Profit shifting in the Norwegian and British …...V Abstract In this master’s thesis, I explain...

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

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.

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.

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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

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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

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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

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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

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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.

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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

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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

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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.

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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

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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).

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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.

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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.

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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

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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


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

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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


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)

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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

Profit shifting in the Norwegian and British …...V Abstract In this master’s thesis, I explain...

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