppliers and/or related parties. Using a CN8-HS4 correspondence table, we match
each 8-digit product category to their corresponding HS4 category. When the INSEE indi-
cates that an HS4 category has a share of intra-firm exports exceeding 98%, we classify all
the corresponding CN8 exports by MNEs to be intra-firm transactions.17 If the share is zero,
we classify the CN8 codes as arm’s length. When the share is positive but below 98%, we
drop this firm’s observations within this destination-HS4 dyad, observations which amount
to roughly 12.6% of French exports. We assume for non-MNEs that all exports are done at
arm’s length and are done through unrelated parties.
Finally, we use information from LIFI, a French-firm level dataset on financial linkages
between firms. This is used to determine whether a firm in the French customs data is a MNE
and, if so, its nationality and the country locations of their related parties. As this identifies
some firms in the French customs data as MNEs but for which we do not have the INSEE
15Échanges internationaux intra-groupe.
16www.insee.fr/fr/ffc/docs_ffc/IP936.pdf, INSEE WP 936, Table 1.
17Changing this threshold does not change the qualitative results of our empirical analysis.
9
data, we drop those observations as we cannot know whether the transaction is intra-firm or
arm’s length.18 We also eliminate the observations of state-owned firms as these firms might
have a different price setting mechanism.19 LIFI is also interesting because it provides the
countries in which the affiliates of firms located in France are themselves located.
This then leaves us with information at the firm, NC8 product, country, and exporting
mode level. Once merged with country characteristics, there are 735,064 observations in
our unbalanced baseline sample.20 Our cross section is composed of 67,312 firms, 5,482
products and 45 countries. About 9.2% of the total number of observations are intra-firm
prices. It is worth emphasizing that most of the prices set by MNEs are not intra-firm
prices. In this sample, only 15.6% of the prices set by MNEs are intra-firm prices. Another
interesting fact is that, in our data, one third of multinational firms do not report intra-firm
trade in countries where they have affiliates (or a headquarter) according to LIFI. A last
fact pertains to the likelihood that we observe both arm’s length and intra-firm trade for
a multinational firm exporting to a given country. To study this point, we restrict to the
sample of firm-destination pairs that feature intra-firm exports. Since firms make part of
their export to these countries intra-firm, we can be certain that the firm has a related party
in the destination country. Among these pairs there are firms selling all their exports intra-
firm while other firms may export to the country through the two modes. In this sample,
the median share of intra-firm trade is 98%. This means that conditional on exporting intra-
firm to a country, the median firms export almost entirely intra-firm. This figure, however,
hides large variation. In particular, we find that for one fourth of product-country pairs, the
share of intra-firm trade is at most 40%. Said differently, even if a firm exports intra-firm
to a country, in 25% of cases, the share of intra-firm exports to the country is below 40%.
These facts confirm the usefulness of having information on intra-firm and arm’s length
transactions. They also show the caveats of databases that only report information on the
presence of related parties in the destination country.
Tax and Tax havens data. In our model, the equilibrium is where the marginal savings
from reducing tariff and tax payments equals the marginal cost of transfer pricing. Thus,
the most appropriate tax measure is the effective marginal tax rate (EMTR) on income as
this represents the tax savings from shifting one euro of income. If taxes are flat, then the
EMTR equals the effective average tax rate (EATR). However, if taxes are progressive (as is
typically the case), then the EATR will understate the tax savings from transfer pricing. In
our baseline results, we use the EMTR from Loretz (2008). In robustness checks, we instead
use the EATR and the top statutory corporate tax rate (both from Loretz (2008)) and find
qualitatively identical results. In the baseline estimation, we used the EMTR reported in
18We lose 605 firms amounting to dropping 2.5% of the value of French exports.
19They account for about 1.7% of French exports.
20We lose information on about 10% of the French export value when merging the dataset with the tax
rates data. We also lose an additional 2.3% of the export value when merging the data with info on tariffs.
The tariffs data are not available for 20 countries of the original sample of 65 countries. Reproducing the
estimations without the tariffs variable leads to qualitatively similar results.
10
1998 or 1997 (whichever is closer) when the data for 1999 were missing.21 An important
aspect of these tax rate measures is that they are constructed from statutory tax policies,
but unlike the headline tax rate, accounts for factors such as the tax offsets from capital
expenditures (see Loretz (2008) for details). As such, EMRT or EATR are exogenous to
firm decisions, something which would not be the case if we used firm accounting data to
construct firm-specific taxes.
As seen in table 5in the appendix, the effective average and marginal tax rates vary
considerably across countries. In our estimation sample, the EMTR ranges from 0% in
the Bahamas to about 46% in the Russian Federation. Of large concern in policy circles
is the use of investment in tax havens in aggressive tax planning. This is particularly the
case for countries such as France or Germany that exempt foreign income from taxation.22
We therefore use additional information on tax havens. Our definition follows Hines &
Rice (1994) which has been recently used by Dharmapala & Hines (2009). A tax haven is
defined as a location with low corporate tax rates, banking and business secrecy, advance
communication facilities and self-promotion as an offshore financial center ((Hines & Rice
1994), Appendix 1 p. 175). Compared to the list of Tax Havens produced by the OECD
(2000), the approach of Dharmapala & Hines (2009) identifies a number of additional tax
havens such as Switzerland. In our estimation sample, the Bahamas, Bermuda, the Cayman
Islands, Cyprus, Hong Kong, Ireland, Luxembourg, Malta, Singapore and Switzerland are
classified as tax havens. Approximately 41% of firms export to these countries and these
exports account for roughly 11% of the total number of observations.
Pricing to market data. As discussed above, firms adjust their prices to the characteris-
tics of the destination market. The empirical literature has identified two main regularities
on firms’ pricing to market behavior, namely, firms charge higher prices when the destination
is further away and when the destination is wealthier (eg. Bastos & Silva 2010,Manova &
Zhang 2012,Martin 2012). Berman et al. (2012) have shown that small and large firms may
react differently to trade costs depending on their size and productivity. In our model, we
show that these factors may impact intra-firm prices differently from arm’s length prices.
Furthermore, as these market characteristics are correlated to the level of corporate tax rate,
it is crucial to control for them. We therefore use data on per capita GDP (measured in US
dollars) from the Internal Financial Statistics of the IMF to control for the level of country
specific income. As measures of trade costs, we use the bilateral distance variable (which
is the population weighted average distance between countries’ main cities in kilometers)
which is taken from CEPII database (Mayer & Zignago 2006) and also use information from
TRAINS on tariffs faced by French exporters developed by the WITS (UNCTAD). In our
data, distance and per capita GDP are both significantly and negatively correlated with
both the effective tax rates and tax haven status, suggesting that their omission could bias
21Notice that the 37 of 45 countries in our sample share a Bilateral Tax Treaty with France. Controlling
for the existence of treaties (and interacting with the intra-firm dummy) does not change the results and
indeed, we find little impact of tax treaties on transfer pricing.
22See the recent paper by Gumpert et al. (2011), who considers this issue for a large sample of German
MNEs.
11
our results.
3.2 Identification strategy
Testing the main propositions of our model requires estimating the effect of the tax variables,
the EMTR and/or tax haven, on the differential between the intra-firm price of a specific
product in a country and its corresponding arm’s length price. Our empirical model includes
a set of triadic fixed effects at the level of firm, product and export mode. The use of triadic
fixed effects allows us to compare the gap between the arm’s length price and the intra-firm
price across countries. These fixed effects also account for a wide set of attributes of the
transactions at the level of the firm, product, and exporting mode that might also account
for the levels of the price differential (Bernard et al. 2006). In our empirical estimation, we
make use of an interaction term between the tax variables and an indicator of the export-
ing mode that is equal to 1 if the transaction is intra-firm and 0 if it is at arm’s length.
Given the set of controls that we discuss below, the estimated interaction coefficients give
an indication of the price differential that is due to transfer pricing.23 As we shall show later
on, we use destination fixed effects in some specifications to control for destination-specific
heterogeneity.
The empirical strategy involves estimating the following model:
pfpmc =α1Intrafpmc +α2T axc+α3T axc×Intrafpmc (11)
+α4T axH avenc+α5T axHav enc×Intraf pmc
+γ1Xc+γ2Xc×Intraf pmc +µfpm +fpmc
where pfpmc is the export price charged by firm ffor product pin country cunder the export
mode m.T ax is a variable that captures the level of tax in the destination country. Our
primary measure is based on the EMTR, defined as T axc=log(1 −τc), with τcbeing the
EMTR in country c.24 Our second measure, T axHav enc, is a dummy variable that takes the
value of one if the country is on the tax haven list of Hines & Rice (1994). These are both
also interacted with Intrafpmc , a dummy variable that takes the value of one if the export
mode is intra-firm and zero otherwise. Since we expect the price wedge to be increasing in
the amount of profits retained by the firm (i.e. T axc=log(1 −τc)is larger or the country is
a tax haven), we anticipate both of these interactions to be negative (i.e. a larger absolute
value difference between the intra-firm and arm’s length prices).
The term µfpm is a comprehensive set of firm-product-mode fixed effects. Notice that it is
no longer possible to estimate the direct effect of the export mode because of the triadic fixed
effects. Xcis a vector of country specific variables that includes the logarithm of distance,
tariffs, and the logarithm of GDP per capita. We interact these variables with the intra-firm
transaction dummy as the pricing behavior of firms is also affected by bilateral trade costs
23Our identification strategy implies that the deviation from the arm’s length price in itself is not evidence
of transfer pricing. It is an evidence when the gap between the arm’s length price and the intra-firm price
is significantly related to the tax differential across countries.
24We also use the EATR variable as an alternative definition of the tax rate.
12
and income in the destination market and might also vary across the export modes. As the
prices might also be influenced by the market structure and the intensity of competition
in the foreign market, and since these characteristics are unobservable, we introduce a set
of country-fixed effects in some specifications. Finally, fpmc is the disturbance term. The
standard errors are allowed to be adjusted for clustering at the country-level to account for
heteroskedasticity and non-independence across the repeated observations within countries.
Table 1gives the summary statistics.
Table 1: Summary statistics
Variable Nature Mean Std. Dev.
pfpmc (log) 3.09 1.799
Intraf pmc 0/1 0.092 0.288
(1 −τc)(EMTR) (log) -0.353 0.095
(1 −τc)(EATR) (log) -0.383 0.091
T ax Hav enc0/1 0.107 0.308
T arif fcContinuous 0.270 0.739
Distancec(log) 6.986 0.865
P er Capita GDPc(log) 9.976 0.569
Intraf pmc×:
(1 −τc)(EMTR) -0.032 0.105
(1 −τc)(EATR) -0.035 0.113
T axH avenc0.007 0.083
T arif fc0.030 0.262
Distancec0.653 2.073
P er Capita GDPc0.905 2.857
Observations 735,064
4 Results
Baseline Results. According to the theoretical predictions the average internal price
should be lower than the arm’s length price in a country with lower marginal effective tax
rates. The estimates are reported in Table 2. Overall, the specifications explain from about
87% of the variation of the log level of export prices as suggested by the adjusted R2. The
estimates using the EATR variable are reported in Table 6in the Appendix.
In column (1), we do not find a statistically significant effect of the effective marginal
tax rate on the level of arm’s length prices. We do, however, find a negative and significant
interaction coefficient between the corporate tax and the intra-firm dummy, i.e. internal
export prices are relatively lower than arm’s length prices in destinations with lower corporate
tax rate. A ten percent decrease in the effective average tax rate leads to a reduction of intra-
firm prices by 1.9% (2.2% using the EATR variable).
13
Table 2: Baseline regression Effective Marginal Tax Rate, All firms
Dependent variables: Export price
(1) (2) (3) (4) (5) (6)
(1 −τc)0.10 0.12 -0.01 -0.03
(0.755) (0.870) (-0.137) (-0.367)
− × Intraf pmc -0.19∗∗ -0.20∗-0.10 -0.05 -0.08
(-2.109) (-1.932) (-1.451) (-1.056) (-1.205)
T axH avenc0.11 0.12
(1.574) (1.555)
− × Intraf pmc -0.11∗∗ -0.09∗∗ -0.09∗∗∗
(-2.686) (-2.365) (-2.843)
P er Capita GDPc0.06∗∗ 0.04 0.04 0.04
(2.128) (1.544) (1.487) (1.568)
− × Intraf pmc -0.03∗∗ -0.01 -0.01 -0.02∗-0.00
(-2.620) (-1.108) (-1.187) (-1.726) (-0.404)
Distancec0.08∗∗∗ 0.08∗∗∗ 0.08∗∗∗ 0.11∗∗∗
(2.919) (3.631) (3.652) (4.288)
− × Intraf pmc -0.04∗∗∗ -0.05∗∗∗ -0.05∗∗∗ -0.06∗∗∗ -0.05∗∗∗
(-2.855) (-4.811) (-4.518) (-4.974) (-4.178)
T arif fc0.03 0.03 0.03 0.01
(1.052) (1.122) (1.158) (0.418)
− × Intraf pmc -0.03∗-0.03∗∗ -0.03∗∗ -0.02 -0.03∗∗∗
(-1.995) (-2.617) (-2.426) (-1.616) (-3.138)
Sample Full Full Full Full w.o Tax H. Full
Country FE No No No No No Yes
Firm-Prod.-Mode FE Yes Yes Yes Yes Yes Yes
Observations 756,332 735,064 735,064 735,064 657,117 735,064
Adj. R20.862 0.865 0.865 0.865 0.870 0.866
Note: This table investigates the impact of effective tax rate, GDP per capita, distance, tariffs, and tax
haven dummy on intra-firm and arm-length export prices. Effective tax rates are transformed as follows:
(log(1−τ)). We use the effective marginal tax rate here. All regressions include firm-product-exporting mode
fixed effects. The last column further includes country fixed effects. In column (5) we restrict the sample
to countries not classified as tax havens. Robust standard errors clustered by destination are computed.
Corresponding t-statistics are reported in parentheses. Significance levels: ∗p < 0.1,∗∗p < 0.05, and
∗∗∗p < 0.01.
In column (2), we control for other country characteristics that might influence the pricing
behavior of the firm. Nevertheless, we continue to find comparable results, namely that taxes
influence internal prices but not those between unrelated parties. If anything, the estimated
impact is slightly larger, suggesting a slight bias when they are excluded. In line with
14
the prediction of our model, we find a positive impact of per-capita GDP on the level of
prices. A ten percent increase in per capita GDP raises the export prices by 0.6%. We find
however a negative and statistically significant interaction coefficient between the per capita
GDP and the intra-firm mode variables. This suggests a slightly lower impact of per-capita
GDP on internal prices which may make sense if internal trade includes a larger share of
intermediate goods which are not directly sold to overseas customers. Turning to the trade
costs variables, in line with the prediction of our model we find a positive effect of distance
on export prices. A ten percent increase in distance raises the export prices by 0.8%. As
an example, given the distances between France and the countries in our sample, the export
prices are on average 0.8% higher in the Netherlands as compared to Belgium. The effect
of distance on internal export prices is lower. Concerning the tariff variable, the effect on
arm’s length prices is not significant. In other words, there is no evidence of dumping by
French arm’s length exporters. This might be due to the low cross-country variation in the
tariff variable as most of the transactions are observed in countries that are member of the
European Union.25 However, intra-firm prices are significantly lower than arm’s length prices
in high-tariff countries, suggesting that firms choose to undervalue their exports to pay fewer
tariffs.
In column (3), we replace our EMTR variable with a dummy variable equal to one if
the destination is a tax haven. As tax havens not only have low taxes but often provide
other mechanisms that facilitate profit shifting (such as the limited exchange of information
between tax authorities), one might expect that internal prices differ markedly in these
nations. The results are striking. The interaction between the tax haven dummy variable
and its interaction with the intra-firm export mode is significant and estimated with a large
degree of precision. We do not find a significant effect of the tax haven dummy variable on
the arm’s length price. This result suggests that arm’s length export prices are the same
regardless of whether or not the destination is a tax haven. The interaction between the
tax haven and the export mode dummy variables is significantly negative, indicating that
the average internal export price for a tax haven is about 11% lower than the comparable
arm’s length price. This suggests that the tax havens are playing a major role in the transfer
pricing strategies of firms.
This finding remains robust in column (4) as we include the effective marginal tax rates
and its interaction term with the export mode, where we find the intra-firm export prices to
be about 9% lower than arm’s length prices in tax haven destinations even when tax rates
do not differ. Notice that the coefficient of the interaction term that involves the EMTR, is
smaller and insignificant once we control for the tax havens. As tax havens tend to have low
taxes, this suggests that the results in column (2) were biased due to failure to control for
tax haven status. Further, it highlights the important difference between having low taxes
and having other policies that make tax planning easier. Indeed, the OECD (2013)’s Action
Plan on Base Erosion and Profit Shifting makes precisely such a distinction.26
25About 90% of the observation concerns a transaction toward an E.U. country.
26The firms might also operate in tax havens and non-tax haven countries. We also drop the firms that
export in tax havens internally. We do not find a significant tax effect. This suggests that there are no
substitution effects. The transfer pricing strategy is not used by firms that do not export to tax havens,
15
In column (5), we investigate the importance of tax havens further by excluding them
from the analysis. Compared to column (2), the coefficient of the interaction term that
involves the effective tax rate is about four times lower and becomes insignificant, again
suggesting that the bulk of the impacts in column (2) were coming from the tax havens.
Finally, column (6) includes a set of destination specific dummy variables. Introducing
country fixed effects does not allow us to estimate the direct effect of the country specific
variables (including the tax rate and tax haven status). This, however, comes with the benefit
of controlling for other destination characteristics. As can be seen, the tax rate interaction
remains insignificant. Nevertheless, the tax haven interaction is virtually unchanged in
magnitude and becomes even more significant. Thus, even after including destination fixed
effects we find evidence of tax-induced transfer pricing which is most evident in tax haven
countries.27
Non-linear tax effects. To this point, we have investigated the average effect of tax
rates on the export price differential. We find evidence of transfer pricing, but only in tax
haven countries which are characterized by very low tax rates. Our results suggest therefore
a non-linearity of the tax rates on the price differential. We examine this effect further
by running a regression using, instead of the EMTR, a set of dummy variables indicating
the decile in which a country’s EMTR falls. We choose the 9th decile as a benchmark.
This decile is composed of 5 countries which have roughly the same effective marginal tax
rate as France and where, in theory, internal and arm’s length prices should be the same.
The first decile includes countries with the lowest effective marginal corporate tax rates.
It includes Bahamas, Hong-Kong, Ireland, Slovenia, and South Africa.28 The 10th decile
includes Argentina, Germany, Japan, and Poland which are the countries with the highest
effective marginal corporate tax rates in our sample.
The estimated coefficients of these interaction terms are shown in Figure 1.29 Each dot
corresponds to the interaction coefficient between the effective average tax rate and the
intra-firm export mode dummy variable. We also display the confidence intervals at the
10% level. The estimated effects are quite heterogeneous. Along the first remark of the
theoretical model, we observe an inaction band when the tax differential is not too large.
The point estimate of the interaction effect is however negative and significant only for the
countries in the first two deciles. This indicates that our results are very heavily driven by
the lowest tax countries, four of which are also classified as tax havens (Ireland, Switzerland,
Honk-Kong and the Bahamas).
while firms that export to tax havens have lower prices in countries with lower tax rates.
27We also investigate whether we find similar effects using firms that sell both arm’s length and intra-firm
and those that do only intra-firm trade. The results are qualitatively similar. They are available upon
request.
28The sample consists of 45 countries. For this reason, some deciles have 5 countries and others have 4
countries.
29The estimated coefficients are obtained from a regression of export prices on the tax decile of the
destination country and its interaction with a dummy equal to one if the price is intra-firm. The regression
also includes firm-product-exporting mode fixed effects, and distance, GDP per capita, and tariffs and their
16
Figure 1: Non-linear effect of corporate tax rate on transfer pricing
−.2
−.15
−.1
−.05
0
.05
Price gap intrafirm − arm’s−length
1 2 3 4 5 6 7 8 9 10
Tax decile
Note: This graph displays the price wedge between intra-firm and arm’s length prices by
decile of the destination country corporate tax rate. The price wedge is measured by the
coefficients on the interaction between tax deciles and an intra-firm dummy in a regression
of the logarithm of export prices on firm-product-exporting mode fixed effects, tax decile of
the destination country, GDP per capita, distance, and tariff, and their interaction with a
dummy equal to one if the exports are between related parties. The first decile is the decile
of countries with the lowest corporate tax rates. The tenth decile is the decile with the
highest corporate tax rates. Decile 9 is normalized to zero (countries with the same level of
tax as France). The gray area corresponds to the confidence interval at 5%.
Additional results. A relevant concern that has been raised in the literature studying
the effects of transfer pricing is the differing abilities of firms to engage in transfer pricing
(Bernard, et al 2006). In our model, firms with greater size are expected to have larger price
differentials. In columns (1) and (2) of Table 3, we split the sample according to the size of
the MNEs measured by their total exports.30 In the first column, we drop MNEs below the
75th percentile of the distribution of multinationals firm size, and thus keep large MNEs and
all pure exporters. In column (2), we drop observations of MNEs above the 25th percentile,
retaining only small MNEs and all pure exporters. Looking at the corporate tax and the tax
haven interactions with the intra-firm trade dummy, we find significance for tax havens only
for the large firms. This indicates that the manipulation of internal prices for tax reasons is
primarily a phenomenon for large firms in tax havens. Further, we find that the relationship
between pricing to market and internal prices is more prevalent in large firms.
In columns (3) and (4), we analyze another source of heterogeneity by operating a dis-
interaction with the intra-firm dummy.
30Note that as all the estimations in Table 3include destination fixed effects, only the interaction terms
can be estimated.
17
tinction across the nationality of ownership of a MNE. In column (3) we include MNEs that
are French resident or owned at a majority by a French group (as well as all non-MNEs). In
column (4), we include MNEs that are majority owned by a foreign group and all exporters.
Comparing the two, we find that the coefficients are estimated more precisely in the French
firms’ sample. In particular, we find the effective marginal tax rate to have a strong, negative
and significant impact on the log level intra-firm export prices. A comparable effect is found
for tax havens. These results therefore again suggest that tax havens are playing a major
role in the transfer pricing strategies of French firms. In column (4), although the sign of
the tax rate and tax haven variables match those in the French-only sample, the significance
of both is much lower with only the tax haven variable significant at the 5% level. This sug-
gests that similar forces are at play for this sample as well, although there may be greater
noise introduced due to the variety of parent countries in this sample as compared to that
in column (3). In particular, if the MNEs from other countries face worldwide taxation (as
do the U.S. firms in Bernard et al. (2006)), this may illustrate the cleaner tax effects to be
found by using data on FDI from a tax-exempting country.
18
Table 3: Additional results, Effective Marginal Tax Rate
Dependent variables: Export price
(1) (2) (3) (4) (5) (6) (7) (8)
Intraf pmc×:
(1 −τc)-0.05 -0.13 -0.14∗-0.03 -0.05 -0.09∗-0.09 -0.07
(-0.912) (-1.240) (-1.724) (-0.532) (-0.573) (-1.880) (-1.563) (-1.087)
T axH avenc-0.11∗∗∗ -0.01 -0.08∗∗∗ -0.11∗∗ -0.04 -0.08∗∗∗ -0.10∗∗∗ -0.10∗∗∗
(-7.597) (-0.171) (-3.307) (-2.326) (-0.726) (-3.788) (-3.877) (-2.715)
P er Capita GDPc-0.01 -0.00 -0.02 0.02 -0.05 -0.01 -0.01 -0.01
(-0.632) (-0.061) (-1.474) (1.500) (-1.410) (-1.175) (-1.147) (-0.542)
Distancec-0.05∗∗∗ -0.06∗∗∗ -0.07∗∗∗ -0.04∗∗∗ -0.01 -0.05∗∗∗ -0.05∗∗∗ -0.06∗∗∗
(-4.976) (-3.630) (-5.308) (-3.479) (-0.176) (-4.976) (-5.388) (-4.718)
T arif fc-0.03∗∗∗ -0.03 -0.05∗∗∗ -0.02∗0.01 -0.04∗∗∗ -0.04∗∗∗ -0.03∗∗
(-4.158) (-1.294) (-3.497) (-1.776) (0.404) (-3.967) (-3.686) (-2.537)
Sample Big Small French Foreign Homog. Diff. w/o
firms firms firms MNEs goods goods wholesale All
Firm-Prod.-Mode FE Yes Yes Yes Yes Yes Yes Yes Yes
Country FE Yes Yes Yes Yes Yes Yes Yes No
Cty-Sect. FE No No No No No No No Yes
Observations 723,921 697,897 567,071 465,008 11,980 608,535 553,745 742,863
Adj. R20.868 0.869 0.876 0.871 0.847 0.885 0.868 0.932
Note: This table investigates the impact of effective tax rate, GDP per capita, distance, tariffs, and tax
haven dummy on intra-firm and arm-length export prices. All regressions include firm-product-exporting
mode fixed effects. Column (1) focuses on MNEs whose export sales are above the P75. Column (2)
focuses on MNEs whose export sales are below the P25. Column (3) excludes affiliates of foreign MNEs
located in France. Column (4) excludes French MNEs. Column (5) contains only the products classified as
homogeneous in Rauch nomenclature. Column (6) contains only the products classified as differentiated in
Rauch nomenclature. Column (7) excludes MNEs whose main activity abroad is wholesale. Robust standard
errors clustered by destination are computed. Column (8) displays the results with Country and sector fixed
effects. Corresponding t-statistics are reported in parentheses. Significance levels: ∗p < 0.1,∗∗ p < 0.05, and
∗∗∗p < 0.01.
19
In France, as in most countries, the tax authority’s expectation is that firms set the price
of their internal transactions according to the arm’s length principle.31 The main force at
play in the above model is that deviations from this price come at a cost. This cost includes
penalties incurred if a firm were caught out. When the appropriate arm’s length price is easily
determined, as is the case for homogeneous goods that are traded on organized exchange,
transfer pricing should therefore be minimal. In contrast, differentiated products that are
by definition specific to the relationship lack such comparable arm’s length transactions
(Blonigen et al. 2014). Thus, MNEs that are exporting differentiated products might more
easily reduce taxes via transfer pricing.32 In columns (5) and (6), we use the Rauch (1999)
classification and document the effect of taxes and tax havens on both the homogenous and
the differentiated goods category. Goods that are exchanged on organized markets, i.e. where
appropriate prices are easily verified by tax authorities, show no differences between intra-
and extra-firm transactions. Differentiated products, on the other hand, do show evidence
of such. Notice that the estimated coefficient reported in column (6) are in line with the one
found in the baseline estimation (Column (6) of Table 2).
In column (7), we show that our baseline results are robust to the exclusion of the
observations of firms active in the wholesale sectors as the pricing behavior of such firms
may differ from that of others. As can be seen, the results are robust to their exclusion.
Last, we deal with the self-selection of firms into the multinational status. As emphasized
by Helpman et al. (2004), the selection of firms into multinationals depends upon a set of
firm characteristics and on barriers to entry and other destination market characteristics such
as the level of competition. These characteristics may well be influenced by the corporate
tax rate or the tax haven status of the destination market. Our specification allows for
the possibility that market characteristics vary across industries and across countries.33 In
column (8), we include country ×HS1-industry fixed effects and show that our main results
remain.
In table 7of the appendix, we provide the estimates using the EATR variable. We find
that our results are robust to the use of this alternative definition of the corporate tax rate.
Back-of-the-envelope calculation. To quantify the loss for tax authorities due to trans-
fer pricing, we use the estimates of the baseline estimation, column (4). In our quantification
exercise, we compute the loss of the exports due to lower pricing in tax havens. In 1999, the
French effective corporate tax rate was 31.77 percent and brought in about 36 billion euros
of corporate tax receipts.34
In column (3) of Table 2, we find that intra-firm prices are 10.4% (exp(-0.11)-1) lower
31This means applying prices that independent enterprises would set in identical transactions (B.O.I.
1999).
32Bernard et al. (2006) find that the difference between intra- and extra-firm prices is larger for differenti-
ated goods than homogenous ones, however, they do not estimate how the effect of taxes impacts the price
wedge across groups.
33In our model, it means that the demand shifter Ais country-product specific.
34http://www.performance-publique.budget.gouv.fr/farandole/archives/1999/lftab99.htm. Taxes are
charged on the taxable income which consists of operational and financial profits minus charges.
20
Table 4: Under-reporting to tax havens
Country Sh. French Sh. exports Value not reported
exports intra-firm (million euros)
Switzerland 0.0407 0.58 590.0
Ireland 0.0083 0.62 129.0
Singapore 0.0072 0.58 105.0
Hong Kong 0.0071 0.54 96.3
Luxembourg 0.0056 0.37 51.3
Malta 0.0019 0.88 42.3
Cyprus 0.0007 0.53 9.9
Bermuda 0.0003 0.85 5.9
Bahamas 0.0002 0.51 2.8
Cayman Islands 0.0001 0.55 0.7
than the market price in tax havens.35 Table 4reports the share of exports and the share of
these that were intra-firm for the ten tax havens. As can be seen, three of these countries
are important export destinations. Further, the shares of intra-firm exports to Switzerland
and Ireland are very high (around 60%). Using the intra-firm trade values in the data, the
final column gives the value of under-priced intra-firm exports, the sum of which amounts
to more than one billion euros. Without this under-reporting, French tax authorities would
have collected 340 million euros more. This figure can be compared to the 36 billion euros
collected in 1999 (which includes both services and manufacturing), meaning that total tax
revenues in that year would have been roughly 1% greater were it not for transfer pricing
by manufacturing firms in these ten tax havens.36 Interestingly, only 2,495 firms make
intra-firm exports to these countries with a scant 450 firms accounting for 90% of intra-firm
exports to these ten countries. More so, almost 50% of intra-firm exports to these tax haven
destinations are done by 25 firms. This suggests that a small number of firms are avoiding a
large tax payment. This is an important factor to acknowledge as the OECD’s (2012) survey
of tax authorities finds that the cost of pursuing transfer pricing MNEs is of major concern.
Our results suggest that the lion’s share of transfer pricing practiced in France is con-
centrated in the exports to at most ten countries by about 7% of multinationals. Targeting
exports by these firms to tax havens would make enforcement of the arm’s length price
principle more efficient.
5 Conclusion
Despite the clear incentive firms have to shift profits through transfer pricing and the
widespread concern over its implications, direct and systematic evidence of this practice
35We consider all intra-firm exports not only the ones used in our estimates.
36Note that this number does not consider any transfer pricing in the services sector for these countries.
21
remains scarce. This is due to a general lack of data on the prices used within a multina-
tional and the prices for comparable arm’s length transactions. Thus, the importance of
transfer pricing practices in terms of monetary value and of number of firms and countries
involved remains largely unanswered.
We have built a unique dataset that overcomes this problem. These data contain prices at
the firm-product-destination level for both intra-firm and arm’s length exports. This level of
data is important for three key reasons. First, it allows us to control for other determinants
of prices across firms, such as the relative productivity of multinationals as compared to
exporters. Second, it allows us to control for the destination country’s characteristics, such
as income and trade costs, which are potentially correlated with tax variables yet impact
intra-firm and arm’s length prices in different ways. Third, the richness of the data allows
us to consider not only the effect of foreign corporate taxes on pricing behavior, but also the
role of tax havens and how this behavior varies with firm and product characteristics.
We find that internal prices are lower in destinations with lower tax rates and most
importantly in tax havens. Furthermore, transfer pricing is primarily found within large
MNEs. These results are crucial for two reasons. First, they support the OECD’s (2013)
assertion that there is a difference between low-tax countries and tax havens which provide
a tax environment particularly amenable to tax avoidance. Second, it shows that although
transfer pricing may result in significant revenue losses, such losses are primarily due to a
small number of firms. Given that our estimates are for 1999 alone, the cumulative tax
losses from such transfer pricing should be quite large. This implies that by appropriately
targeting enforcement, a significant increase in revenues may be achieved at a small cost.
Moreover, since our data is only for manufacturing, and not services, this tax loss is likely
just the tip of the iceberg.
References
Atalay, E., Hortacsu, A. & Syverson, C. (2014), ‘Vertical integration and input flows’, Amer-
ican Economic Review 104(4), 1120–48.
Bartelsman, E. J. & Beetsma, R. M. W. J. (2003), ‘Why pay more? Corporate tax avoidance
through transfer pricing in OECD countries’, Journal of Public Economics 87(9-10), 2225–
2252.
Bastos, P. & Silva, J. (2010), ‘The quality of a firm’s exports: Where you export to matters’,
Journal of International Economics 82(2), 99–111.
Becker, J. & Davies, R. B. (2014), A Negotiation-Based Model of Tax-Induced Transfer
Pricing, mimeo.
Behrens, K., Peralta, S. & Picard, P. M. (2009), Transfer Pricing Rules, OECD Guidelines,
and Market Distortions, Cahiers de recherche 0943, CIRPEE.
22
Berman, N., Martin, P. & Mayer, T. (2012), ‘How do Different Exporters React to Exchange
Rate Changes?’, The Quarterly Journal of Economics 127(1), 437–492.
Bernard, A. B., Jensen, J. B. & Schott, P. K. (2006), Transfer Pricing by U.S.-Based Multi-
national Firms, NBER Working Papers 12493, National Bureau of Economic Research,
Inc.
Blonigen, B. A., Oldenski, L. & Sly, N. (2014), ‘Separating the Opposing Effects of Bilateral
Tax Treaties’, American Economic Journal: Economic Policy 6(2), 1–18.
B.O.I. (1999), Bulletin Officiel des Impots/Official Tax Bulletin, general tax directorate,
Technical report.
Clausing, K. A. (2003), ‘Tax-motivated transfer pricing and US intrafirm trade prices’, Jour-
nal of Public Economics 87(9-10), 2207–2223.
Cristea, A. D. & Nguyen, D. X. (2014), Transfer Pricing by Multinational Firms: New
Evidence from Foreign Firm Ownerships, mimeo.
Dharmapala, D. & Hines, J. R. (2009), ‘Which countries become tax havens?’, Journal of
Public Economics 93(9-10), 1058–1068.
Dharmapala, D. & Riedel, N. (2013), ‘Earnings shocks and tax-motivated income-shifting:
Evidence from European multinationals’, Journal of Public Economics 97(C), 95–107.
Diewert, E., Alterman, W. & Eden, L. (2006), Transfer Prices and Import and Export
Price Indexes: Theory and Practice, in ‘Price and Productivity Measurement’, W. Erwin
Diewert, Bert M. Balk, Dennis Fixler, Kevin J. Fox and Alice O. Nakamura.
Ernst & Young (2012), Transfer pricing global reference guide, Ernst and Young.
Fuest, C., Huber, B. & Mintz, J. (2003), Capital Mobility and Tax Competition: A Survey,
CESifo Working Paper Series 956, CESifo Group Munich.
Goldberg, L. S. & Campa, J. M. (2010), ‘The Sensitivity of the CPI to Exchange Rates:
Distribution Margins, Imported Inputs, and Trade Exposure’, The Review of Economics
and Statistics 92(2), 392–407.
Gresik, T. A. (2001), ‘The Taxing Task of Taxing Transnationals’, Journal of Economic
Literature 39(3), 800–838.
Gumpert, A., Hines, J. R. & Schnitzer, M. (2011), The Use of Tax Havens in Exemption
Regimes, NBER Working Papers 17644, National Bureau of Economic Research, Inc.
Haufler, A. & Schjelderup, G. (2000), ‘Corporate tax systems and cross country profit shift-
ing’, Oxford Economic Papers 52(2), 306–25.
23
Heckemeyer, J. H. & Overesch, M. (2013), Multinationals’ profit response to tax differentials:
Effect size and shifting channels, ZEW Discussion Papers 13-045, ZEW - Zentrum fÃijr
EuropÃďische Wirtschaftsforschung / Center for European Economic Research.
Helpman, E., Melitz, M. J. & Yeaple, S. R. (2004), ‘Export Versus FDI with Heterogeneous
Firms’, American Economic Review, American Economic Association 94(1), 300–316.
Hines, J. R. & Rice, E. M. (1994), ‘Fiscal Paradise: Foreign Tax Havens and American
Business’, The Quarterly Journal of Economics 109(1), 149–82.
Huizinga, H. & Laeven, L. (2008), ‘International profit shifting within multinationals: A
multi-country perspective’, Journal of Public Economics 92(5-6), 1164–1182.
Kant, C. (1988), ‘Endogenous transfer pricing and the effects of uncertain regulation’, Jour-
nal of International Economics 24(1-2), 147–157.
Keuschnigg, C. & Devereux, M. P. (2013), ‘The arm’s length principle and distortions to
multinational firm organization’, Journal of International Economics 89(2), 432–440.
Loretz, S. (2008), ‘Corporate taxation in the OECD in a wider context’, Oxford Review of
Economic Policy 24(4), 639–660.
Manova, K. & Zhang, Z. (2012), ‘Export prices across firms and destinations’, The Quarterly
Journal of Economics 127(1), 379–436.
Martin, J. (2012), ‘Markups, quality, and transport costs’, European Economic Review
56(4), 777–791.
Mayer, T. & Zignago, S. (2006), Notes on cepii’s distances measures, MPRA Paper 26469,
University Library of Munich, Germany.
OECD (2000), Towards Global Tax Cooperation.
OECD (2010), OECD Transfer Pricing Guidelines for Multinational Enterprises and Tax
Administrations.
OECD (2012), Dealing Effectively with the Challenges of Transfer Pricing.
OECD (2013), Action Plan on Base Erosion and Profit Shifting.
Overesch, M. (2006), Transfer pricing of intrafirm sales as a profit shifting channel: evidence
from German firm data, ZEW Discussion Papers 06-84, ZEW - Zentrum fÃijr EuropÃďis-
che Wirtschaftsforschung / Center for European Economic Research.
Ramondo, N., Rappoport, V. & Ruhl, K. J. (2011), Horizontal vs. vertical fdi : Revisiting
evidence from u.s. multinationals, Working Papers 11-12, New York University, Leonard
N. Stern School of Business, Department of Economics.
24
Rauch, J. E. (1999), ‘Networks versus markets in international trade’, Journal of Interna-
tional Economics 48(1), 7–35.
Simonovska, I. (2010), Income differences and prices of tradables, NBER Working Papers
16233, National Bureau of Economic Research, Inc.
Swenson, D. L. (2001), ‘Tax reforms and evidence of transfer pricing’, National Tax Journal
54(n. 1), 7–26.
Vicard, V. (2014), Transfer pricing of multinational companies and aggregate trade, mimeo.
Zucman, G. (2014), ‘Tax Evasion on Offshore Profits and Wealth’, Journal of Economic
Perspectives, (forthcoming) .
25
Table 5: Countries, EATR, EMTR and Tax Havens in 1999
Country EATR EMTR Country EATR EMTR Country EATR EMTR
Bahamas∗∗ 0.00 0.00 Bulgaria 0.24 0.27 Czech Republic 0.30 0.31
Ireland∗∗ 0.08 0.09 Norway 0.25 0.26 China 0.30 0.31
Hong-Kong∗∗ 0.09 0.12 Great-Britain 0.25 0.26 Uruguay 0.30 0.30
Slovenia 0.12 0.18 Cyprus∗∗ 0.25 0.25 Spain 0.31 0.32
South-Africa 0.15 0.21 Denmark 0.25 0.28 New-Zealand 0.31 0.31
Estonia 0.17 0.20 India 0.26 0.29 Brazil 0.31 0.32
Chile 0.17 0.16 Trinidad and Tobago 0.26 0.29 Canada 0.31 0.32
Turkey 0.17 0.23 Luxembourg∗∗ 0.28 0.30 Australia 0.31 0.33
Switzerland∗∗ 0.18 0.21 Portugal 0.28 0.31 Colombia 0.32 0.33
Korea 0.20 0.24 Indonesia 0.29 0.29 Italy 0.33 0.35
Guatemala 0.21 0.23 Greece 0.29 0.32 United States of America 0.33 0.34
Sweden 0.21 0.23 Netherlands 0.29 0.31 Poland 0.34 0.34
Mexico 0.22 0.26 Austria 0.29 0.31 Argentina 0.35 0.35
Finland 0.22 0.24 Peru 0.29 0.29 Japan 0.41 0.41
Ecuador 0.22 0.23 Belgium 0.29 0.33 Germany 0.42 0.43
Note: ∗∗ Tax Havens as defined by Hines & Rice (1994).
26
Table 6: Baseline regression Effective Average Tax Rate, All firms
Dependent variables: Export price
(1) (2) (3) (4) (5) (6)
(1 −τc)0.12 0.12 -0.02 -0.04
(0.870) (0.847) (-0.211) (-0.419)
− × Intraf pmc -0.22∗∗ -0.22∗-0.11 -0.06 -0.08
(-2.277) (-1.994) (-1.590) (-1.248) (-1.253)
T axH avenc0.11 0.12
(1.574) (1.561)
− × Intraf pmc -0.11∗∗ -0.09∗∗ -0.09∗∗∗
(-2.686) (-2.346) (-2.795)
P er Capita GDPc-0.03∗∗ -0.01 -0.01 -0.02∗-0.00
(-2.636) (-1.108) (-1.178) (-1.715) (-0.390)
− × Intraf pmc -0.03∗∗∗ -0.01 -0.01 -0.02∗-0.01
(-3.269) (-1.138) (-1.320) (-2.024) (-0.628)
Distancec0.08∗∗∗ 0.08∗∗∗ 0.08∗∗∗ 0.11∗∗∗
(2.849) (3.631) (3.651) (4.301)
− × Intraf pmc -0.04∗∗∗ -0.05∗∗∗ -0.05∗∗∗ -0.06∗∗∗ -0.05∗∗∗
(-2.806) (-4.811) (-4.440) (-4.961) (-4.151)
T arif fc0.03 0.03 0.03 0.01
(1.056) (1.122) (1.165) (0.425)
− × Intraf pmc -0.03∗-0.03∗∗ -0.03∗∗ -0.02 -0.03∗∗∗
(-1.986) (-2.617) (-2.397) (-1.596) (-3.125)
Sample Full Full Full Full w.o Tax H. Full
Country FE No No No No No Yes
Firm-Prod.-Mode FE Yes Yes Yes Yes Yes Yes
Observations 756,332 735,064 735,064 735,064 657,117 735,064
Adj. R20.862 0.865 0.865 0.865 0.870 0.866
Note: This table investigates the impact of effective taxe rate, GDP per capita, distance, tariffs, and tax
haven dummy on intra-firm and arm-length export prices. Effective tax rates are transformed as follows:
(log(1 −τ)). All regressions include firm-product-exporting mode fixed effects. The last column further
includes country fixed effects. In column (5) we restrict the sample to countries not classified as tax havens.
Robust standard errors clustered by destination are computed. Corresponding t-statistics are reported in
parentheses. Significance levels: ∗p < 0.1,∗∗ p < 0.05, and ∗∗∗p < 0.01.
27
Table 7: Additional results, Effective Average Tax Rates
Dependent variables: Export price
(1) (2) (3) (4) (5) (6) (7) (8)
Intraf pmc×:
(1 −τc)-0.05 -0.13 -0.14 -0.04 -0.01 -0.10∗-0.10 -0.07
(-0.950) (-1.174) (-1.614) (-0.567) (-0.097) (-1.972) (-1.677) (-1.112)
T axH avenc-0.11∗∗∗ -0.01 -0.08∗∗∗ -0.11∗∗ -0.05 -0.07∗∗∗ -0.09∗∗∗ -0.10∗∗∗
(-7.533) (-0.177) (-3.306) (-2.287) (-0.779) (-3.706) (-3.776) (-2.673)
P er Capita GDPc-0.00 -0.00 -0.02 0.02 -0.04 -0.01 -0.01 -0.01
(-0.618) (-0.047) (-1.453) (1.505) (-1.364) (-1.164) (-1.144) (-0.530)
Distancec-0.05∗∗∗ -0.06∗∗∗ -0.07∗∗∗ -0.04∗∗∗ -0.01 -0.05∗∗∗ -0.05∗∗∗ -0.06∗∗∗
(-4.971) (-3.586) (-5.170) (-3.473) (-0.166) (-4.925) (-5.356) (-4.695)
T arif fc-0.03∗∗∗ -0.03 -0.05∗∗∗ -0.02∗0.01 -0.04∗∗∗ -0.04∗∗∗ -0.03∗∗
(-4.141) (-1.305) (-3.462) (-1.768) (0.371) (-3.944) (-3.664) (-2.527)
Sample Big Small French Foreign Homog. Diff. w/o
firms firms firms MNEs goods goods wholesale All
Firm-Prod.-Mode FE Yes Yes Yes Yes Yes Yes Yes Yes
Country FE Yes Yes Yes Yes Yes Yes Yes No
Cty-Sect. FE No No No No No No No Yes
Observations 716,158 686,580 571,872 458,998 11,659 603,575 558,313 735,064
Adj. R20.868 0.869 0.876 0.871 0.847 0.885 0.868 0.932
Note: This table investigates the impact of effective taxe rate, GDP per capita, distance, tariffs, and tax
haven dummy on intra-firm and arm-length export prices. All regressions include firm-product-exporting
mode fixed effects. Column (1) focuses on MNEs whose export sales are above the P75. Column (2)
focuses on MNEs whose export sales are below the P25. Column (3) exclude affiliates of foreign MNEs
located in France. Column (4) exclude French MNEs. Column (5) contains only the products classified as
homogeneous in Rauch nomenclature. Column (6) contains only the products classified as differentiated in
Rauch nomenclature. Column (7) exclude MNEs whose main activity abroad is wholesale. Robust standard
errors clustered by destination are computed. Column (8) display the results with Country and sector fixed
effects. Corresponding t-statistics are reported in parentheses. Significance levels: ∗p < 0.1,∗∗ p < 0.05, and
∗∗∗p < 0.01.
28