Profit shifting in the Norwegian and British petroleum industry:
Differentiating between the real and the
shifting response to tax changes
Helene Vada
Master of Philosophy in Economics
Department of Economics
University of Oslo
May, 2016
II
III
Profit shifting in the Norwegian and British petroleum industry: Differentiating
between the real and shifting response to tax changes.
IV
© Helene Vada
2016
Profit shifting in the British and Norwegian petroleum industry: Differentiating between the
real and the shifting response to tax changes
Helene Vada
http://www.duo.uio.no/
Trykk: Reprosentralen, Universitetet i Oslo
V
Abstract In this master’s thesis, I explain the concept of profit shifting within multinational enterprises
and investigate whether petroleum companies on the Norwegian and British continental
shelves engage in tax motivated profit shifting, by applying ordinary least squares and
company fixed effects estimation.
To be able to distinguish between traditional tax distortions and profit shifting, I extend the
model developed by James R. Hines and Eric M. Rice in their 1994 article “Fiscal Paradise:
Foreign Tax Havens and American Business” published in The Quarterly Journal of
Economics, by including the statutory tax rate that applies to the petroleum companies and the
parent companies’ corporate income tax rates as separate explanatory variables in the
regressions, while also performing regressions using the tax difference as explanatory
variables. The majority of previous studies on profit shifting use the average tax difference
between affiliates as the explanatory variable. The tax difference variable used in this thesis is
a simplified version including only the difference between the tax rates that apply to the
petroleum affiliate and the parent company. As companies also have the option of shifting
profits to other affiliates within the group, the simplified tax difference variable is expected to
capture only parts of any profit shifting. I propose that the statutory tax rate that applies to the
petroleum companies also represent the tax difference between the petroleum affiliate and the
affiliates located in a country with a corporate income tax rate of zero. As this is the most
profitable channel for profit shifting, the coefficients that result from a regression of reported
profits on the tax rate that applies to the petroleum companies can also be interpreted as the
semi-elasticity of reported profits with respect to the maximum tax difference between the
petroleum company in question and its affiliates.
Previous studies have shown that the semi-elasticities of reported profit with respect to the tax
difference between the affiliate at hand and its group members are in the range [-3,-0.5]. The
corresponding semi-elasticities that result in this thesis are in the range [-3, -1.4]. The semi-
elasticities of reported profit with respect to the petroleum tax rate are in the range [-5.5, -0.1],
while semi-elasticities of reported profits with respect to the parent company tax rate are in
the range [-12.4, 3.3]. I conclude that there is some evidence of profit shifting in the data, and
that some of the results are comparable to the ones from previous studies.
VI
VII
Preface This thesis was written as a completion of the Master of Philosophy in Economics at the
University of Oslo.
I want to thank my supervisor Professor Diderik Lund for invaluable guidance, for generously
sharing his knowledge about taxation of petroleum companies and the at times confusing
world of multinational petroleum enterprises.
I also want to thank Oslo Fiscal Studies (OFS) for granting me one of the OFS Scholarships
for 2016 and for providing me with workspace in their offices.
Writing a master’s thesis is a lonely project, which is why I want to thank my friends and
study partners, Thea and Pauliina, for providing moral support and companionship.
At last I wish to thank my friends and family for giving me advice and encouragement
throughout this period.
VIII
IX
Contents 1 Introduction ........................................................................................................................ 1
1.1 Background .................................................................................................................. 1
1.1.1 History of international profit shifting ................................................................. 1
1.1.2 Profit shifting in the hydrocarbon industry .......................................................... 3
1.1.3 Main research question ......................................................................................... 4
1.1.4 Overview of this thesis ......................................................................................... 4
1.2 Government revenue from natural resources ............................................................... 4
1.2.1 Resource rent taxation .......................................................................................... 6
1.2.2 Royalties, Production Sharing Agreements and other arrangements ................... 7
1.3 Why look at the petroleum sector in Norway and in the UK? .................................... 8
1.3.1 Similarities of production conditions and history ................................................ 8
1.3.2 Differences in taxation ......................................................................................... 8
2 Theory and previous research on the subject ................................................................... 12
2.1 Tax distortions ........................................................................................................... 12
2.1.1 Tax rates and investment .................................................................................... 13
2.1.2 Statutory tax rates and profit shifting ................................................................. 14
2.2 Previous work on the subject ..................................................................................... 14
2.3 Theory on profit shifting ............................................................................................ 23
2.3.1 The Hines & Rice approach ............................................................................... 23
3 Empirical strategy ............................................................................................................ 26
3.1 Model ......................................................................................................................... 26
3.1.1 Using the Hines & Rice approach ...................................................................... 26
3.1.2 Modifying the model to capture the traditional tax distortions .......................... 28
3.2 Data ............................................................................................................................ 31
3.2.1 The Amadeus data .............................................................................................. 31
3.2.2 Estimating the actual fraction of PRT-liable income ......................................... 32
3.3 Fixed Effects and OLS estimation ............................................................................. 33
3.3.1 Panel data, explanation and transformation of variables .................................... 33
3.3.2 Fixed effects and unobservables ........................................................................ 36
3.3.3 OLS estimation ................................................................................................... 37
4 Results and interpretation ................................................................................................. 38
X
4.1 Specifications and control variables .......................................................................... 38
4.1.1 Results from the OLS estimation ....................................................................... 39
4.1.2 Results from the company fixed effects estimation ........................................... 42
5 Conclusion ........................................................................................................................ 46
Bibliography ............................................................................................................................. 49
Appendix .................................................................................................................................. 52
Table 1: ..................................................................................................................................... 39 Table 2 ...................................................................................................................................... 42 Table 3 ...................................................................................................................................... 52 Table 4 ...................................................................................................................................... 53 Table 5 ...................................................................................................................................... 54 Table 6 ...................................................................................................................................... 55 Table 7 ...................................................................................................................................... 55 Table 8 ...................................................................................................................................... 56 Table 9 ...................................................................................................................................... 57
1
1 Introduction
1.1 Background
In this part I provide a background on the subject of international profit shifting in general and
in the petroleum industry in particular. I present my research question and give a brief outline
of the content of my thesis.
1.1.1 History of international profit shifting
Over the last 20 years, a greater interest in multinational enterprises’ (MNEs’) behavioral
response to taxes has developed both within media, in politics and in economic research.
Recently this has been induced by anecdotes about certain high profile companies that have
paid surprisingly little taxes. Some investigation into the matter has revealed that companies
through complex systems of intra-group trade are able to limit their corporate tax liability
extensively and, in some cases, eliminate corporate tax liability all together (Gompertz, 2012;
Stewart, 2015).
MNEs have the opportunity to take advantage of differences in tax rates, mainly through
distorting prices on intra-firm traded items and through the allocation of debt and equity,
thereby shifting profits to lower taxed jurisdictions. This is done to reduce the overall tax
liability of the MNE. This is eroding the tax bases of governments all over the world, which is
why this type of tax avoidance is referred by the OECD as base erosion and profit shifting
(BEPS).
The problem of BEPS within MNEs is by the OECD regarded as severe, and also by national
policy-makers and by other international organizations, e g. Tax Justice Network (2015).
BEPS poses a serious problem for governments all over the world, as it puts pressure on the
scope for taxation. The OECD estimates lost government tax revenue in the realms of $100 –
240 billion annually.
“The findings of the work performed since 2013 highlight the magnitude of the issue, with
global corporate income tax (CIT) revenue losses estimated between 4% and10% of global
CIT revenues, i.e. USD 100 to 240 billion annually. Given developing countries’ greater
2
reliance on CIT revenues, estimates of the impact on developing countries, as a percentage of
GDP, are higher than for developed countries.” (OECD, 2015, p. 15)
The OECD has in recent years launched an initiative to investigate the existence and extent of
BEPS among MNEs and to introduce new or more effective ways to counter BEPS
multilaterally. This in addition to, or in place of, existing countermeasures that are mainly
unilateral, individual country, anti-avoidance rules (OECD, 2015, p. 106). Such unilateral
rules are for instance Germany’s interest barrier rule, an example of a thin-capitalization rule,
introduced in 2008, which limits the deductibility of interest expenses to 30% of EBITDA.
The introduction of this rule led to a decrease in firms’ debt-to-asset ratio and had no negative
effect on investments (Simmler, 2012, p. 24). The possibility of intra-group lending can result
in attempts by an MNE to present what is in reality equity investment as financed by debt, to
exploit the more favourable tax treatment of debt compared to equity in many countries.
Another example of rules to counter BEPS is the arm’s length principle. It is an evaluation
principle applied to commercial and financial transactions between related companies. It is
defined by the OECD as the principle that transactions should be valued as if they had been
carried out between unrelated parties, each acting in his own interest (OECD, 2006, p. 176).
The arm’s length principle has been incorporated in the Norwegian General Tax Act, section
13-1, and is in line with Article 9 in the OECD Model Tax Convention (OECD, 2014, pp. 29-
30) and the OECD’s Transfer Pricing Guidelines (OECD, 2010, p. 36). In Norway this
implies that all corporations that trade with related parties are required to file a separate form
in which the nature and scope of the transaction and accounts outstanding with associated
companies or entities are specified, as an attachment to the annual tax return. Small and
medium sized companies outside the petroleum industry are under certain circumstances
exempt from this requirement (OECD, 2012, pp. 2-4). The tax legislation in the UK is also
construed in a manner that is consistent with Article 9 in the OECD Model Tax Convention
and OECD’s Transfer Pricing Guidelines (HM Revenue & Customs, 2016b). The UK does
not have the same documentation requirements, yet provides an Advance Pricing Agreement
that is a written agreement between a business and the Commissioners of HM Revenue &
Customs (HMRC). It determines a method for resolving transfer pricing issues in advance of
the tax return being filed, to provide assurance to the business that the treatment of those
transfer pricing issues will be accepted by the HMRC (HM Revenue & Customs, 2010). The
3
HMRC can require any person to provide them with information, and penalties may arise for
failing to comply with an information notice (Beer & Loeprick, 2015b, p. 27).
For some traded items, however, arms-length prices can be hard to establish, for instance
when the traded item is a bespoke item, as is common for input factors in the petroleum
sector, and when there does not exist a well-functioning market for the good in question, for
instance for many used capital goods.
1.1.2 Profit shifting in the hydrocarbon industry
The international oil and gas industry has over the history been dominated by multinational,
vertically integrated enterprises. These enterprises’ decisions are based on their overall
worldwide interests and are imposed on their affiliates in a range of different locations (Parra,
2004, p. 272). This creates opportunity for tax motivated profit shifting, for instance through
transfer pricing arrangements that overprice sales from affiliates in low-tax jurisdictions to
affiliates in high-tax jurisdictions, and underprice sales from affiliates in high-tax jurisdictions
to affiliates in low-tax jurisdictions. The multinational petroleum enterprises also have the
opportunity to reduce world-wide tax liability through captive insurance companies or by
decisions on debt-equity allocation. Captive insurance companies are insurance companies
that are wholly owned and controlled by its insureds or by a member of the insureds’ group.
While its primary purpose is to insure the risk of its owners, the captive insurance company,
who are often located in tax havens, can design its insurance policies such that the price of
insurance overstate the risk faced by the insurance company. While the insured may be able to
fully deduct the costs of insurance from the tax base, the captive insurance company often
faces a considerably lower tax rate on its profits, and hence represents a channel for profit
shifting.
Affiliated exploration and production (E&P) companies of larger multinational groups may
choose to borrow from related parties to obtain larger loans than unrelated parties would be
willing to offer, but also be subject to higher interest rates than what the arm’s length
principle would imply (HM Revenue & Customs, 2016d). Common for these practices are the
use of the enterprises’ multinationalism for exploiting differences is tax rates and tax rules to
reduce tax liabilities.
4
1.1.3 Main research question
I will attempt to answer two questions. Firstly: To what extent do multinational hydrocarbon
companies that are active in Norway and in the United Kingdom engage in profit shifting?
And secondly: What is the importance of profit shifting relative to the more traditional
distortionary effects of taxation in explaining the changes in reported profits one can observe
when tax rates change?
1.1.4 Overview of this thesis
To be able to answer these questions, I first give a brief explanation of the central concepts
that are discussed throughout the thesis and a theoretical overview of the subject. Theories on
tax distortions, taxes’ implications for firm’s decisions on investment and financing as well as
theories on profit shifting are covered in chapter two, along with a presentation of central
empirical research on the subject.
I give a presentation of my method to empirically test my hypotheses in chapter three,
including a presentation of my data and the work on collecting these.
In chapter four I present my findings and discuss the results.
Left to chapter five is my conclusion and suggestions for future work on the subject. I also
discuss the validity of my results and some possible weaknesses of the analysis.
1.2 Government revenue from natural resources
Oil and gas are very valuable, yet non-renewable, natural resources. In most countries,
including Norway and the United Kingdom, oil and gas reserves are the legal property of the
state. This legal right to the resource is exercised in various ways: National oil companies
(NOCs) accounted for 75 % of the global oil production and controlled 90 % of the world’s
proven reserves in 2010 (Tracy, Tordo, & Arfaa, 2011, p. xi). Through NOCs, governments in
resource rich countries manage to extract revenue both through dividends and taxes. The
development of NOCs started in 1908 in Austria-Hungary as a way to increase refining
capacity in a time where private oil producers faced an excess supply of crude. As oil became
an increasingly important strategic commodity, more governments started to set up or
participate in oil companies, to control the domestic markets and to pursue upstream
5
operations (Tracy et al., 2011, p. 16). Both the United Kingdom and Norway have used NOCs
to extract the value of petroleum resources discovered on their continental shelves: The
British government established the British National Oil Corporation (BNOC) as a
nationalized body in 1975 (Parra, 2004, p. 274) and it was given the objective to “exercise the
state participation rights” (Noreng, 1980, p. 51). Its business was transferred to a new
company, Britoil, in 1982, and it was privatized in two stages, in 1982 and 1985, before it was
bought by British Petroleum in 1988
The Norwegian government established Den Norske Stats Oljeselskap A/S, later to be known
as Statoil, in 1972. It continued as a fully state-owned company until 2001, when it was
gradually privatized, but its majority shareholder is still the government of Norway, holding
67% of the shares.
There are several reasons why both Norway and the UK have put gradually less weight on the
state’s direct involvement with exploration and production of oil and gas through NOCs.
These are in part political: Throughout the late 1970s and 1980s, the neoliberal ideology that
was dominating British politics sought privatization and less state involvement in the market
for private goods. Although the Norwegian political sphere was less explicitly neoliberal, the
development throughout the 1990s and onwards was toward deregulation and privatization of
state owned enterprises. One important reason for establishing a state owned petroleum
company, Statoil, was Norway’s objective of developing a domestic workforce with the
necessary skillset and knowledge about the offshore petroleum industry. With some twenty to
thirty years of experience with petroleum exploration and production, this need was
considered met, which is probably the main reason why Norwegian politicians in 2001
decided to partly privatize Statoil.
Unless firms in the private sector are able to retain some share of the profits however, it is not
likely that they will undertake the job of finding and producing the oil and gas. Even if firms
are given capital allowance in order to avoid taxation of the normal return to capital, the
entrepreneurial effort necessary to undertake large offshore projects is hard to value for the
purpose of deducting costs. The task of the government is therefore to choose a fiscal regime
that is stable, that provides the incentives necessary for firms to undertake the projects and
that secures for the public the share of the economic rent that is deemed to be right. Economic
rent can be defined as the amount by which the payment for some good or service exceeds the
minimum that is required for the good or service to be produced (Boadway & Keen, 2010, p.
6
15). It is not necessarily clear how large a ‘right’ share is. Some would claim that the right
share is 100%, as the state has the legal right to the resource. The government should aim to
maximise public welfare given the constraint that firms in the private sector probably need to
be given some incentive to participate in the exploration and production of oil and gas.
Depending on whether the petroleum firms are domestic or foreign, some weight could be
assigned to the private profits of the firms when maximising public welfare.
The governments have several different tools to choose from: Rent taxes, royalties,
production sharing agreements, and licensing fees are the most common among these.
1.2.1 Resource rent taxation
A commonly used principle in tax theory builds on a hierarchical view of taxes, with
externality correcting taxes (Pigouvian taxes) being superior to neutral taxes as these improve
economic efficiency. Neutral taxes have no impact on economic efficiency, and are therefore
superior to distortive taxes, which reduce economic efficiency. Externality correcting taxes
often aim to limit the consumption of the good onto which they are levied, which is why they
are not suited to the task of collecting the necessary amount of revenue to the state. Neutral
taxes should be used to their full capacity to collect revenue, before introducing distortionary
taxes (Sandmo, 1976).
Hindriks and Myles define a tax as being neutral with respect of a choice, if the tax does not
change the relative values of marginal benefits and marginal costs involved with that choice
(2013, p. 710). It has been claimed that a tax applied to economic rent does not distort the use
of productive factors. Firms employ capital, labour and other productive factors until the
return on the marginal unit is equal to the cost. At the margin, rents are zero (Mintz & Chen,
2012, p. 3).
A resource rent tax (RRT)1 is aimed at the extraordinary profits from resource extraction. One
type of neutral tax on firms is a proportional tax on real cash flows that gives full, immediate
loss offset, with refunds in years with negative cash flow (Fane, 1987, pp. 9-10). This tax is
similar to equity participation by the government, except the government does not have voting
rights. The neutrality comes from the fact that projects will be undertaken if the valuation of
1 Resource rent tax (RRT) is used as a generic term, not to describe any specific tax system
7
the cash flow of the project is strictly positive2. The after-tax value of the cash flow will only
be positive if the taxed value is positive, and by this the pure cash flow tax will not influence
decisions made by the firm on what projects to undertake. In standard economic theory on the
firm, there are no income effects (Hicks, 1939, as cited in de Villiers Graaff, 1950, p. 81) .
This implies that the state can use a neutral tax to collect part of the profit without this
affecting which projects the firm decides to undertake. For the resource rent tax to be neutral,
it must give firms full and immediate deduction for costs incurred in all phases of the
exploration and production of oil and gas, or the deductions must be carried forward from
years with insufficient earnings at the appropriate interest rate. If a firm goes out of business
with a forward-carried loss, the tax value of this loss must be refunded to the firm.
1.2.2 Royalties, Production Sharing Agreements and other arrangements
Royalties are payments from the firm to the government that are based on production
volumes3. The strength of such a regime is that it is not sensitive to cost information
asymmetry. As long as firms have private information about costs, and the firm is given
immediate or forward-carried deductions for costs, there is a risk that the firm will exaggerate
the costs associated with the exploration and production of oil and gas, thereby reducing their
tax liabilities. When taxation is based only on royalty, this risk is eliminated.
Production Sharing Agreements (PSAs) are arrangements where the government awards the
right to extract minerals, oil or gas, to a firm or a group of firms. The firms bear the entire risk
and financial responsibility of exploration and production. The firms are allowed to recover
costs when they start producing oil and/or gas. The amount of oil necessary to cover the costs
of exploration and production is called cost oil, and is usually upwards limited to an amount
called cost stop. The rest of the oil, after cost oil is deducted, is called profit oil and is split
between the firms and the government according to the agreement. PSAs are commonly used
in the Middle East and in Central Asia, sometimes in combination with corporate income tax
or fees on subsoil use. PSAs can be thought of as a combination of a tax system and rules
regarding the decision making process.
2 Valuation of a project, in the absence of risk, equals net present value. If risk is present, the valuation is based on expected cash flows and a risk adjusted discount rate. 3 Some authors use the term "royalties" in a wider meaning, to include taxes that allow deductions for reported costs. In what follows, royalties only refer to payments that allow no such deductions.
8
In order to maximise the value of the public’s share of the natural resources, the government
must consider all available instruments. Lund (2002, p. 220) shows that the choice between a
tax on pure rents and a gross tax on production (i.e., royalty payment) can be considered a
trade-off between the maximisation of the rent tax base and the need to reduce incentives for
transfer pricing. Unless the output price and the cost of profit shifting are above some upper
limit, and the productive cost parameter is below some lower limit, a mix of the two tax
instruments should be used if the objective is to maximise the value of the state’s share of the
resource.
1.3 Why look at the petroleum sector in Norway and in the UK?
1.3.1 Similarities of production conditions and history
To be able to better identify the effects of taxation on reported profits, it is necessary to
compare firms that are operating in similar environments. I have chosen to look at firms
operating on the British and Norwegian continental shelves, because the operating conditions
are comparable with regards to water depth, weather and geology. The quality of the crude is
also quite similar. The history of the development of offshore petroleum industry in the two
countries is also similar: From the mid-1960s and onwards, the UK offshore petroleum
industry was built. The first significant discovery of natural gas was made in 1965, when BP
made a successful drilling on a field that is now a part of the West Sole Field. In October
1970 BP struck oil in what was to be named the Forties oil field (Dukes Wood Oil Museum,
2007). On the Norwegian continental shelf, a small oil discovery was made by ESSO on the
Balder field in 1967, but the first commercially interesting discovery of oil was made in 1969.
Phillips Petroleum made a large discovery on the field that was to be named Ekofisk, which
started producing in 1971. A large discovery of natural gas, the Frigg field, was also made in
1971(Norsk Olje & Gass, 2010).
1.3.2 Differences in taxation
In this section, I provide an overview of the various elements of the fiscal regimes of the UK
and Norway in the time period for which I have data, 2005 – 2014. Some of the elements
9
described have changed in 2015 – 2016. The overview is limited to the elements relevant for
the petroleum industry.
The British petroleum fiscal regime consists of three main elements:
The Petroleum Revenue Tax (PRT) is a ring-fence tax that applies to profits derived from the
extraction of oil and gas from individual fields that were given development consent before
16 March 1993. The PRT was abolished for all fields given development consent on or after
this date. The ring-fencing arrangement of the PRT is on a field-by-field basis, which implies
that a firm’s profit derived from one field cannot be set off against the same firm’s losses
from another field. The PRT rate was reduced from 75% to 50% at the same time as it was
abolished for fields with development consent dated on or after 16 March 1993 (HM Revenue
& Customs, 2016c).
The Ring Fence Corporation Tax (RFCT) is a standard corporate tax applicable to all
companies in the petroleum sector with the addition of a ring fence. This ring fencing
arrangement implies that excessive interest payments or losses from activities in other sectors
cannot be deducted from the taxable profits from petroleum exploration and production, with
the intention of reducing the tax payments. However, unlike the ring-fencing arrangement of
the PRT which is on a field-by-field basis, the RFCT is ring-fenced for each company’s
activity in the whole petroleum sector (KPMG, 2012, p. 1). Since 1 April 1999 the RFCT has
been fixed at 30% (HM Revenue & Customs, 2013).
The Supplementary Charge (SC) is an additional charge on a company’s ring fence profits,
without deductions for finance costs. The SC was introduced on 17 April 2002 and was
originally set at 10% (HM Revenue & Customs, 2016a). On 1 January 2006 it was increased
to 20%. On 24 March 2011 it was further increased to 32%. The SC rate was reduced to 20 %
in 2015. Over the period considered in this paper, the only statutory tax rate that varies in the
UK is the SC rate. When calculating the tax liability of a company, any PRT liability is
deductible before taxing the remainder at the RFCT and SC rate, which implies that the total
statutory tax rate for a company whose profits derive in full from PRT-liable fields is
1 , which in 2015 was equal to [0.5 + (1-0.5)*(0.3+0.2)] =
0.75.
Interest payments are not deductible in PRT or SC. For RFCT purposes interest payments can
be set off against profit in the case the interest was paid in respect of money borrowed to
10
finance oil extraction activities or purchase of ring-fence assets, but restrictions apply: There
is no deduction for interest where the debt has “an unallowable purpose, involves ‘arbitrage’
or if the loan has unusual terms, for example quasi-equity characteristics” (Deloitte, 2013, p.
6) .
In addition to the three aforementioned main elements of the UK hydrocarbon fiscal regime,
there exist several special arrangements that apply to some fields (KPMG, 2012, p. 76):
‐ Small Field Allowance: Applies to fields producing less than 7.0 million tonnes oil
equivalents.
‐ Ultra Heavy Oil field allowance: Applies to fields that produce oil of especially high
viscosity, higher than 18 API (oil gravity) and under 50 centipoise (viscosity).
‐ Ultra HPHT (high pressure high temperature): Applies to fields where pressure is
higher than 12500 psi (pound-force per square inch) and temperature higher than
330 °F (≈ 166 °C).
‐ Deep Water field allowance: Applies to fields with higher than 1000 meters water
depth, and reserves of more than 187 million barrels of oil equivalent.
‐ Remote Deep Water Gas field allowance: Applies to fields that are more than 60
kilometers from infrastructure, more than 300 meters water depth and where reserves
are more than 75% gas.
‐ Shallow Water large Gas field allowance.
‐ Brown Field Allowance: Applies to FDP (Field Development Plan) Addenda.
In the rest of my paper, I have chosen to neglect these special arrangements. This is because
there is a large amount of variables that decide what arrangements apply to each individual
field, information that it is not possible for me to gather in an efficient and timely manner. As
this master thesis has a limited time frame, I could not prioritize to pursue this information.
The Norwegian petroleum fiscal regime consists of two main elements:
Corporate Income Tax (CIT) applies to all corporations operating in Norway. It was reduced
from 50.8 % to 28 % in 1992 and has been stable at 28 % for two decades. It was reduced to
27 % in 2014. The base for the CIT is sales income less operating costs (including exploration
costs and indirect taxes) and depreciation costs (by a linear schedule at up to 16.67% per year
over 6 years), less interest costs and losses carried forward from previous years (Norwegian
Ministry of Finance, 2013).
11
Corporations in the petroleum sector face an additional special surcharge of 50 % before
2014, later 51%. The special surcharge was increased from 50 % to 51 % when the CIT was
reduced to 27 %, to keep the total statutory tax rate unchanged. Uplift is given when
calculating the base for the special surcharge. The uplift is calculated as 5.5 % (reduced in
2014 from 7.5%) of the investment costs for four years from the investment was incurred. The
purpose of the uplift is to ensure that normal returns are not subject to the special surcharge
(Norwegian Ministry of Finance, 2013). Since none of these two taxes is deductible in the
base for the other tax, the total statutory tax rate for corporations in the petroleum industry is
78 %.
Companies that do not receive any income from petroleum activities while in the exploration
phase will be refunded the tax share of exploration costs. Moreover, any losses incurred
through later phases of the petroleum production can be carried forward with interest set by
the Norwegian Ministry of Finance (Deloitte, 2014, p. 5), and if a company ceases activity
with a forward-carried loss, the company will be refunded the tax-value of this loss. This is
rather unique in a global perspective.
Interest payments and other finance costs are deductible for tax purposes, provided the terms
are regarded to be on arm’s length basis, up to a certain limit (Deloitte, 2014, p. 4).
The Norwegian hydrocarbon fiscal regime aims to be as distortive as the regime that applies
to other industries. The intention is that the special surcharge does not create additional
distortions above the ones created by the CIT. Any project that is profitable under the CIT
shall remain profitable under the CIT and special surcharge, and vice versa.
Petroleum companies are in addition liable to area based royalty, CO2 emission fees and
minor license application fees.
12
2 Theory and previous research on the subject
2.1 Tax distortions
According to the Marshallian view of corporate taxes, the corporate income tax (CIT) falls
strictly on rents and is thus not distorting any decisions made by the firm. This rests on the
assumption that the cost of capital is deducted from the tax base (Atkinson & Stiglitz, 2015, p.
108). In what follows, full certainty is assumed for simplicity.
If a firm’s rent in the absence of taxes is given by , and in the
presence of a tax is given by 1 , , then the first order condition
for the choice of K is , in either instance, and so not influenced by the tax. If
the cost of capital is not, or only asymmetrically, deductible from the tax base (as when the
firm’s interest expenses are deducted, but not the cost of equity), then the non-distortionary
claims are no longer valid.
The British corporate tax regime allows for the deduction of interest costs when calculating
the RFCT, but the interest costs are added back to the tax base for the SC (Deloitte, 2013, p.
1). The Norwegian CIT provides full deduction for the cost of debt, but no deduction for the
cost of equity. The special surcharge base is the CIT base net of financing costs and uplift.
This is a peculiarity with the Norwegian special surcharge: The uplift applies equally to
equity and debt financed capital, while at the same time deduction for the cost of debt is
allowed up to a threshold4. This can potentially be too generous, and create distortions in the
positive direction: Firms may invest more than what is optimal. This was partly mediated with
a reduction of the uplift rate in 2014.
An increase in the statutory tax rate combined with limited or absent provisions for deducting
the cost of equity, will increase the cost of capital. As a general assumption, most firms’
production functions have decreasing returns to scale, implying that as the firm employs more
and more capital, the return to capital decreases. This in turn implies that as the cost of capital
4 The threshold is given by: ∗
% " "
, where the term
“relevant assets” is limited to production facilities and pipelines, other fixed assets in relation to the upstream activity, capitalized R&D in relation to the upstream activity, and other intangible assets in relation to the upstream activities (Deloitte, 2014).
13
increases, the company will invest less to restore the equality between the marginal product
and the marginal cost of capital. As there is no variation in the total tax rate that applies to
petroleum companies in Norway over the period 2005 – 2014, which is the period covered by
my data, the potential distortionary effect of this tax will not be explored any further.
2.1.1 Tax rates and investment
Multinational enterprises make decisions on several investment margins, both on the scale
and the timing of investments and on where to invest, if at all. These investment decisions all
depend on the expected profitability of the investment which again depends on, among other
factors, the current and expected future fiscal regime in the countries where their affiliates are
located. The scale of an investment depends on the marginal effective tax rate (METR), which
is the wedge between the before-tax required rate of return to investment for a marginal
project (p) and the after-tax rate of return to savers (r), expressed as a proportion of the
before-tax rate of return:
The METR depends on the statutory corporate tax rate, but also on the interaction with
personal taxes, depreciation rules, investment tax credits et cetera (Daniel, Goldsworthy,
Maliszewski, Puyo, & Watson, 2010, p. 199).
The average effective tax rate (AETR) is a measure of the difference between the net present
value (NPV) of a hypothetical project in the presence and absence of tax, scaled by the NPV
of income generated by the project in the absence of tax5. For a marginal project this is equal
to the METR, but as the rate of profit rises, it converges to the statutory tax rate. It can
therefore be considered a weighted average of the METR and the statutory tax rate, adjusted
for personal taxes (Devereux & Griffith, 2003, p. 108). When deciding on where to make new
investments, the average effective tax rate is a useful metric for comparing the profitability of
identical projects undertaken in different jurisdictions.
5 Devereux and Griffith (2003) also provide an alternative definition of the AETR, where the difference between the NPV of a hypothetical project in the presence and absence of tax is scaled by the NPV of the value of the project in the absence of tax.
14
2.1.2 Statutory tax rates and profit shifting
When an MNE decides whether or not to shift profit from one subsidiary to another, the
statutory tax rate is of special interest. As the profit is shifted into or out of the affiliate, and
not made through an investment, the existence and extent of profit shifting depends primarily
on differences in the statutory tax rates of the locations where the MNE has affiliates. As the
MNE makes decisions with the entire structure of the company group in mind, it has been
suggested that the profit shifting depends on an average or a weighted average of the
difference between the statutory tax rates of one affiliate and all the other (Huizinga &
Laeven, 2008, p. 1165).
2.2 Previous work on the subject
A seminal paper on how to estimate profit shifting empirically is “Fiscal paradise: Foreign
Tax Havens and American Business” by James R. Hines, Jr and Eric M. Rice, published in
The Quarterly Journal of Economics (1994). Several other authors have later investigated
multinational enterprises’ profit shifting behavior by employing the estimation strategies that
are presented in this paper, with small or large modifications. This approach considers a US
MNE that has several affiliates, some of which are located in tax havens. Hines and Rice
address a concern that the US, at the time of writing, could have its domestic tax base eroded
by MNEs that were able to report their profits in the most tax-preferred locations, and the
related concern that they might shift productive factors to low-tax countries. Hines and Rice
consider primarily US affiliates located in tax havens, a group of 41 countries which for their
purpose was selected by criteria such as low corporate tax rates and freedom from capital
controls. These countries were further divided into two groups, the Big-7 tax havens and the
Dots, where the Big 7 tax havens accounted for 80 % of tax haven population and 89% of tax
haven GDP. Most of the physical activity undertaken by US haven affiliates took place in the
Big 7 tax havens. The US tax system provided tax credits to US MNEs for taxes paid to
foreign governments. If the tax rate was 34% in the US, and the MNE paid 15% tax to the
foreign government on income earned abroad, the MNE would receive tax credits for the 15%
previously paid when the income from the foreign affiliate was repatriated to the US, and then
be liable to pay only 19% tax on this repatriated income. If the tax rate abroad was higher
than the US tax rate, no tax rebate would be given, but the MNE would not be liable to pay
tax on this income to the US government. Special rules applied to delaying profit repatriation,
15
such that a controlled foreign corporation’s (CFC’s) passive income was treated as if it were
distributed to its American owners and subject to immediate taxation. If earnings were
reinvested in active foreign business the CFC would avoid this rule and could continue to
defer US tax liability on those earnings (Hines & Rice, 1994) Whether deferral or repatriation
of profit was chosen by the MNE, the tax rules provided incentives to locate affiliates in tax
havens.
The paper seeks to test whether US firms allocated profits and physical operations in tax
havens and other low-tax countries to a greater extent than normal business conditions would
indicate. They consider two reasons why firms would want to take advantage of the low tax
rates in tax havens: The first is that the firms have incentives to transfer profits from high-tax
locations where their physical activity actually takes place to low-tax locations where the
economic opportunities are more limited. The other reason is that some projects that are not
profitable at a high tax rate may become profitable at low or zero tax rate. These reasons are
treated separately in the analysis. The model which is estimated is presented in chapter 2.3.1,
so for now I will limit the exposition to an overview: Hines & Rice use country-level
aggregate data on US nonbank majority-owned affiliates in 1982, treating all affiliates as if
they were owned by one representative US parent firm. The MNE has the option to shift
profits between affiliates, but profit shifting is costly. The costs associated with profit shifting
is related to setting up additional facilities to make transfer prices seem plausible, legal costs,
and inefficient use of intrafirm trade to facilitate profit shifting. The concealment cost
function is convex and increasing in the ratio of shifted profit to earned profit. The optimal
level of shifted profit is a function of the true profit and the estimated tax rate in the affiliate
location6. Hines & Rice use ordinary least squares (OLS) and instrumental variables (IV)
estimation. The explanatory variables Tax and Tax2 are instrumented with Log (Population)
and [Log (Population)]2 in the IV estimation. Hines & Rice estimate the effect of changes in
the statutory local tax rate on reported pretax non-financial income. They find that a one
percentage point increase in the tax rate is associated with a reduction in reported pretax non-
financial income of around 3%. The estimates vary from -2.83 to -2.25 in the OLS estimation,
excluding the regression that includes a quadratic tax-variable, and from -3.65 to -2.97 in the
IV estimation, also excluding the specification that includes the quadratic tax-variable. The
6 Hines & Rice calculate average tax rates for each affiliate location as a simplification, as they claim that “no simple measure of the corporate income tax rate can accurately capture the precise differences in tax burdens corporations face in different countries.” (Hines & Rice, 1994, p. 30 ) Average tax rates are given by corporate income taxes paid by all U.S. affiliates in a country, divided by their total pretax net income.
16
instrumental variable (IV) approach is chosen as a supplement to OLS, because the authors
are concerned that there may be unobservable characteristics in some countries that both
affect the tax rates and the reported income of the affiliates located there. If for instance the
country in question has a large amount of tax-insensitive US investments, it may choose a
high rate and this will result in a downward biased estimate of the effect of the tax. The
instrument chosen for the tax rate is the log of the host country population. The rationale
behind this choice is that small countries have little locally provided capital, and therefore
face elastic supply of capital on the world market. The optimal tax rates are expected to be
low in such countries and positively related to the size of their population (Hines & Rice,
1994). The results from the first estimation do not describe the full impact of low tax rates on
reported non-financial profits, since they control for use of inputs. Hines and Rice proceed to
estimate factor demands, which reflect firms’ incentives to allocate productive factors based
on the weight of the tax burden in the various locations. This is what I will refer to as
traditional tax effects below. The estimates show that the tax rate has a significant impact on
the employment of productive factors. A 1 percentage point reduction in the tax rate is
associated with a 3 % increase in the use of labour and capital by US investors. Together
these results imply that a 1 percentage point change in the local tax rate is associated with a 6
% change in reported profits, but taking into account the results from the specifications that
include the quadratic tax-variable, the effect of the tax rate change is strongest when the tax
rate is initially low. The authors are also able to estimate a revenue-maximising tax rate for
the tax havens based on the regression coefficients from their previous estimations. This
yields an optimal tax rate of 5.7%, and the authors claim that as the parameter estimates
indicate the effect of a tax change in one small tax haven, a coordinated effort between the tax
havens could increase the revenue maximising tax rate.
Harry Huizinga and Luc Laeven’s article “International profit shifting within multinationals:
A multi-country perspective” (2008) considers profit shifting incentives that arise from
differences between affiliates’ and parents’ statutory tax rates, and also the tax differences
between affiliates in different host countries. They claim that an MNE’s profit shifting
depends on a weighted average of international tax differences between all countries where
the MNE is active (Huizinga & Laeven, 2008). They use firm-level data on European MNE’s
parents and affiliates, and information about the various tax systems that apply to these. They
find a semi-elasticity of reported profits with respect to the top statutory tax rate of 1.3, and
estimate shifting costs to be 0.6% of the tax base. They claim that international profit shifting
17
leads to substantial redistribution of national corporate tax revenues and that many European
countries seem to gain from profit shifting largely at the expense of Germany.
Their model contains mainly the same elements as Hines and Rice’s, but they introduce a
composite tax variable Ci that summarizes all information about each affiliate’s profit shifting
incentives and opportunities, as it contains measures of the differences in statutory tax rates
between each pair of affiliates and a measure of the scale of operations in each affiliate. The
coefficient on the composite tax variable is interpreted as the semi-elasticity of reported
profits with respect to the composite tax variable. After calculating each affiliates’ tax
composite variable, Huizinga and Laeven run six different OLS regressions using the
logarithm of earnings before interest and taxes (EBIT) as the dependent variable, all with
slightly different choices of independent variables. In one specification they split their
composite tax variable in two: One variable contains tax differences vis-à-vis other
subsidiaries and one contains the tax differences vis-à-vis the parent company. The parent tax-
difference variable is significant at a 99 % confidence level, the other is not significant. In
later specifications the sample is restricted to subsidiaries of MNEs for which they have data
on at least 50% of the subsidiaries, and when splitting the composite tax variable in the
second of these specifications both coefficients come out significant at a 99% confidence
level, in fact the coefficient on the tax difference vis-à-vis other subsidiaries is very large and
negative. Huizinga and Laeven takes this to support their multi-country approach, and claims
that the previous literature focusing only on profit shifting between affiliates and their parent
has missed a key part of actual profit shifting (Huizinga & Laeven, 2008). The authors end
their article with aggregate country-by-country estimates of true profits, profits shifted,
shifting costs, and tax revenue losses/gains. They conclude that many European countries in
the period considered have gained from European multinationals’ profit shifting, mainly at the
expense of Germany, who has lost significant amounts of tax revenue according to these
estimates. This is in part explained by the size of the German economy involving MNEs and
the high German tax rate, which was 53.76% in 1999.
A different method of estimating profit shifting within multinational companies is used by
Dhammika Dharmapala and Nadine Riedel in their 2013 article “Earnings shocks and tax-
motivated income-shifting: Evidence from European multinationals”, where they consider a
multinational company that has a parent and two subsidiaries, one located in a high-tax
country and the other in a low-tax country. They look at the effects of an earnings shock
18
experienced by the parent company and analyze how this shock propagates across the
subsidiaries of the parent company, assuming that the parent is located in a higher-taxed
jurisdiction than the low-tax subsidiary (Dharmapala & Riedel, 2013).
The authors use a sample of 18000 observations of approximately 4800 multinational
affiliates over the period 1995-2005, and restrict the sample to affiliates that operate in a
different industry and location from their parent, to avoid that the earnings shock that affects
the parent also impacts the affiliates considered. The costs of shifting profits arise mainly due
to the same reasons as in Hines and Rice (1994). The cost function is in two arguments, the
fraction of shifted income to total income and the amount of shifted income, and is increasing
and convex in both arguments.
Comparative statics show that both the optimal fraction of shifted profit to total profit (in
high-tax parent country) and total shifted profit increase in the tax difference between the
high- and the low tax country (Dharmapala & Riedel, 2013, p. 97). There are alternative
explanations for why an income shock at the parent level will propagate through the group:
Risk sharing within the group and operation of intra-firm capital markets are among these.
The alternative explanations apply to both higher and lower taxed affiliates. Dharmapala and
Riedel (2013, p. 96) argue that there will be no profit shifting when the affiliate is located in a
similar- or higher-taxed country as the parent. This provides an identification strategy, as the
affiliates located in the higher-taxed countries will function as a control group that captures
other potential linkages between the pre-tax profits of affiliates in the same multinational
group.
Dharmapala and Riedel (2013) employ a fixed effects estimation strategy, estimating the
effect on pre-tax profits in a subsidiary from an unexpected income shock at the parent level,
with a special focus on the interaction term between parent company profits and a dummy
variable indicating that the subsidiary is located in a lower taxed country than the parent, as
this is expected to capture the tax motivated profit shifting. The coefficient on the interaction
term is significantly different from zero throughout all specifications, albeit at slightly varying
confidence levels.
“(The estimates) suggest that an increase in the pre-tax and pre-shifting profits at the parent
level by 10% enhances the profit earned at the affiliate by 0.4%”(Dharmapala & Riedel, 2013,
p. 101). Although this seems like a small effect, the total effect, when taking account of the
19
average number of affiliates located in countries with lower tax rates than the parent, is that
2% of the extra income is shifted out of the parent company to lower taxed affiliates.
Through estimating the impact of the fraction of a parent’s subsidiaries that are located in
lower taxed countries, on the debt-to-asset ratio of the parent, the authors conclude that the
main channel for profit shifting is through the use of inter-affiliate debt. The authors caution
that this is most likely a result of the construction of the study, as the included affiliates are
restricted to those who do not belong to the same industry as the parent. They claim that the
opportunity of profit shifting through transfer mispricing, which has been the main focus of
other previous studies, e.g. Huizinga & Laeven (2008) and Hines & Rice (1994), therefore is
limited (Dharmapala & Riedel, 2013, p. 103).
The authors discuss the impact on the analysis of excluding loss-making subsidiary-year
observations, which is common in the literature. If the tax rules allow for immediate
refunding of the tax value of the loss or for losses to be carried forward, with added interest,
and two affiliates are lossmaking, one located in a high tax country and one located in a low
or zero taxed country, it can be more profitable for a parent company to shift income to the
low tax affiliate than to a high tax affiliate, as the tax value of the forward carried loss is
greater in the high taxed country. In case there is no refunding of the tax value of the loss or
loss offset against future profits, the parent company will be indifferent between shifting
profit to the high taxed or to the low taxed affiliate (Dharmapala & Riedel, 2013, p. 103).
Dharmapala and Riedel also run a test on the hypothesis that MNEs have an incentive to shift
profit to the subsidiary that faces the lowest corporate tax rate in the group. They do this by
creating a dummy variable indicating that the subsidiary is the lowest taxed within the group,
and interact this dummy variable with the parent’s earning shock (Dharmapala & Riedel,
2013, p. 105). The coefficient on this interaction term is positive and statistically significant,
which lends support to my view that the most important profit shifting incentive is created by
the maximum tax difference between affiliates. They also find that the impact of a parent
company earnings shock on the income of low tax affiliates is greater in the MNEs who have
at least one subsidiary in a non-European tax haven. As the accounts for the non-European
affiliates are not available for the authors, this is interpreted as suggesting that MNEs with
more profit shifting opportunities are more likely to establish subsidiaries in non-European
tax havens (Dharmapala & Riedel, 2013, p. 106).
20
Dhammika Dharmapala has also done a survey of the existing empirical literature that
attempts to estimate the magnitude of base erosion and profit shifting (2014). Its emphasis is
on discussing empirical methods, on describing what is known about the magnitude of BEPS,
and interpreting the implications of these findings. Dharmapala points out that “a shift from
aggregate country-level data sets to firm-level microdata has greatly enhanced the credibility
of more recent estimates of BEPS. In the recent literature, the estimated magnitude of BEPS
is typically much smaller than that found in earlier studies” (2014, p. 423) Early estimates of
the semi-elasticity of reported income with respect to the tax rate difference are about three
times higher than currently accepted estimates.
The paper presents the most commonly used approach to empirical estimation of BEPS in the
economic literature, derived from early research on the subject, notably Hines and Rice
(1994) and Grubert and Mutti (1991) with the basic premise that observed profit is the sum of
actual profit and shifted profit.
Another tradition in the accounting literature uses data from Compustat to test whether US-
based MNEs shift income from the US to their foreign affiliates, considered as a whole, by
regressing the ratio of foreign pre-tax income to foreign sales on measures of the foreign tax
rate. The foreign tax rate is weighted by the distribution of the firm’s activities across
jurisdictions. The regression controls for the ratio of worldwide income to worldwide sales.
The premise of this approach is that accounting rates of return would be equalized across
affiliates of the MNE in the absence of profit shifting. The differences in accounting rates of
return that are related to the foreign tax rates are interpreted as being attributable to profit
shifting (Dharmapala, 2014, p. 427). Dyreng and Markle (2016) develop this approach: They
estimate profit shifting based on the premise that the allocation of a US MNE’s sales between
US customers and foreign customers is relatively non-manipulable given the fixed location of
final customers. They argue that it is possible to directly estimate the direction and extent of
profit shifting by analyzing the difference between the location of US MNEs’ sales and the
location of their reported earnings.
There has also been done much research using the German MiDi data set. Buettner, Overesch,
Schreiber, and Wamser (2012) use a panel of German affiliates of MNEs to analyse the
effects of tax rates and rules on debt-equity allocation among multinational affiliates. They
find a modest effect of tax on the use of inter-affiliate debt, and find that the introduction of
21
thin capitalization-rules has a relatively large impact. When thin-capitalization rules are
introduced, the tax sensitivity of the internal debt ratio falls by about a half (Dharmapala,
2014, p. 433).
Heckemeyer & Overesch (2013) perform a meta-regression of the semi-elasticities that result
from 25 empirical studies, on various characteristics of the data sets that have been used,
whether it is cross-sectional or longitudinal, and on the empirical approach used, and identify
a consensus estimate of the semi-elasticity of reported earnings with respect to the tax
difference between the parent and its affiliate of -0.8, when controlling for various sources of
bias (Heckemeyer & Overesch, 2013).
Sebastian Beer and Jan Loeprick’s article in International Tax and Public Finance (2015a)
considers the effect on profit shifting behavior of countermeasures, like documentation
requirements and enforcement of the arm’s length principle for transfer pricing, and also the
effect of intangible asset holdings and the complexity of the MNE structure on profit shifting.
The authors use a sample from the Orbis database, which includes members of MNEs, both
subsidiaries and parents. They focus on the subgroup of these that are not parents, and remove
observations that lack basic accounting data, have registered negative profits, affiliates with
less than or equal to 90% ownership by one parent, and non-OECD affiliates. They are left
with 74812 observations of 15009 affiliates. As in many of the before-mentioned studies,
Beer & Loeprick (2015a) use the tax difference between an affiliate and the other members of
the group as a key variable for determining the incentive for profit shifting. An affiliate that
has a positive tax difference vis-à-vis the rest of the group has an incentive to shift profits out
of the affiliate, while an affiliate with a negative tax difference vis-à-vis the rest of the group
has the opposite incentive. The baseline regression indicates that the semi-elasticity of
reported profit with respect to the tax difference is around -1 (Beer & Loeprick, 2015a, p.
434). When more variables are introduced, it shows that the semi-elasticity depends on the
complexity of intra-firm supply chains and the ratio of intangible assets to total assets within
the affiliate.
Beer & Loeprick (2015a, p. 435) find that high intangible asset holding is associated with a
higher semi-elasticity of reported profit with respect to the tax difference variable, which may
be explained by the increased scope for mispricing of transfers, as intangible asset prices are
inherently difficult to evaluate in an arm’s length perspective. The complexity of intra-group
22
supply chains are also found to be associated with a higher corresponding semi-elasticity, but
to a smaller extent.
As Beer and Loeprick (2015a, p. 435) also want to test whether official countermeasures has
an effect on profit shifting, they use the introduction of documentation requirements as a
proxy for domestic enforcement of transfer pricing provision on the national level. They find
that the introduction of documentation requirements has a dampening effect on profit shifting
(measured by the semi-elasticity of reported profits with respect to the tax difference), and
that this dampening effect is larger for companies that have a high degree of complexity in
their intra-group supply chain. The documentation requirement has a smaller impact for
companies that hold a larger fraction of intangible assets. This highlights the problems of
enforcing the arm’s length principle on intra-group transfers of services from intangible
assets, such as patents and brand names. It also suggests that domestic enforcement of
documentation rules faces less problems with regard to complex supply chains that with
regard to the difficulty of pricing intangible assets.
Sebastian Beer and Jan Loeprick (2015b) have also recently written a working paper on the
existence of profit shifting within the petroleum industry. In addition to considering the
international channel for profit shifting, i.e., profit shifting between affiliates located in
different countries, they examine the domestic channel for profit shifting that is created when
the statutory tax rate that applies to petroleum companies differs from that which applies to
companies in other sectors.
When an MNE, or any other company, has two or more affiliates in one country, where one of
the affiliates is a petroleum company and the other is not, the company can use this additional
channel to shift profit out of the petroleum affiliate into the non-petroleum affiliate. Beer &
Loeprick (2015b) also in this setting consider the effect of documentation requirements on the
amount of shifted profit and the possibility that regulations such as documentation
requirements apply stronger (or exclusively) to trade among affiliates located in different
countries.
Their findings are in line with previous estimates of profit shifting, namely an estimated
lower-bound semi-elasticity of reported profit with respect to sector-specific income taxation
of -1.88, and that the domestic channel for profit shifting accounts for about one third of total
income concealed/shifted. They estimate that revenue losses in the sector due to profit shifting
amount to 12-35% of the tax base. They also find that documentation requirements have a
23
mitigating effect on international transactions and that increased enforcement of rules
regarding international transfers prompts petroleum MNEs to rely more heavily on domestic
reallocation of profits (Beer & Loeprick, 2015b, p. 21).
They extend the model by Huizinga and Laeven by including the possibility of heterogeneous
transaction costs across affiliates in different jurisdictions. The reasoning behind this
extension is that enforcement capabilities are heterogeneous across countries, and that
domestic shifting is less of a concern for tax administrations and can therefore be associated
with lower costs to a firm (Beer & Loeprick, 2015b, p. 8).
2.3 Theory on profit shifting
2.3.1 The Hines & Rice approach
The firm used as an example in Hines’ and Rice’s paper “Fiscal paradise: Foreign Tax
Havens and American Business” (1994) is a multinational enterprise with affiliates in N
countries. In country/location i, the firm earns profits ρi by the employment of capital and
labour there. The reported profit in this location differs from ρi because the firm shifts income
into or out of the location, depending on the local statutory tax rates, and how it differs from
tax rates in other locations in which the firm has affiliates. In my application of this model,
the petroleum companies in Norway and the UK in general face a higher tax rate than the
parent company. The hypothesis is therefore that profit is shifted from the petroleum company
to the parent company7. The shifting of income ψi has a cost that depends on the amount of
shifted income relative to ρi. The reported profit of affiliate i is:
2
2
( 1 )
This is constrained by∑ 0, since the activity of shifting income does not generate
extra pre-tax profits. The last part of the expression represents the cost of shifting profit. If
profit is shifted out of the affiliate, the ψi term is positive, if profit is shifted into the affiliate,
the term is negative. It is a quadratic function of the amount of shifted profit, and the
7 Apart from one company-year observation all tax differences are positive, implying that the tax rate applicable to the petroleum company is higher than the one applicable to the parent company.
24
convexity of the concealment cost function speaks in favor of splitting the profit shifting
equally between affiliates that face the same tax rate. The MNE chooses its profit shifting to
maximise after-foreign-tax profits, while taking as fixed the true profits earned by its
employed factors8:
max 1 1
2
2
11
( 1 )
subject to
0
1
( 2 )
yielding the first-order condition
1 1 ⁄ , ∀ 1,… , ( 3 )
where λ is the Lagrange multiplier corresponding to the constraint that the sum of all shifted
income is less than or equal to zero.
The first-order condition implies that
11
( 4 )
Combining the last equation with the expression for reported profits gives:
1
12
2
2 1 2
( 5 )
This implies that reported profit is a function of before-tax earnings and the local tax rate. The
before-tax earnings are not directly observable, but by the use of a logarithmic transformation,
a Taylor expansion of the logged expression and an assumption about a Cobb-Douglas
production function of the firm, Hines and Rice (1994) arrive at an expression which is the
departure for my own empirical test.
The logarithmic transformation results in an expression,
log log log 1
12
2
2 1 2
( 6 )
8 In this formulation, the concealment cost is tax deductible, as opposed to the formulation in Lund (2002).
25
which Hines and Rice further transform by the use of a Taylor expansion in τi around the
value of τi which would make the last term of the expression equal to zero, τi = 1 – λ (Hines &
Rice, 1994).This yields:
log log
1
( 7 )
The estimation requires making some assumptions about the firm’s production function.
Hines and Rice (1994) assume that the firm operates with a production function of the Cobb-
Douglas type:
( 8 )
Here, c is a constant term, A is the level of productivity, L is labour input, K is capital input,
and u is a normally distributed stochastic error term with mean zero. Hines and Rice further
assume that the firm employs labour to maximise profits, which implies that
1
( 9 )
When this is combined with equation (9) and logarithmically transformed, the resulting
expression is an estimable linear equation that can be taken to the test in statistical software:
log log log log ,
( 10 )
where β1 = log c + log (1- α) + (1- λ)/aλ, β2 = α, β3 = ϕ, β4 = ϵ and β5 = -1/aλ.
The β5 coefficient is interpreted as the semi-elasticity of reported profit with respect to the tax
variable.
26
3 Empirical strategy
3.1 Model
3.1.1 Using the Hines & Rice approach
I follow Hines & Rice in assuming that reported profit is the sum of the company’s true profit
and profit that is shifted into or out of the company. The true profit is a function of the
company’s employed labour and capital, and I assume that this function is of a Cobb-Douglas
type:
True operating profits , , 1 .
( 12)
L is a measure of the company’s labour employment, a variable for which labour expenditure
or number of employees can be a proxy. K is a measure of the company’s employed capital, a
variable that can be proxied by for instance fixed assets or fixed tangible assets. The Cobb-
Douglas production function using only two input factors may be a good approximation of the
transformation of capital and labour into goods and services in the economy as a whole. In the
petroleum sector, the most important input factor for determining production volume is the
resource in place. The Cobb-Douglas production function could be modified to take account
of this input factor as well, but it would require knowing the amount of oil or gas on each
field. With the absence of this information, there is a large amount of variation in the data
which cannot be explained by the use of capital and labour alone. It could also be the case that
the production function is not a Cobb-Douglas function.
A is a productivity measure. In the original literature, Hines and Rice (1994) claim that GDP
per capita can be a good proxy for productivity. Beer & Loeprick (2015b) also use GPD per
capita as a productivity measure in their analysis, but for the petroleum sector in Norway and
the UK, GDP per capita may not be such a good productivity measure. The data I use in my
analysis are firm’s financial accounts available through the Amadeus database. These are
upwards limited to ten years of annual accounts, most of these spanning the period 2005 –
2014. The productivity growth in the general economy, measured as annual change in gross
27
value added per hour worked, keeping prices constant, has been low in Norway and the UK in
these years, with an average UK productivity growth in the period 2005 – 2014 of 1.19%
(OECD.Stat, 2016a). The corresponding productivity growth in Norway was 0.78%
(OECD.Stat, 2016a). The average productivity growth in the mining and utilities sector, using
the same definition of productivity growth, has been negative over the period 2005 –
2014: -6.58% in the UK and -6.3% in Norway (OECD.Stat, 2016b). Productivity in the
petroleum sector depends on both the maturity of the fields, the availability of reserves and
the location of new discoveries, in addition to the factors that determine the productivity in
other industries, such as technological development and improved efficiency.
Solow and Wan show in their article “Extraction Costs in the Theory of Exhaustible
Resources” (1976), that it is not optimal to use any higher-cost resources until the lowest-cost
resource is exhausted. The cost of extracting oil and gas is not homogeneous across fields,
and to minimize the NPV of the costs firms should extract the resources with the lowest costs
first. This principle can show up as negative productivity growth in the petroleum sector, if
the fields with low extraction costs become exhausted and fields with higher cost per unit of
resource start producing some time during the period 2005 – 2014, as this would result in
gradually increasing unit costs of production throughout the period.
Because of the difference in productivity between the economy as a whole and the mining and
utilities sector, using GDP per capita as a productivity measure can be misleading. As a
substitute for the productivity measure suggested by Hines and Rice (1994), and used by Beer
and Loeprick (2015b), I use OECD’s productivity index for the mining and utilities sector.
This is based on changes in the gross value added per hour worked, keeping prices constant.
As gross value added per hour worked generally depends on the amount of capital employed
and also, in this sector, on the resource base, this may also be an imperfect measure of
productivity in the sector, but it still seems better than using GDP per capita. I also use a
measure of yearly change in production per hour worked, which is compiled and published by
Statistics Norway (2016). This measure differs somewhat from the statistics published by the
OECD (2016b) although the average productivity growth is very similar (-6.88%
versus -6.3%). This could be a better productivity index, but I have not been able to find the
corresponding statistics for the UK.
28
3.1.2 Modifying the model to capture the traditional tax distortions
All the previous research using the Hines & Rice approach has included tax variables as
differences. This is logical to test the transfer incentives. As an extension I find it interesting
to include each tax rate as an explanatory variable, not only their difference. If only the
difference matters, coefficients would have the same absolute value, but opposite signs. To
test my hypothesis that traditional tax distortions are present, I propose two different model
specifications as estimation strategies: In one of the specifications I include one variable for
the local statutory tax rate that applies to the petroleum affiliate9, and one variable for the CIT
rate that applies to the petroleum affiliate’s parent company. In the other specification I
include a variable that captures the difference between these two tax rates, a simplified
version of the tax difference variable that is used both by Huizinga & Laeven (2008), and
Beer & Loeprick (2015b).
The reasons why I choose a simplified version, only taking account of the difference between
the affiliate in question and its parent, and not the average difference between the affiliate in
question and all its group members, are twofold. The first reason is that I believe the tax
difference with the lowest taxed affiliate(s) is the one primarily incentivizing profit shifting. It
is likely that an MNE will take full advantage of the possibility of shifting profits to the
lowest taxed affiliate(s) first, then the next-to-lowest, et cetera. Due to the convexity of the
concealment cost function, it is possible that an MNE will choose to shift equal amounts of
profit to the lowest taxed affiliates, when the MNE has two or more affiliate in equally low
taxed jurisdictions.
For companies that have affiliates in zero-taxed jurisdictions, the tax difference will equal the
local statutory tax rate. This means I can also interpret the coefficient on the local statutory
tax rate as the semi-elasticity of reported pre-tax profit with respect to the tax difference
toward the lowest taxed affiliate. The other reason for simplifying the tax difference variable
is more practically motivated: The data available to me are restricted to companies located in
Europe, and for some MNEs the information about the possible existence of affiliates located
outside of Europe was not available. To the extent that the lack of availability of this
9 This is either, for British affiliates, a combination of the Ring-Fenced Corporation Tax, the Supplementary Charge, and possibly the Petroleum Revenue Tax or, for Norwegian affiliates, a combination of the Corporate Income Tax and the Special Surcharge.
29
information is correlated with profit shifting behavior, including this information only
partially would be a source of bias. The tax difference between the affiliate and the parent can
capture profit shifting to the parent. If the parent company tax rate is increased, this will
reduce the profitability of shifting profits to the parent company, and can thus result in a
higher reported pre-tax profit with the affiliate.
In theory, these two tax variables can affect the reported profits in either the same way or in
opposite ways:
A large tax difference towards the parent company, that can be the result of a high petroleum
tax rate or a low corporate tax rate in the parent country or both, will give a larger incentive to
shift profits out of the affiliate. An increase in this variable should then result in a reduction in
the reported profit.
A higher local statutory tax rate will make new investments less profitable, which will lead to
reduced investments. Some fields that were profitable to develop under the previous tax
regime may no longer be so under a new regime with a higher tax. Developments can also be
scaled back, in the case where they are still undertaken. To the extent that changes in the
affiliate’s investments are reflected in the book value of their fixed assets and the cost of
employees, a change in tax rates that affect reported pre-tax profit through changes in
investments should not produce significant coefficients when controlling for factor inputs. If
it does, it could indicate that fixed assets and costs of employees are measured with error. If
the amount of capital and labour actually employed is very inaccurately measured, to the
extent that the measured variables contain almost no information about the amounts actually
employed, the effect on reported profits that comes from changes in employed inputs, will be
accounted for by changes in the tax variables and not through changes in inputs.
There is also a possibility that the firms adjust their employed amount of capital and labour
with a delay, so that the book value of the capital and labour corresponds poorly with the
amount which is actually employed in the production. It can be very costly to readjust the
amount of labour that is on the payroll, especially if employees are highly specialized. This
can lead to so-called labour hoarding. This is also true with respect to capital: If there is a
change in the tax rates, or some other factor that affects the profitability of the production
(e.g. oil price), it can be in the firm’s interest to leave some capital equipment unused, without
this necessarily being reflected in the book value of the capital. Another reason why there
30
may be errors in measurement is that the observed values are the cost of employment over
time, i.e., wt*Lt, which will only reflect the changes in labour inputs accurately if the wages
are constant.
An expectation that the tax rate will stay high in years to come, can reduce the firm’s
exploration activities, as they expect a lower profitability from new discoveries. Whether a
change in exploration and development activity will reduce or increase the reported profit
depends on when exploration costs are deducted. One can imagine that all costs of exploration
are deducted from earnings the same year that they are incurred. If that is the case, a higher
local statutory tax rate can lead to increased reported profits, as less exploration and
development costs are deducted from earnings.
Huizinga and Laeven’s (2008) strategy (followed by Beer and Loeprick (2015b)) of creating a
tax difference variable that incorporates the information about the tax difference to all other
affiliates in the group, rests on the assumption that some weighted average of this difference
will determine each affiliate’s level of profit shifting. In my opinion, this argument has a
weakness: For a group that has many affiliates in high-tax countries and one in a low (or zero)
tax country, the weighted average tax difference may be quite small. However, the high-tax
affiliates still have an opportunity to shift profits into a low (or zero) tax country and this will
provide a clear incentive to do so, given that the costs of shifting profits to a low (or zero) tax
country are not much higher than the costs of shifting profits elsewhere.
In addition I include the statutory CIT rate that applies to the parent company separately. This
tax variable is interesting, not only because it affects the profitability of shifting profits from
affiliate to parent company. Because the companies in my dataset are all located in the UK
and in Norway, there is not much variation in the tax rates that apply to these companies that
can serve to identify the causal effect of tax changes on reported profit. The only change is the
increase in the Supplementary Charge in 2012. The parent companies on the other hand, are
located in several different countries, with correspondingly different CIT rates and more
changes over the period (see table 5 in the appendix).
This leaves two hypotheses to be tested in Stata10: The first hypothesis is that when
performing a regression on the logarithm of EBITDA on the tax difference variable, the
10 Stata is a statistical software package. I have used version StataSE 14.
31
coefficient on the tax difference will be negative. A larger tax difference is expected to
provide a greater incentive to shift profits to the parent company.
The other hypothesis is that when the tax rate variables appear in the regressions separately,
the coefficient on the affiliate’s tax rate will be negative and the coefficient on the parent’s tax
rate will be positive. The tax that applies to the petroleum affiliate is expected to have a
negative impact on reported profits through two channels: Traditional tax distortions and
profit shifting. The tax rate that applies to the parent company has a positive impact on
reported profits, as a higher parent CIT rate represents a reduced incentive for shifting profit
to the parent company.
3.2 Data
3.2.1 The Amadeus data
The AMADEUS (Analyse Major Databases from European Sources) database is published by
Bureau Van Dijk and is provided to students at the University of Oslo by the University of
Oslo Library. It contains up to ten years’ archives of standardized annual accounts from over
19 million companies located in Europe. I use a search strategy that selects companies into
my dataset by the following criteria:
‐ Industry classification (NACE Rev.2): B6: Extraction of crude petroleum and natural
gas
‐ Location: Norway and the United Kingdom
‐ Number of subsidiaries: 0
‐ Companies owned by a Global Ultimate Owner (Definition of the Ultimate Owner:
Minimum path of 50.01%, known or unknown shareholder)
‐ Number of years with accounts: 3-10
Unfortunately, it is not possible to automatize a search including the requirement that the
firms selected are part of a multinational group. This has to be determined manually after the
search, following the listed criteria, is complete.
The reason why I choose to exclude companies that have subsidiaries is that I want to make
sure the companies in my dataset do not receive revenues from activities that they themselves
32
did not directly engage in, by use of factors of production. This would contradict an important
premise of the model, that the “real profits” are a function of the company’s employment of
capital and labour.
As the maximum number of accounts available is ten years, the period for which I have the
most accounts is spanning from 2005 to 2014. I restrict my attention to this period, and
therefore exclude all accounts from years prior to 2005 and after 2014, where these are
available. I follow Beer and Loeprick (2015b) in selecting only the companies that have a
minimum of three years of accounts. This is done to improve the analysis, as the one or two
year accounts will not provide enough information about the trends of the companies. The
identification of the effects of changes in tax rates on reported profit is mainly based on
variation in the various tax rates over time.
After I have compiled the data on the companies that meet the above-mentioned criteria, I
compare this list to the lists of licensees from British and Norwegian official records,
collected from the Norwegian Oil Directorate’s fact pages (Oljedirektoratet, 2016) and the
corresponding pages from the UK Oil and Gas Authority (UK Department of Energy &
Climate Change, 2016). Due to a lot of company acquisitions and name changes, this process
requires a bit of investigatory effort, just to determine which companies have actually been
active as operators or equity holders on fields in the UK and Norwegian petroleum sectors in
the period I consider. Excluding companies that have not been active as either operators or
equity holders decreases the dataset from approximately 1000 companies to about 120.
Descriptive statistics, on full sample and separated by country, is located in the Appendix.
3.2.2 Estimating the actual fraction of PRT-liable income
Beer and Loeprick (2015b, p. 29) do a crude approximation of the statutory tax rate that the
various British petroleum companies face. Their total statutory tax rate applicable to British
petroleum companies is an average of the two applicable tax rates (PRT liable and non PRT
liable, see table 9 in the appendix), weighted by the proportion of earnings that derive from
non-PRT-liable and PRT-liable field. If the fraction of total earnings that derive from PRT-
liable fields is equal to λ, and the fraction of earnings that derive from non-PRT-liable fields
is equal to 1-λ, then the tax rate should be equal to
33
∗ 1 1
( 11 )
Beer and Loeprick estimate that tax revenues from PRT-liable fields as a fraction of total tax
revenues from all oil and gas fields on the UKCS is 25%. This fraction is then applied to all
companies in the UK, regardless of their actual share of equity ownership on PRT-liable and
non-PRT-liable fields.
I use field production volume data from 2005 – 2014 (Department of Energy & Climate
Change, 2016b) and field equity ownership data from 2009 – 2014 (Department of Energy &
Climate Change, 2016a) to estimate the tax rates more precisely for each company. The mean
of this resulting tax rate (0.582) differs only to a small extent from the mean tax rate obtained
by applying the generalized 25% rule used in Beer and Loeprick’s estimates (0.585), but the
range of difference is [-0.075 , 0.225] so there is a chance that this will affect the estimates. I
primarily report results using my own estimation of the tax rates, but include a comparison of
the results using this tax rate with the results from using the generalized 25% PRT liability tax
rate (see tables 3 and 4 in the appendix). This comparison shows that the results differ most
when using the tax difference variable: In the OLS estimation, the 25% PRT liability rule
produce more significant results, but in the company fixed effects estimation, my estimated
tax rates produce the most significant results. One weakness with this point of the analysis is
that I have not been able to obtain ownership data from the period 2005 -2008. As is clear
from the data spanning the 2009 – 2014 period, the changes in equity ownership of PRT-
liable versus non-PRT-liable fields for each individual company has not been systematic or
monotonous, so rather than make further assumptions about ownership in this period, I have
applied the 25% rule suggested by Beer and Loeprick (2015b, p. 29), for 2005 – 2008.
3.3 Fixed Effects and OLS estimation
3.3.1 Panel data, explanation and transformation of variables
My data is a panel consisting of 119 different hydrocarbon companies with accounts
observations in the range of 3 -10 years. The total number of observations is 1189, but one or
more variables are missing in a large fraction of these. The panel is unbalanced, as I do not
34
have observations of all companies for all 10 years. Some companies, although having
accounts for a minimum of three years, have less than three years of observations on either
the dependent or one or more of the independent variables. For most parts of the estimation I
drop all observations where either the dependent or one or more of the independent variables
are missing, and also drop all companies who then are left with only one observation. After
dropping these observations from my data set, it is reduced to 265 observations from 28
different companies.
The explanatory variables are the logarithms of fixed assets and cost of employees. Some of
the accounts include the firm’s number of employees, for one or more years. There are more
reports on costs of employees (264 observations) in the accounts that on the number of
employees (148 observations), and although these measures may not be perfect substitutes, I
choose to include only the cost of employees. One reason is that there are more observations
of this variable, but also because the employee compensation variable captures two effects
that are not captured by the number of employees: Differences in labour productivity affect
both production and cost of employees in the same direction. Less efficient workers, with
lower marginal productivity, are expected to have lower wages. Differences in working hours
will also affect the cost of employees and production in the same direction. On the other hand,
an argument in favor of using number of employees is that wage rates may change for other
reasons than productivity.
Beer & Loeprick are faced with the same problem, as 43% of the observations used in their
estimation were missing observations of the number of employees (2015b). The authors
choose to impute the missing observations by estimating the function
, , , where K denotes total assets, and z is at vector of country specific variables.
They use a censored regression model, and obtain the following:
log 2.98 0.59 log 1.18 ln 2.22ln
This model is then used to predict the number of employees for the companies that are
missing this variable. This could potentially introduce a problem for the following estimation
of profit shifting.
Two of the most common methods for dealing with missing observations in quantitative
research are these two: Listwise deletion and some form of imputation. If data are missing
35
completely at random, listwise deletion does not introduce bias, but decreases the power of
the analysis by reducing the sample size. If the observations are missing at random if we take
into account observable factors that determine whether they are missing, for instance if
number of employees are missing at random when controlling for fixed assets and parent
country, then excluding the observations with missing observations does not introduce a bias
in the sample, as long as the determining factors are included as controls in the regression. If
the observations are not missing at random, then the listwise deletion will give biased
estimates, as the subsample of deleted observations are not representative of the original
sample (Gelman & Hill, 2007, p. 530). The imputation methods available vary from very
simple to more complicated, e.g. imputation of the mean, last value carried forward, and using
regression predictions as deterministic imputations. These can also bias the sample and in
effect the resulting estimates (Gelman & Hill, 2007, p. 536). As a result, there is a trade-off
between on one hand keeping the sample size unchanged while possibly introducing a
significant bias in the sample by using imputation, and on the other hand reducing the sample
size while also possibly introducing bias in the sample by deleting perhaps non-random parts
of the sample.
The dependent variable in my estimation is the logarithm of EBITDA (earnings before
interest, taxes, depreciation and amortization). I choose this dependent variable instead of
EBIT (Earnings before interest and taxes), because equation 12 (p.26) is equal to revenue
minus the cost of labour, but not minus the cost of capital. EBITDA is a better measure of the
earnings before deducting the cost of capital, as the values of depreciation and amortization
are not deducted, and this may provide an improvement of the analysis compared to Huizinga
& Laeven (2008) and Beer & Loeprick (2015b) who use EBIT.
I encounter a very common problem when taking the logarithms of EBITDA, fixed assets and
costs of employees, namely that one cannot take the logarithm of zero or a negative number.
The problem is smaller when using the logarithm of EBITDA as opposed to using the
logarithm of EBIT, since the number of negative EBITDA observations is smaller than the
number of negative EBIT observations, as fewer items are deducted.
An often suggested solution to this is to add a constant to each observation. Since there is a bit
of disagreement as to whether this is an appropriate solution (although adding a constant to
each observation does not change the variance, kurtosis and skewness of the distribution, the
results one gets may be sensitive to the choice of constant), I decide not to alter any of the
36
original observations and for the estimation only use those which produce non-missing
logarithmic transformations.
Dharmapala (2014) comments on the choice of excluding loss-making company-year
observations from the sample: “It is possible to include negative observations using a simple
rescaling of the variables. However, incentives for BEPS are typically attenuated for loss-
making firms due to tax asymmetries such as limitations on loss offsets.” This supports the
choice of not including the observations with negative EBITDA, as it could be that the
companies reporting losses can be considered as not belonging to the same population of
companies as those reporting profits, with respect to their profit shifting incentives.
For my analysis I use only observations with non-missing values of log(EBITDA), log(Fixed
assets) and log(Cost of employees), which further reduces my sample to 122 company-year
observations, of which 69 are British.
3.3.2 Fixed effects and unobservables
I follow Beer and Loeprick (2015b) in the choice of estimator, the company fixed effects
estimator, also called “within estimator”. I do this because I believe that there are certain
unobservable characteristics of each company that will affect its reported profits, and this can
in turn help reveal profit shifting. These unobservable characteristics can include willingness
to test the boundaries of the law, political persuasion, owners’/executives’ background etc.
Koester, Shevlin and Wangerin investigate the effect of managerial ability on tax avoidance,
and find that moving from the lower to the upper quartile of managerial ability is associated
with a 3.15% reduction in a firm’s one-year cash effective tax rate, and a reduction of 2.5% in
the same firm’s five-year cash effective tax rate (Koester, Shevlin, & Wangerin, 2016, p. 3).
They explain these findings with higher ability managers devoting more effort to tax planning
activities; they shift more income to foreign tax havens, make more R&D credit claims and
make greater investments in assets that generate accelerated depreciation deductions (Koester
et al., 2016, p. 4). There are of course some observable characteristics that can affect the level
or existence of profit shifting, but to the extent that these are reported, they are included in the
regression as control variables. The unobservables on the other hand, can be controlled for
through a fixed effects estimation strategy.
37
The argument for using company fixed effects is particularly strong for resource extraction.
Beer & Loeprick (2015b), dealing exclusively with the oil and gas industry, include proven
reserves on a country level as a control variable. This is in my opinion only slightly better
than ignoring the reserve aspect completely. As resources in place tend to vary between each
oil and gas field within a country, I have doubts about the appropriateness of including a
country level variable. The companies have not, in general, changed their field ownership
much throughout the period. There have been some license-transfers, but for the most part the
companies have maintained their interest on each field for longer periods. Since I lack
information about the size of fields or reserves in my dataset, and thus cannot control for the
effect of variation in field size on reported profit, the fixed-effects estimator works well for
the purpose of absorbing the effect of field size on reported earning, thus hopefully
highlighting the effect of taxation.
3.3.3 OLS estimation
The OLS estimation is sensitive to omitted variables, both unobservable variables and
observable variables which are not recorded in data. The OLS estimates will provide results
with which it can be interesting to compare the company fixed effects results. One of the
reasons is the shortcomings of the dataset with respect to oil and gas reserves in place. When
using OLS, the impact of the differences in oil and gas reserves in place on each field (which
may be fully observable but not recorded in the data) will be reflected in the coefficients on
the variables that are included in the regression, in case they are correlated with the reserves.
The amount of fixed assets on a field is probably highly correlated with the amount of
reserves in place, possibly also the amount of labour employed. It is therefore likely that
much of the variation in reported earnings will be explained by variation in the amount of
fixed assets and labour employed in the OLS estimates.
38
4 Results and interpretation
4.1 Specifications and control variables
Here I present the results from my estimations and discuss the different choices of model
specifications.
In table 1, I use OLS estimation on the full sample, first regressing the logarithm of EBITDA
on the tax difference variable, while controlling for the logarithms of fixed assets and cost of
employees and the average the second, third and fourth lag of the oil price in specification 1.
I proceed by splitting the tax variable into two separate variables in specification 2, the local
tax variable, and the parent tax variable, while controlling for the logarithms of fixed assets
and cost of employees as well as the average of lag(2), lag(3) and lag(4) of the oil price.
In table 2 I use company fixed effects estimation. I first regress the logarithm of EBITDA on
the tax difference variable in specification 1, before I proceed by splitting the tax variable into
the local tax rate and the parent tax rate in specification 2. I use the same controls in the
company fixed effects estimation as in the OLS estimation.
In the OLS estimation I have experimented with including different control variables that I, a
priori, suspected could influence companies’ profit shifting behaviour. These are variables
that do not vary within each company over the period, but which vary between companies:
Location (either Norway or the UK), a dummy variable indicating membership of one of the
Big 7 oil companies (ExxonMobil, Royal Dutch Shell, BP, Chevron, Total, Eni and
ConocoPhillips), a dummy variable for each group, and different lags of the oil price. After
concluding that these have no significant impact, together or by themselves, on the coefficient
on the explanatory variables of interest, and no significant impact on the reported profit, these
control variables were excluded from the regressions.
Similarly in the company fixed effects estimation, I tentatively included control variables that
varied within each company over time, as well as between companies: These included
percentiles of fixed assets holdings, percentiles of reported earnings, and different lags of the
oil price. When, as in the OLS regressions, these did not show any significant impact on the
coefficients of interest, nor on the reported profits, they were excluded from the regressions.
39
4.1.1 Results from the OLS estimation
Table 1:
Dependent variable: log(EBITDA)
Explanatory variable: (1) (2)
Log(Fixed assets) 0.750*** 0.717***
(0.100) (0.100)
0.000 0.000
Log(Cost of employees) 0.323*** 0.275***
(0.098) (0.092)
0.001 0.003
Oil price, average lag(2) ‐ lag(4) ‐0.030*** ‐0.027***
(0.006) (0.006)
0.000 0.000
Tax difference ‐1.431
(0.997)
0.151
Parent tax rate 3.204**
(1.397)
0.022
Local tax rate ‐0.112
(0.932)
0.904
Constant 1.354* 0.601
(0.791) (1.007)
0.087 0.550
Number of observations 122 122
Adjusted r squared 0.6143 0.6308 Specification 1 includes the tax difference; specification 2 uses the tax variable split in two. Bootstrapped standard errors are in parenthesis. P-values are in italics. Stars indicate significance level: * p<0.1; ** p<0.05; *** p<0.01.
40
The specification is log-linear in the tax variables and the oil price variable, which implies
that a unit change in these independent variables is associated with a 100*β% change in the
dependent variable. The coefficient can thus be interpreted as the semi-elasticity of the
dependent variable with respect to the explanatory variable in question. The specification is
log-log in fixed assets and cost of employees, which implies that the coefficients on these
variables give the elasticities of reported profits with respect to the input factors. A 1%
change in the use of the input in question is associated with a β% change in reported profits.
In the first specification (table 1, column 1), the explanatory variables are the logarithms of
fixed assets and cost of employees, the difference between the local tax rate and the tax rate
that applies to the parent company, and the average of lag(2), lag(3) and lag(4) of the oil
price. The coefficient on the tax difference is -1.431 and is not statistically significant. The
sign of the coefficient is however as expected, since a larger tax difference provides an
incentive to shift profit out of the high tax jurisdiction to the lower taxed jurisdiction. The
coefficients on the log of fixed assets and the log of employee compensation are statistically
significant at a 99 % confidence level. This supports my hypothesis that a difference in the
amount of resource in place has an impact on reported earnings through the amount of fixed
assets and labour employed.
The coefficient on the average of three lags of the oil price is small, negative and statistically
significant at a 99% confidence level. Intuitively, I would expect the oil price to affect
reported EBITDA positively. However, there is a possibility that an increase in the oil price
affects the firm’s incentives to undertake more exploration of new oil fields. If the costs
associated with exploration are immediately deductible from EBITDA, this would help to
explain the negative coefficient on this variable.
In specification 2, (column (2) of Table 1) there is one change in the explanatory variables:
The tax difference variable is split in two: One parent company tax rate variable and one local
tax rate variable. The parent company tax rate variable is positive and statistically significant
at a 95% confidence level. This supports the hypothesis that the companies shift profit to the
parent companies when the parent company tax rate is lower than the local tax rate. When the
parent company tax rate decreases by one percentage point, the associated change in reported
EBITDA is -3.2 %.
41
The coefficient on the local tax rate is not statistically distinguishable from zero. This does
not rule out a real effect on profits through a change in investments. As a real effect would
work through a change in investments and hence through the employment of productive
factors (i.e. capital and labour), the effect of the local tax rate on reported EBITDA is
expected to be small when we condition on the amount of employed capital and labour.
It is clear that the parent company’s tax rate has a larger effect on reported EBITDA than the
local tax rate. This can imply that there exists tax motivated profit shifting in the UK and
Norwegian petroleum sector.
All specifications were also run separately including a productivity measure as a control
variable, but it fails to show any effect on the dependent variable. The productivity measure I
included differs from the one used by Hines and Rice (1994) and by Huizinga and Laeven
(2008), but it is, as mentioned, difficult to justify using GDP per capita as a productivity
measure for the petroleum sector.
When regressing the logarithm of factor inputs separately on the local tax rate applicable to
the petroleum sector (Table 9 in the appendix), I find that the local tax rate does have a
significant effect on capital (proxied by fixed assets), but surprisingly the coefficient is
positive. Hines & Rice (1994) do a similar estimation of the effect of local tax rates on
location of factors of production, and find that the local tax rates have a significant negative
impact on the use of fixed assets and labour. The coefficient from my estimation, 3.78,
implies that when the local tax rate increases by one percentage point, the company’s fixed
assets increases by almost 4%. Tables with these results are placed in the appendix. As there
is no variation in the Norwegian local tax rate, this regression is performed using data on
petroleum companies located in the UK. The results are contrary to the hypothesis that the
local tax rate has a separate negative effect on the reported earnings through reducing
investments. The fraction of the variation in fixed assets explained by the variation in the
local tax rate is small, with a R2 of 0.03, which implies that there are probably other factors
that explain the variation in fixed assets better. The results from the regression of the
logarithm of employee compensation on the local tax rate show that the use of labour as a
function of the local tax rate is convex and has a minimum where the local tax rate is 0.454.
The use of fixed assets as a function of the local tax rate is also convex, but does not attain a
global minimum in any positive values of the local tax rate. There are several possible
explanations for why the function shows that the use of fixed assets is increasing in all
42
positive values of the local tax rate. As the tax rate has been monotonously decreasing
throughout the period, a time trend that coincides with the reduction of the tax rate is hard to
distinguish from the actual effect of the tax rate. If the local tax rate impacts the use of factors
of productions with a delay, for reasons mentioned previously, using lagged tax variables in
the regression could provide more correct estimates.
4.1.2 Results from the company fixed effects estimation
Table 2
Dependent variable: log(EBITDA)
Explanatory variables (1) (2)
Log(Fixed assets) 0.098 ‐0.092
(0.266) (0.272)
0.711 0.737
Log(Cost of employees) 0.232 0.277*
(0.188) (0.159)
0.217 0.081
Oil price, average of lag(2) ‐ lag(4) ‐0.011 ‐0.016*
(0.008) (0.009)
0.193 0.077
Tax difference ‐3.087*
(1.666)
0.064
Parent tax rate ‐12.429**
(5.781)
0.032
Local tax rate ‐5.500**
(2.406)
0.022
Constant 9.478*** 18.019***
(2.652) (4.558)
0.000 0.000
Number of observations 122 122
Within r‐squared 0.1219 0.2134 Specification 1 includes the tax difference; specification 2 uses the tax variable split in two. Bootstrapped standard errors are in parenthesis. P-values are in italics. The stars indicate significance-level: * p<0.1; ** p<0.05; *** p<0.01.
43
In company fixed effects estimation (Table 2), the interpretation of the coefficients is like in
the OLS estimation, as the specification is still log-linear in the coefficients that are of
interest: The tax difference, the local tax rate, and the parent company’s tax rate. In the first
specification the explanatory variables included are: The logarithm of fixed assets and cost of
employees, the local tax rate, the tax difference, and the average of lag(2), lag(3) and lag(4) of
the oil price. Time-fixed effects are not included, since a test on the hypothesis that all year
dummy coefficients were equal to zero was not rejected with a p-value of 0.7125.
In contrast to the OLS-estimation, the coefficients on the logarithms of fixed assets and
employee compensation are small and imprecisely estimated. The size and significance of the
coefficients on capital and labour input reflects the high degree of correlation between field
size and factor inputs. As there is no information about field size in the data, an effect of field
size on reported profit, will likely be captured by the capital and labour variables in the OLS
estimation. It is therefore not surprising that the coefficients on the log of fixed assets and the
log of cost of employees are so significant in Table 1. In the fixed effects model, all
unobservables that do not change over time are controlled for. For the majority of firms, that
only to a small degree change ownership in licences, the size of the fields plays a big role
here. This is the reason why the coefficients on the logarithms of fixed assets are not
significant in any of the fixed effects specifications, and the coefficients on the cost of
employees only to a limited extent.
The coefficient on the tax difference is negative and significantly different from zero at a 90%
confidence level. The coefficient implies that a 1 percentage point increase in the local tax
rate, or conversely a 1 percentage point decrease in the parent tax rate, is associated with a 3%
reduction in reported EBITDA
The second specification (Table 2, column (2)) uses the tax variables split in two, the local tax
rate and the parent company tax rate. The coefficient on the local tax rate is negative and
statistically significant at a 95% confidence level. The sign of the coefficient is according to
expectations, and the magnitude (-5.5) is somewhat larger than the coefficients from the
previously cited articles. There has been no variation in the statutory tax rate that applies to
Norwegian petroleum companies over the period under consideration. This leads me to
believe that the strong negative impact of the local tax rate on reported EBITDA possibly
44
captures a UK-specific trend in profitability. The local tax rate in the UK has been stepwise
increased over the period (Table 9 in the appendix). If the profitability in the British
petroleum industry has decreased on average in the same period, this could be captured by
this coefficient.
The coefficient on the parent company’s tax rate is surprising. Its size and sign (-12.4) implies
that a one percentage point increase in the parent company tax rate is associated with a 12.4%
decrease in reported EBITDA. This is contrary to expectations. If the parent company tax rate
increases by one percentage point, this should reduce the incentives for profit shifting, as it
makes profit shifting to the parent company less profitable, because more of the shifted profit
is paid in taxes.
In isolation, this result means that the hypothesis that splitting the tax variable in two would
give a negative coefficient on the local tax rate and a positive coefficient on the parent tax
rate, as stated at the end of section 3.1.2, is rejected. This indicates that splitting the tax
difference variable in two has provided some new insight, in the form of new questions which
it would be interesting to pursue further in future research.
Several of the parent country CIT rates have decreased over the period 2005 – 2014: The UK,
which accounts for 28% of the parents of all company-year observations in the sample, have
seen a steady decline in corporate income tax rates, with the tax rate starting at 30 % in 2005,
and declining stepwise to 21% in 2014. Japan is the second most frequent parent country in
the sample, being parent country in 9% of all company-year observations in the sample. The
Japanese corporate tax rate increased slightly in 2006, from 39.5% to 40.69%, before it again
declined in two steps, first to 38.01% in 2012, then to 35.64% in 2014. The tables with
corporate tax rates are included in the appendix (Table 5), along with a frequency table
showing location of the parent companies in the sample (Table 6). If the petroleum companies
have been increasingly profitable over the period, for some reason that is not captured by the
oil price control variable or the inclusion of year dummies, this could explain why the
coefficient it negative, large, and statistically significant. This could be unrelated to taxes, but
there is also a chance that the estimates capture the existence of strategic location of assets
and affiliates, which are not observed in the data set which is confined to European affiliates.
Reduced CIT rates in parent countries may induce tax authorities to increase enforcement
capacity, as the perceived threat to the tax base is heightened. This could be reflected in
45
increased reported EBITDA, as companies have to abide by stricter forms of regulation, while
the risk of being caught and penalized is higher. This is slightly different from the
documentation requirement explanatory variable employed by Beer and Loeprick (2015b).
They argue that the number of years passed since the documentation requirements were
introduced, determines the level of enforcement of arm’s length prices in intrafirm trade. I
propose that there is also a possibility that the enforcement increases as a response to foreign
CIT rates.
The R2 that is reported in the fixed effects-table is the within R2. In the fixed effects model,
we are rid of the explanatory effects of the individual intercepts, so the within R2 is
necessarily lower than the adjusted R2 from the OLS estimation. The increase in the within R2
from the first to the second specification is worth to remark on: The within R2 gives the
proportion of the explainable variance, after group effects have been taken into account, that
is explained by the variables varying within groups. An increase in the within R2 of nearly 0.1
is quite high, given the initial value of 0.1219.
46
5 Conclusion My goal in this thesis was to investigate whether petroleum companies that are active on the
Norwegian and British continental shelves engage in tax motivated profit shifting. By the use
of two different techniques, I have estimated that the companies on average reduce their
reported EBITDA by 1.4%-3% when the tax difference increases by 1 percentage point.
When splitting the tax difference variable into two separate variables, the local tax rate and
the parent tax rate, some of the coefficients that result are harder to explain. From the OLS
estimation (Table 1, column(2)), the coefficient on parent tax rate implies that a one
percentage point increase in the parent tax rate is associated with a 3.2% increase in reported
EBITDA, which is in line with the results in column (2) of the company fixed effects
estimation (Table 2). The coefficient on the local tax rate is very imprecisely estimated and
seems to have no separate effect on the reported EBITDA. This lends support to the view that
local tax rates are likely to affect reported profit mainly through investment decisions. The
coefficients that result from the second specification of the fixed effects estimation (Table 2,
column(2)) imply that an increase in the local tax rate is associated with a reduction in
reported EBITDA of 5.5%, which is a larger effect than those seen in most previous research
in this thesis. The coefficient on the parent CIT rate of -12.4, suggests that there are other
factors that impact reported profits, which correlate with the trend in parent company CIT
rates. This could be an interesting path to follow in future research.
The estimations presented in this thesis thus suggest that there exists some tax motivated
profit shifting in the Norwegian and British offshore petroleum industries. This confirms the
findings presented in Beer and Loeprick’s paper to a certain extent (2015b). There are several
differences between the approach used in this thesis, and the strategy used in Beer and
Loeprick: I have used log(EBITDA) in place of log(EBIT), based on my opinion that this
variable corresponds better to the dependent variable in the theoretical model. I have also
excluded observations that have missing values of costs of employment. This reduces the
amount of measurement error that may have biased the estimates in Beer and Loeprick
(2015b), but may have introduced its own bias in the sample. I have found the productivity
measure used by both Hines and Rice (1994), and Beer and Loeprick (2015b) to be
inappropriate for use in this context, but would have liked to be able to include a better
measure of the labour productivity in this specific sector. I have also estimated the tax rates
applicable to British petroleum companies more precisely, using ownership data and
47
production volume data from the period 2009 – 2014 (Department of Energy & Climate
Change, 2016b). This alters the results somewhat, as presented in table 3 and 4 in the
appendix. In my estimations, I use only data from companies that are producing petroleum on
the British and Norwegian continental shelves. This ensures that the companies are facing
similar production conditions. I have used a simplified version of the tax difference variable.
It is not given that this simplified version is better, as it captures only the difference between
the tax rates of the affiliate and its parent. This is nonetheless a reflection of my belief that the
average difference between the tax rates of the petroleum affiliate and all other affiliates in the
group not automatically and in full captures the company’s profit shifting incentives.
Including the statutory tax rate applicable to the petroleum company as a separate explanatory
variable produces some interesting results, but as there has been no variation in the tax rate
that applies to Norwegian petroleum companies, these results may capture a UK-specific
trend.
The results are hard to compare to the ones obtained by Beer and Loeprick (2015b), as the
sample used for the analysis I present here is much smaller and the selection criteria may have
introduced bias in the sample, which would make it unwise to generalize these results out of
sample.
The criteria that were used in the selection procedure were on location, on industry
classification, the number of subsidiaries, the availability of accounts for at least three years,
and ownership structure. When choosing companies that are located in Norway and in the
UK, all companies selected are located in countries with well-developed institutions and
capabilities to enforce the rules that apply. Although this is true for several other oil and gas
producing countries, there are also those who do not have these institutions in place. This may
lead to smaller estimates of profit shifting than if I were using a sample of companies located
in countries with a larger variation in institutional capabilities. The fact that profit shifting in
Norway and the UK indeed seems to exists, as far as my analysis shows and with reference to
the work cited previously, points to the information asymmetries that arise from the
complexities of MNEs and the problems of establishing arms’ length prices for bespoke items
and used capital goods.
The exclusion of companies that have subsidiaries was done for practical reasons. This could
also have introduced bias with respect to available channels for profit shifting. I exclude
companies that have the opportunity to shift profits to and from a subsidiary. However, as the
48
channels for profit shifting include shifting to and from all affiliates of the same group, this
bias may be insignificant.
The bias I am most concerned about is the one created by the restriction I put on the
dependent variable when I use a logarithmic transformation: The exclusion of all observations
with reported EBITDA ≤ 0. This introduces a bias by only allowing for profitable company-
year observations to be part of the estimations. It seems clear that the profitability of the
company both will be affected by and have an effect on the profit shifting that takes place in a
company in a given year. The direction of the possible bias is not evident: Loss-making
companies can have less incentive to engage in profit shifting, as there could be some limit on
loss offsets. While Norwegian and British companies that report a loss are allowed to carry
forward the loss at a risk free interest rate, this is not sufficient to make the companies
indifferent between having positive profits that are taxed this period and having a loss this
period and deduct the forward carried loss from positive profits in the next period. The
present value of the future deduction is lower, both due to the interest rate loss and the
uncertainty. This implies that a firm would not intentionally create a loss by shifting too much
profit to the parent or to an affiliate. A reported loss could still be a consequence of profit
shifting if the firm is mistakenly setting transfer prices too high or too low. The firm would
end up with a loss, perhaps also because it is not able to adjust production volumes to reduced
output prices fast enough, but the negative reported profit is most likely not intended. The
direction of the possible bias that is introduced by the exclusion of loss-making companies is
therefore hard to determine.
A suggestion for further research would be to include variables, other than statutory tax rates,
that affect EMTR and EATR, to better be able to differentiate between profit shifting and
traditional tax distortion. EMTR predicts traditional tax effects better than statutory rates, at
least theoretically. As the negative coefficient on parent tax rate from Table 2, column (2) also
leaves me with questions unanswered, a further investigation into this matter would be
interesting for future research.
49
Bibliography Atkinson, A. B., & Stiglitz, J. E. (2015). Lectures on public economics. Princeton, N.J:
Princeton University Press. Beer, S., & Loeprick, J. (2015a). Profit shifting: drivers of transfer (mis)pricing and the
potential of countermeasures. International Tax and Public Finance, 22(3), 426-451. doi:10.1007/s10797-014-9323-2
Beer, S., & Loeprick, J. (2015b). Taxing Income in the Oil and Gas Sector - Challenges of International and Domestic Profit Shifting. WU International Taxation Research Paper Series, (2015 -18). Vienna.
Boadway, R., & Keen, M. (2010). Perspectives on resource tax design. In P. Daniel, M. Keen, & C. McPherson (Eds.), The taxation of petroleum and minerals: Principles, problems and practice (pp. 13-74). London: Routledge.
Buettner, T., Overesch, M., Schreiber, U., & Wamser, G. (2012). The impact of thin-capitalization rules on the capital structure of multinational firms. The Journal of Public Economics, 96(11-12), 930-938. doi:10.1016/j.jpubeco.2012.06.008
Daniel, P., Goldsworthy, B., Maliszewski, W., Puyo, D. M., & Watson, A. (2010). Evaluating fiscal regimes for resource projects. An example from oil development. In P. Daniel, M. Keen, & C. McPherson (Eds.), The taxation of petroleum and minerals: Principles, problems and practice (pp. 187 - 240). London: Routledge.
de Villiers Graaff, J. (1950). Income Effects and the Theory of the Firm. The Review of Economic Studies, 18(2), 79-86.
Deloitte. (2013). Oil and gas taxation in the UK Deloitte taxation and investment guides. London: Deloitte Touche Tohmatsu Ltd.
Deloitte. (2014). Oil and gas taxation in Norway Deloitte taxation and investment guides. London: Deloitte Touche Tohmatsu Ltd.
Department of Energy & Climate Change. (2016a). DECC Field Partners. Retrieved from https://www.og.decc.gov.uk/fields/field_partners.txt 11.03.2016
Department of Energy & Climate Change. (2016b). UK Annual Oil / Gas Production (M3) Offshore Fields. Retrieved from https://itportal.decc.gov.uk/pprs/full_production.htm, 11.03.2016
Devereux, M., & Griffith, R. (2003). Evaluating Tax Policy for Location Decisions. International Tax and Public Finance, 10(2), 107-126. doi:10.1023/A:1023364421914
Dharmapala, D. (2014). What Do We Know about Base Erosion and Profit Shifting? A Review of the Empirical Literature. Fiscal Studies, 35(4), 421-448. doi:10.1111/j.1475-5890.2014.12037.x
Dharmapala, D., & Riedel, N. (2013). Earnings shocks and tax-motivated income-shifting: Evidence from European multinationals. The Journal of Public Economics, 97, 95.
Dukes Wood Oil Museum. (2007). The Story of North Sea Oil and Gas. Retrieved from http://www.dukeswoodoilmuseum.co.uk/offshore%20history.htm, 19.4.2016
Dyreng, S. D., & Markle, K. S. (2016). The Effect of Financial Constraints on Income Shifting by U.S. Multinationals. The Accounting Review, Forthcoming, accr-51420. doi:10.2308/accr-51420
Fane, G. (1987). Neutral taxation under uncertainty. Journal of Public Economics, 33(1), 95-105. doi:10.1016/0047-2727(87)90084-3
Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel/hierarchical models. Cambridge: Cambridge University Press.
Gompertz, S. (2012). Starbucks 'paid just £8.6m UK tax in 14 years'.16.10.2012 BBC News.
50
Grubert, H., & Mutti, J. (1991). Taxes, Tariffs and Transfer Pricing in Multinational Corporate Decision Making. The Review of Economics and Statistics, 73(2), 285-293. doi:10.2307/2109519
Heckemeyer, J. H., & Overesch, M. (2013). Multinationals’ Profit Response to Tax Differentials: Effect Size and Shifting Channels. Discussion Paper, (13-045). Mannheim.
Hindriks, J., & Myles, G. D. (2013). Intermediate public economics (2nd ed. ed.). Cambridge, Mass: MIT Press.
Hines, J. R., & Rice, E. M. (1994). Fiscal Paradise: Foreign Tax Havens and American Business. The Quarterly Journal of Economics, 109(1), 149-182.
HM Revenue & Customs. (2010). Statement of practice 2 (2010). Retrieved from https://www.gov.uk/government/publications/statement-of-practice-2-2010/statement-of-practice-2-2010. 27.04.2016
HM Revenue & Customs. (2013). Corporation Tax: rates of tax. (CTM01750). HM Revenue & Customs Retrieved from http://www.hmrc.gov.uk/manuals/ctmanual/ctm01750.htm. 19.04.2016
HM Revenue & Customs. (2016a). Corporation tax ring fence: the supplementary charge: introduction. (OT21200). Retrieved from https://www.gov.uk/hmrc-internal-manuals/oil-taxation-manual/ot21200. 19.04.2016
HM Revenue & Customs. (2016b). An introduction to the UK's transfer pricing legislation. Retrieved from https://www.gov.uk/hmrc-internal-manuals/international-manual/intm412010. 27.04.2016
HM Revenue & Customs. (2016c). PRT: Changes - FA93 - Reduction in rate of PRT. (OT03525). Retrieved from https://www.gov.uk/hmrc-internal-manuals/oil-taxation-manual/ot03525. 06.02.2016
HM Revenue & Customs. (2016d). Transfer pricing: the main thin capitalisation legislation: Overview. Retrieved from https://www.gov.uk/hmrc-internal-manuals/international-manual/intm413010. 19.04.2016
Huizinga, H., & Laeven, L. (2008). International profit shifting within multinationals: A multi-country perspective. Journal of Public Economics, 92(5), 1164-1182. doi:10.1016/j.jpubeco.2007.11.002
Koester, A., Shevlin, T. J., & Wangerin, D. (2016). The Role of Managerial Ability in Corporate Tax Avoidance. Management Science, Forthcoming.
KPMG. (2012). A Guide to UK Oil and Gas Taxation: KPMG LLP. Lund, D. (2002). Rent taxation when cost monitoring is imperfect. Resource and Energy
Economics, 24(3), 211-228. doi:10.1016/S0928-7655(01)00053-7 Mintz, J., & Chen, D. (2012). Capturing Economic Rents from Resources through Royalties
and Taxes (Vol. 5). Calgary: The School of Public Policy. Noreng, Ø. (1980). The oil industry and government strategy in the North Sea. London:
Croom Helm. Norsk Olje & Gass. (2010). Olje- og gasshistorien. Retrieved from
https://www.norskoljeoggass.no/no/Faktasider/Oljehistorie/, 18.04.2016 Norwegian Ministry of Finance. (2013). Reduced uplift in the petroleum tax system [Press
release]. Retrieved from https://www.regjeringen.no/en/aktuelt/reduced-uplift-in-the-petroleum-tax-syst/id725999/
OECD. (2006). Annual Report on the OECD Guidelines for Multinational Enterprises - 2006 Edition : Conducting Business in Weak Governance Zones. Paris: OECD Publishing.
OECD. (2010). OECD Transfer Pricing Guidelines for Multinational Enterprises and Tax Administrations 2010. Paris: OECD Publishing.
51
OECD. (2012). Transfer Pricing Country Profile - Norway. Retrieved from http://www.oecd.org/tax/transfer-pricing/transferpricingcountryprofiles.htm, 27.04.2016
OECD. (2014). Model Tax Convention on Income and on Capital : Condensed Version 2014. Paris: OECD Publishing.
OECD. (2015). Measuring and Monitoring BEPS, Action 11 - 2015 Final Report. Paris: OECD Publishing.
OECD.Stat. (2016a). Growth in GDP per capita, productivity and ULC. OECD.Stat http://stats.oecd.org/Index.aspx?DataSetCode=PDB_LV Retrieved 28.04.2016
OECD.Stat. (2016b). Productivity and ULC by main economic activity (ISIC Rev.4). OECD.Stat http://stats.oecd.org/Index.aspx?DatasetCode=LEVEL# Retrieved 28.04.2016
Oljedirektoratet. (2016). Factpages. Retrieved from http://factpages.npd.no/factpages/Default.aspx?culture=no 07.01.2016
Parra, F. (2004). Oil politics : a modern history of petroleum. London: I.B. Tauris. Sandmo, A. (1976). Optimal taxation: An introduction to the literature. Journal of Public
Economics, 6(1), 37-54. doi:10.1016/0047-2727(76)90040-2 Simmler, M. (2012). The Impact of Introducing an Interest Barrier: Evidence from the
German Corporation Tax Reform 2008 (Vol. 1215): DIW Berlin, German Institute for Economic Research.
Solow, R. M., & Wan, F. Y. (1976). Extraction Costs in the Theory of Exhaustible Resources. The Bell Journal of Economics, 7(2), 359-370. doi:10.2307/3003261
Statistics Norway. (2016). Årlig nasjonalregnskap. Produksjon per utførte timeverk. Endring fra året før (prosent). Faste priser. . https://www.ssb.no/statistikkbanken/SelectVarVal/Define.asp?MainTable=NRLonnSyssel&KortNavnWeb=nr&PLanguage=0&checked=true Retrieved 15.04.2016
Stewart, H. (2015). Facebook paid £4,327 corporation tax despite £35m staff bonuses.11.10.2015 The Guardian. Retrieved from http://www.theguardian.com/global/2015/oct/11/facebook-paid-4327-corporation-tax-despite-35-million-staff-bonuses
Tax Justice Network. (2015). The Scale of BEPS. Retrieved from http://www.taxjustice.net/scaleBEPS/, 27.04.2016
Tracy, B. S., Tordo, S., & Arfaa, N. (2011). National Oil Companies and Value Creation. Washington: World Bank Publications.
UK Department of Energy & Climate Change. (2016). Licence Data - by Company Group and Block. Retrieved from https://itportal.decc.gov.uk/information/licence_reports/databycompanyandblock.html, 26.01.2016
52
Appendix Table 3
Comparison of OLS results using 25 % PRT-liability rule
Dependent variable: Log(EBITDA) OLS estimation
Explanatory variable (1) (2) (3) (4)
Log(Fixed assets) 0.750*** 0.754*** 0.717*** 0.721***
(0.089) (0.099) (0.099) (0.101)
0.000 0.000 0.000 0.000
Log(Cost of employees) 0.323*** 0.311*** 0.275*** 0.280***
(0.093) (0.083) (0.087) (0.106)
0.001 0.000 0.002 0.008
Oil price, average of lag (2 ‐ 4) ‐0.030*** ‐0.029*** ‐0.027*** ‐0.027***
(0.006) (0.006) (0.006) (0.006)
0.000 0.000 0.000 0.000
Tax difference ‐1.431
(1.021)
0.161
Alternative tax difference1 ‐2.092**
(0.957)
0.029
Local tax rate ‐0.112
(0.875)
0.898
Alternative local tax rate2 ‐0.606
(0.883)
0.493
Parent tax rate 3.204** 3.308**
(1.492) (1.382)
0.032 0.017
Constant 1.354* 1.601* 0.601 0.790
(0.755) (0.914) (0.865) (0.800)
0.073 0.080 0.487 0.324
Number of observations 122 122 122 122
Adjusted R2 0.6143 0.6232 0.6308 0.6316 1)The alternative tax difference is equal to the alternative local tax rate2 less the CIT rate that applies to the parent company. 2)The alternative local tax rate is calculated by imposing a rule that 25% of a company’s earnings derive from PRT-liable fields, thereby taxing this share of the earnings at the rate (τPRT + (1 – τPRT)(τRFCT + τSC), while taxing the rest at (τRFCT + τSC).
53
Table 4
Comparison of company fixed effects results using 25% PRT-liability rule
1)The alternative tax difference is equal to the alternative local tax rate2 less the CIT rate that applies to the parent company. 2)The alternative local tax rate is calculated by imposing a rule that 25% of a company’s earnings derive from PRT-liable fields, thereby taxing this share of the earnings at the rate (τPRT + (1 – τPRT)(τRFCT + τSC), while taxing the rest at (τRFCT + τSC).
Dependent variable: Log(EBITDA) Company fixed effects estimation
Explanatory variable (5) (6) (7) (8)
Log(Fixed assets) 0.098 0.142 ‐0.092 0.0250
(0.264) (0.304) (0.241) (0.269)
0.710 0.640 0.704 0.926
Log(Cost of employees) 0.232 0.247 0.277 0.308*
(0.160) (0.168) (0.178) (0.163)
0.147 0.141 0.118 0.059
Oil price, average of lag (2 ‐ 4) ‐0.011 ‐0.012 ‐0.016* ‐0.018**
(0.009) (0.009) (0.009) (0.008)
0.217 0.162 0.076 0.025
Tax difference ‐3.087**
(1.520)
0.042
Alternative tax difference1 ‐3.306
(2.575)
0.199
Local tax rate ‐5.500***
(1.950)
0.005
Alternative local tax rate2 ‐7.803**
(3.148)
0.013
Parent tax rate ‐12.429** ‐11.577*
(5.769) (6.858)
0.031 0.091
Constant 9.478*** 9.027*** 18.019*** 17.797***
(2.606) (3.104) (3.999) (4.746)
0.000 0.004 0.000 0.000
Number of observations 122 122 122 122
Within R2 0.1219 0.1060 0.2134 0.2016
54
Table 5
Corporate Income Tax rates
Country 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Austria 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25
Bermuda 0 0 0 0 0 0 0 0 0 0
British Virgin Islands 0 0 0 0 0 0 0 0 0 0
Canada 0.342 0.361 0.361 0.335 0.33 0.31 0.28 0.26 0.26 0.265
Cayman Islands 0 0 0 0 0 0 0 0 0 0
Cyprus 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.125 0.125
Denmark 0.28 0.28 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.245
Germany 0.399 0.3834 0.3836 0.2951 0.2944 0.2941 0.2937 0.2948 0.2955 0.2958
Hungary 0.16 0.16 0.16 0.16 0.16 0.19 0.19 0.19 0.19 0.19
Iran 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25
Japan 0.395 0.4069 0.4069 0.4069 0.4069 0.4069 0.4069 0.3801 0.3801 0.3564
Kuwait 0.55 0.55 0.55 0.55 0.15 0.15 0.15 0.15 0.15 0.15
Norway 0.28 0.28 0.28 0.28 0.28 0.28 0.28 0.28 0.28 0.27
Poland 0.19 0.19 0.19 0.19 0.19 0.19 0.19 0.19 0.19 0.19
Russia 0.24 0.24 0.24 0.24 0.2 0.2 0.2 0.2 0.2 0.2
South Korea 0.275 0.275 0.275 0.275 0.242 0.242 0.22 0.242 0.242 0.242
Spain 0.35 0.35 0.325 0.35 0.35 0.35 0.28 0.28 0.28 0.28
USA 0.393 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4
UK 0.3 0.3 0.3 0.3 0.28 0.28 0.26 0.24 0.23 0.21
55
Table 6
Frequency table of parent countries’ fraction of parent companies.
Table 7
OLS estimation of the impact of local tax rates on factors of production
Dependent variables: Log(Fixed assets) Log(Cost of employees) Explanatory variables (1) (2) (3) (4)
Local tax rate 3.784*** 2.871 4.279*** ‐11.569 (0.796) (8.713) (1.226) (13.989) 0.000 0.742 0.001 0.410
(Local tax rate)2 0.744 12.744 (7.070) (11.206) 0.916 0.257
Constant 8.524*** 8.796*** 4.948*** 9.705** (0.474) (2.625) (0.730) (4.246) 0.000 0.001 0.000 0.024
Number of observations 770 770 150 150
Adjusted R squared 0.0273 0.0261 0.0698 0.0717 Stars indicate significance level: * p<0.1; ** p<0.05; *** p<0.01. P-values also included in italics.
Parent country Frequency Percent
Austria 17 6.42
British Virgin Islands 7 2.64
Canada 9 3.4
Cayman Islands 9 3.4
Cyprus 4 1.51
Denmark 8 3.02
Germany 19 7.17
Hungary 14 5.28
Iran 9 3.4
Japan 24 9.06
Kuwait 9 3.4
Norway 8 3.02
Poland 16 6.04
Russia 5 1.89
South Korea 10 3.77
Spain 6 2.26
UK 74 27.93
USA 9 3.4
Bermuda 8 3.02
Total 265 100.03
56
Table 8
Descriptive statistics of original sample. Fixed assets, costs of employees and EBITA are in 1000 EUR. Standard deviation of the mean is given in parenthesis.
Descriptive statistics
Norway United Kingdom Total
Observations Min Max Mean Observations Min Max Mean Observations Min Max Mean
Years w/accounts 250 3 10 7.92 939 3 10 8.850 1189 3 10 8.654
(2.596) (1.953) (2.137)
Group size 250 2 5135 540.56 939 2 8781 628.076 1189 2 8781 609.675
(1038.091) (1373.057) (1309.844) Number of employees 25 0 110 30.76 209 1 328 30.368 234 0 328 30.410
(28.107) (66.151) (63.149)
Fixed assets 198 0 4699957 388298.8 817 0 5605617 233525.9 1015 0 6E+06 263718.1
(817368.2) (574887.9) (632078.4)
Cost of employees 140 ‐315.73 142452.7 6075.026 154 2.98 58322 5101.139 294 ‐315.73 142452.7 5564.895
(12445.03) (8533.624) (10570.68)
EBITDA 156 ‐157958.8 668346.7 63002.48 612 ‐614593.3 3075687 85622.08 768 ‐614593.3 3E+06 81027.47
(152406.8) (258206.1) (240597.7)
Log(EBITDA) 64 5.3 13.413 11.321 461 0.308 14.939 10.273 525 0.308 14.939 10.401
(1.801) (2.008) (2.012)
Parent CIT 236 0 0.55 0.263 850 0 0.55 0.288 1086 0 0.55 0.283
(0.112) (0.083) (0.091)
Local CIT+RRT 236 0.78 0.78 0.78 856 0.4 0.81 0.582 1092 0.4 0.81 0.625
(0) (0.104) (0.123)
Tax difference 236 0.23 0.78 0.517 850 ‐0.06 0.62 0.2934153 1086 ‐0.06 0.78 0.342
(0.112) (0.130) (0.156)
57
Table 9
Petroleum company tax rates
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
United Kingdom Non PRT‐liable 0,40 0,50 0,50 0,50 0,50 0,50 0,50 0,62 0,62 0,62
PRT‐liable 0,70 0,75 0,75 0,75 0,75 0,75 0,75 0,81 0,81 0,81
Norway All 0,78 0,78 0,78 0,78 0,78 0,78 0,78 0,78 0,78 0,78