Real Responses to Anti-tax Avoidance:Evidence from the UK Worldwide Debt Cap

Katarzyna Bilicka∗ Yaxuan Qi†

Jing Xing‡

April 2020

Abstract

We analyze how multinational firms reallocate real operations and debt across their

affiliates in response to anti-tax avoidance policies. The UK introduced a worldwide

debt cap in 2010, generating a quasi-natural experiment that limited interest deductibil-

ity for a group of multinational firms. We find that multinationals affected by the

reform reduced the amount of debt held in the UK and increased debt held abroad.

Affected multinationals reallocated a share of their real operations away from the UK.

Our findings provide causal evidence for tax-motivated debt and real activity realloca-

tion within multinationals and show how multinationals can circumvent tax avoidance

regulations.1

JEL: H25, H26

Keywords: Debt Shifting, Multinational Companies, Capital Reallocation

∗Utah State University and Oxford University Centre for Business Taxation, John Huntsman BusinessSchool, Logan, United States; katarzyna.anna.bilicka@gmail.com.†Department of Economics and Finance, City University of Hong Kong, yaxuanqi@cityu.edu.hk.‡Antai College of Economics and Management, Shanghai Jiao Tong University, 1954 Huashan Road,

Shanghai 200030, China, jing.xing@sjtu.edu.cn1We would like to thank Jennifer Blouin, Steve Bond, Mike Devereux, Jim Hines, Krzysztof Karbownik,

James O’Donovan, Daniela Scur, Michael Stimmelmayr, Juan Carlos Suarez Serrato and Bohui Zhang fortheir comments. Further thanks to the participants of National Tax Association conference, Utah TaxInvitational, China International Conference in Finance, Asia Meeting of Econometric Society, Ce2 workshop,Oxford University Centre for Business Taxation Summer Symposium, Fanhai International School of Financeat Fudan University seminar, International Institute of Public Finance Annual Congress and EuropeanEconomic Association Congress for their helpful suggestions. Xing acknowledges financial support fromNational Natural Science Foundation of China (No. 71903125), Shanghai Pujiang Program (No. BV1200116)and Shanghai Institute of International Finance and Economics. All omissions and errors are our own.

1 Introduction

Multinational tax avoidance has been a subject of political discussion in recent years,

as there is growing evidence that multinational corporations (MNCs) pay little tax (Bilicka,

2019; Torslov et al., 2018). The political pressure has been exacerbated by the revelations

from Panama and Paradise papers in 2016 and 2017 that exposed details of some of the

tax avoidance schemes to the public. Despite efforts to curb such practices, with countries

around the world adopting various anti-tax avoidance measures, the extent of profit shifting

has been increasing over time (Clausing, 2016). Therefore, it remains empirically unclear

how effective these measures are. Even less is known about how anti-tax avoidance measures

affect business activities of multinational firms.

Allocating debt across different tax jurisdictions is a particularly popular method that

MNCs use to lower their worldwide tax burden. Relative to a domestic firm, an MNC can

easily shift debt across affiliates via its internal capital market. In this paper, we examine

a new anti-tax avoidance measure that aims to tackle debt shifting by MNCs. In 2010,

the UK pioneered in implementing a worldwide anti-avoidance approach, the Worldwide

Debt Cap rule (WDC), which benchmarks operation of MNCs in a single country against

their worldwide activities. Such measures are becoming more prominent policy tools, with

countries like the United States implementing similar restrictions in December 2017.2 In

its Action Plan for limiting Base Erosion involving interest deductions, the OECD suggests

using the worldwide approach to complement the existing anti-debt shifting rules (OECD,

2015). In this paper, we provide the very first empirical investigation of the impact of this

new anti-tax avoidance regulation.

We rely on difference-in-differences (DID) methodology to draw causal inference. The

key feature of the UK’s WDC is that it set up a maximum ratio of debt to be held in the

UK relative to the overall debt for each MNC. Debt above the maximum ratio, the “gateway

ratio”, was disallowed for tax deduction. Therefore, only MNCs that failed the gateway

test were affected by the WDC. This feature allows us to use the DID approach to control

for confounding effects, such as the UK’s territorial tax system reform which applied to all

UK firms, and provide causal estimates for the incremental effect of the WDC. Further, the

2The US rule put a 30% limit on net business interest expense (the excess of business interest expense overbusiness interest income) as a fraction of a taxpayer’s “adjusted taxable income.” For tax years beginningafter December 31, 2017, and before January 1, 2022, “adjusted taxable income” is similar to EBITDA. Fortax years beginning after December 31, 2021, adjusted taxable income is similar to EBIT. For more details seehttps://www.cbh.com/guide/articles/planning-for-the-new-business-interest-expense-deduction-limitation.

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WDC targeted one particular form of profit shifting, i.e., interest deductibility. This allows

us to directly pin down the effects of tax-motivated debt shifting.

We compile a unique dataset that matches MNCs with their subsidiaries around the

world. This dataset allows us to trace over a decade of financing and real business activities

of the ultimate parents of MNCs and their subsidiaries. We use this novel data to investi-

gate how MNCs adjust their debt, operations and organizational structures across different

jurisdictions in response to the WDC. Our key findings are as follows.

First, we find that the WDC effectively curbed MNCs’ excessive borrowing in the UK, as

evidenced by significantly reduced UK debt and gateway ratio. Affected MNCs reduced their

gateway ratios by 29%. This was achieved by decreasing the UK net debt and increasing

the worldwide debt. The WDC also caused affected MNCs to increase debt in foreign

subsidiaries, particularly in those located in countries with statutory tax rates higher than

the UK. This provides causal evidence that MNCs shift debt cross-border to minimize their

overall tax liabilities.

Second, we show that tax-motivated debt shifting leads to reallocation of real operations.

Affected MNCs shrank the size of their business operations in the UK, measured by the

change in total assets, fixed assets, and employment, while expanding elsewhere. On average,

over the period 2010-2014, affected MNCs reduced total assets, fixed assets and employment

in their UK subsidiaries by 7.5%, 11.4% and 3.9% respectively. At the same time, they

substantially increased their real operations in their non-UK subsidiaries. We find that

MNCs moved real operations towards countries with higher tax rates, which is consistent

with our conjecture that debt shifting into these regions lowers the cost of capital. This

evidence suggests that MNCs reallocate asset and labour in response to the WDC in the

same direction as debt. We further find that MNCs adjust their organizational structures

to offset the impact of the UK anti-tax avoidance measure. In particular, affected MNCs

reduced the percentage of relevant UK subsidiaries that were included in the calculation of

UK debt. Affected MNCs also increased the percentage of subsidiaries in countries with a

higher tax rate than that in the UK, while reduced that in countries with a lower tax rate.

Taken together, these results suggest that the WDC affected MNCs beyond their financing

patterns, yielding real reallocation of subsidiaries, assets and employment across borders.

Third, we find that foreign MNCs have more flexibility than their UK counterparts in

circumventing the UK anti-tax avoidance policy. MNCs can reduce the gateway ratio by

either decreasing the net UK debt (i.e., the numerator of gateway ratio) or increasing the

worldwide debt (i.e., the denominator of gateway ratio). We find domestic MNCs lower their

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gateway ratios mainly through reducing net UK debt, while foreign MNCs do so mainly

through increasing their worldwide debt. Further, the effect of the WDC on reallocation of

business activities is stronger for foreign MNCs than for domestic MNCs, indicating a home

bias for the latter. In particular, only foreign MNCs reduced the size of their UK operations

significantly, while expanding the size of their non-UK operations more than domestic MNCs.

We further study UK tax paid by foreign and domestic MNCs and find that the WDC raised

UK tax payment from domestic MNCs, but not from foreign MNCs. One implication of

these findings is that the WDC may have created a competitive disadvantage for domestic

MNCs.

Further, our findings suggest that the WDC had spill-over effects on other countries’

economies and tax revenues. We show that the WDC led to more investment and employment

in non-UK affiliates of the affected MNCs. Although affected MNCs shift debt abroad, there

was no negative shock to foreign national governments’ budget as we didn’t find reduced

foreign tax payment by affected MNCs. This is because real business activities also went

overseas, and this enlarged tax base of foreign countries.

To make sure that our results are not contaminated by other events or policy reforms that

occurred during our sample period, we address three potential threats to our identification

strategy: the 2007-2008 financial crisis, UK corporate tax rate cuts and its 2009 territorial tax

reform. Our DID setting partially addresses these concerns, because these events would affect

all firms, while the WDC only affects MNCs that failed the gateway ratio test. However,

if these events affected the debt policies of our treated and control firms differently, our

results may be confounded. For example, if MNCs that failed the gateway ratio test faced

higher default risk, the 2007-2008 financial crisis could have caused them to reduce debt

more than the control group.3 Alternatively, if MNCs that failed the gateway ratio test were

facing higher non-UK average corporate tax rate relative to the UK one, the UK tax rate

cut would affect them more than the control group. The tax cuts may also have different

impact on treated and control MNCs, if they had different effective tax rates or profitability

in the UK. Last, the transition from the worldwide to the territorial tax system may lead

treated MNCs to reduce debt financing in the UK more than the control group. This would

be the case, if the treated MNCs repatriated more profits back to the UK to support new

investment, which would reduce debt financing (Arena and Kutner, 2015; Egger et al., 2015).

We take multi-pronged approach to address these concerns. First, we employed propen-

sity score matching to ensure that the treated and control groups have similar group-level

3However, this argument is mostly relevant to firms’ external debt.

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size and total debt. This alleviates the concern that treated MNCs may have higher default

risk than the control group. Second, to address the concerns about the UK tax rate cuts,

we directly compare the average statutory corporate tax rates faced by MNCs’ non-UK sub-

sidiaries. We further include UK effective tax rate (ETR) and MNCs’ UK profitability as

additional matching variables in the robustness tests. Matching on these two variables does

not change the main result.4 Third, to alleviate concerns about the territorial tax system

reform, we directly examine differences in repatriated profits between treated and control

group MNCs and find no evidence that treated MNCs received more repatriated profits.

In addition, the territorial tax system reform should have much smaller impact on foreign

MNCs relative to domestic ones. We in fact find stronger results in terms of both debt and

real operations reallocation for treated foreign MNCs. This further suggests our results are

unlikely to be driven by the territorial tax reform.

We are at the frontier of research on the impact of anti-tax avoidance measures on real

economic activities. The paper closest to our analysis of real effects is Serrato (2018), who

shows that the repeal of a tax code that allowed US MNCs to exclude income from Puerto

Rico from US corporate taxes led them to shift investment and employment away from

the US. Our study focuses on a more general anti-tax avoidance measure that targets debt

shifting of MNCs. Unlike Serrato (2018) who uses consolidated group-level and geographic

segment data from Compustat to analyze the effects of anti-tax avoidance policies on real

activity reallocation, we use more detailed group-subsidiary matched data. This allows us

to address the reallocation across subsidiaries within the same MNC while controlling for

subsidiary-level characteristics. Further, while Serrato (2018) shows the general reallocation

of investment away from the US towards foreign countries by US MNCs, we find that most

of reallocation triggered by the WDC was done by foreign MNCs. In contrast, domestic

MNCs did not significantly reallocate real operation away from the UK.

Our study extends the literature on MNCs debt shifting and tax avoidance. The existing

literature mainly uses cross-jurisdictional differences in tax rates or interest deductibility

restrictions to understand MNCs’ borrowing patterns (Blouin et al., 2014; Buettner et al.,

2012; Desai et al., 2004; Huizinga and Laeven, 2008; Huizinga et al., 2008; Mintz and We-

ichenrieder, 2010). Nevertheless, results from cross-country studies may be confounded by

unobserved country-level differences that affect both interest deductibility and debt usage by

multinational firms. In contrast, we employ a quasi-natural experiment and the difference-

4Matching on these additional variables significantly reduces our sample size. Hence, we do not use thisapproach for the benchmark estimations.

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in-differences approach to provide causal estimates for the effect of anti-tax avoidance re-

strictions on MNCs’ behaviour.

This paper also echoes a growing literature that examines how MNCs reallocate real busi-

ness activities in response to economic and policy shocks, and how the resource allocations

of MNCs further affect the global economy (Almedia et al., 2015; Biermann, 2019; Boutin

et al., 2013; Desai et al., 2007; Giroud and Mueller, 2015, 2016; Huber, 2018; Kalemli-Ozcan

et al., 2016; Santioni et al., 2017). Textbook finance theories suggest that the change in

debt level and the net-of-tax cost of debt would affect the cost of capital and in turn have

a direct effect on investment. Hence, the tax-motivated debt shifting should have a direct

impact on MNC’s capital allocation. It is surprising that evidence on how tax-motivated

debt reallocation affects the real activities of MNCs is rare. Our paper fills this gap by

proving a detailed analysis on this issue.

Finally, our study provides the very first comprehensive examination of the impact of

the effectiveness of the “worldwide approach” as a new anti-tax avoidance measure. While

many countries have adopted the stand-alone rules that consider debt-to-equity or debt-to-

asset ratios of each subsidiary of MNC separately (notably, the thin-capitalization rules)

to curb debt-shifting by MNCs, evidence on their effectiveness is mixed. Many have rec-

ommended using the worldwide approach, more difficult to circumvent, to complement the

thin-capitalization rules. Apart from the UK, in December 2017 the US passed the Tax

Cuts and Jobs Act in which similar limits on net interest expense deductions of MNCs were

put into effect in the US. A paper concurrent to ours (Carrizosa et al., 2020) examines the

effects of the US tax reform, focusing only on debt reallocation of US firms. It is likely that

more countries will adopt the worldwide approach to tackle MNCs’ tax avoidance in the near

future. Therefore, our findings have important implications for the current policy debate.

The rest of the paper is structured as follows. Section 2 provides the policy background.

Section 3 illustrates our conceptual framework to understand the impact of the WDC. Section

4 discusses data and our empirical strategies. Section 5 presents the results and Section 6

concludes.

2 Policy background

Many countries have attempted to curb the extent of debt shifting of MNCs by im-

plementing anti-tax avoidance policies such as the thin-capitalization rules. The thin-

capitalization rules usually set up a fixed ratio, such as the debt-to-equity ratio or the

5

interest coverage ratio, and interest expense associated with debt exceeding the ratio are

often disallowed for tax deduction. The thin capitalization rules are stand-alone rules in the

sense that they consider each subsidiary of the MNC as a separate entity. Despite some evi-

dence that the thin capitalization rules reduce MNCs’ incentives to use internal debt for tax

planning purposes (Blouin et al., 2014; Buettner et al., 2012), the limitation of these rules

has also become apparent over the years. For example, the financing policies of MNCs are

likely to be highly centralized and the thin capitalization rules can be easily circumvented.5

More recently, the OECD has recommended to use the “worldwide approach” to supple-

ment the thin capitalization rules.6 The worldwide approach evaluates the MNCs’ allocation

of debt across affiliates by comparing the amount of debt located in each host country to

some worldwide consolidated benchmark, such as the MNCs’ worldwide debt or earnings

before interest, tax, depreciation and amortization (EBITDA). Arguably, it may be more

difficult or costly to circumvent the worldwide anti-tax avoidance measures since doing so

requires MNCs to manipulate the group-level consolidated debt or EBITDA. To circumvent

thin capitalization rules, by contrast, MNCs only need to adjust the financing policies of

a single subsidiary, which can be easily achieved via their internal capital market. Conse-

quently, it has been advocated that the worldwide approach should be more effective than the

thin capitalization rules in addressing earning stripping and debt shifting by MNCs (Desai

and Dharmapala, 2015; Dharmapala, 2014).

In January 2010, the UK tax authority (the HMRC) introduced the “worldwide debt cap”

(WDC) to restrict the generous tax deductions for financing expenses enjoyed by MNCs. The

rule was an outcome of a long consultation that started in June 2007. The HMRC’s aim

was that the UK should not bear interest expenses that, in aggregate, exceed the amount of

interest borne by an MNC as a whole. After the territorial tax system reform, the HMRC

needed to compensate tax revenue losses, as it no longer taxed dividends repatriated by

MNCs under the new territorial tax regime.7 Raising tax revenue by implementing the WDC

is one such measure. The WDC was also implemented to complement existing debt-related

thin-capitalization rules, which proved to not be that effective.8

5For example, multinationals can inject equity to subsidiaries with a high debt-equity ratio to avoidexceeding the fixed ratio. Webber (2010) provides the survey on the thin-capitalization and interest de-ductibility rules around the world.

6See, OECD (2015)‘s BEPS 2015 final report, Action 4.7Miller (2017)estimates that the anti-tax avoidance measures, especially the restriction on relief for in-

terest, have been the main way UK tax revenues have been raised since 2010.8Unlike thin capitalization rules in other countries, the UK rule is conducted on case by case basis and

hence, it is considerably more discretionary.

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The WDC was applicable for periods beginning on or after January 1 2010 and up until

April 1 2017. The WDC applies to qualifying MNCs that have a corporate tax residence

in the UK9, except those in the financial sector. A qualifying MNC is one that has more

than 250 employees, above e50m turnover and/or above e43m balance sheet total assets.

To apply the rule, each MNC first needs to calculate its UK net debt, which is aggregated

across its all UK relevant subsidiaries. Next, a gateway test based on the ratio of the MNC’s

UK net debt to its worldwide gross debt is conducted. If the gateway ratio exceeds 75%,

interest deduction is disallowed for the exceeding level of interest expenses. The WDC is not

optional. On April 1st 2017 the UK modified the WDC: the worldwide debt denominator

was replaced by EBITDA. This change likely reflects the concern that the original WDC

may lead to increase in MNCs’ worldwide debt and as a result default risk. Our result shows

that this concern is valid.

The UK net debt held by each UK subsidiary is the difference between relevant liabilities

and relevant assets. The type of borrowings that would be treated as relevant liabilities

includes short-term loans, overdrafts and long-term debt. Trade credit and liabilities in the

form of share capital, such as preference shares, are not treated as relevant liabilities for the

purposes of the gateway test, even if they are accounted for in financial liabilities. Relevant

assets include cash and cash equivalents, lending, investment in government or company

securities, and net investment in financial leases. To calculate the numerator of the gateway

ratio, the MNC needs to aggregate the UK net debt across all relevant UK subsidiaries,

which are 75% or more owned by the MNC. The denominator of the gateway ratio, the

MNC’s worldwide gross debt, is the consolidated liabilities of the worldwide group. While

the UK net debt includes both external and internal debt, the worldwide gross debt only

considers the MNC’s external debt.10

It is worth noting that the UK experienced other tax policy changes during the same

period of time. First, the UK moved from the worldwide tax system to the territorial tax

system in 2009 and thereafter it exempts dividend repatriation by MNCs from being taxed in

the UK. Studies show that the territorial tax system reform led to more dividend repatriation

(Egger et al., 2015) and higher payouts to shareholders (Arena and Kutner, 2015). Second,

the UK government gradually lowered the statutory corporate income tax rate from 28% in

2010 to 20% by 2015. The reduction in the statutory rate is a byproduct of the territorial tax

system reform and it is a measure to increase UK’s competitiveness. These two tax changes

9This means either a UK company or a UK permanent establishment of a non-UK company.10See the HMRC’s https://www.gov.uk/hmrc-internal-manuals/corporate-finance-manual/cfm90160 for

more detailed information.website.

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could have induced MNCs to reduce the amount of debt financing in the UK. However, the

territorial tax system reform and the tax rate reduction apply to all UK companies and are

not specific to a certain group of MNCs. In contrast, the 2010 worldwide debt cap targets

MNCs with exceeding debt holdings in the UK alone. Nevertheless, we examine the potential

confounding effects of these other tax changes in the robustness test section. There are also

other smaller tax policy changes in the UK, such as the Annual Investment Allowances

with the aim to stimulate business investment, and the corporate tax surcharge on banks.

However, these other tax changes should have little impact on MNCs’ debt policies.

3 Conceptual framework

To understand the potential impact of the WDC on MNCs’ debt policy, it is necessary to

first compare the cost of debt in the UK with that elsewhere. With full interest deductibility

for tax purposes, the cost of debt is the net-of-tax interest rate, i(1 − τ), where i is the

nominal interest rate and τ is the statutory corporate income tax rate. Between 2008 and

2014, the average UK interest rate was 2.58% and the average corporate income tax rate was

26.8%.11 Relative to the average of the other OECD countries, the UK had lower interest

rate and higher corporate tax rate.12 This implies that the average cost of debt in the UK

was 1.89%, which is below the average OECD one of 2.08%. This means that the UK was a

preferred location, at least among OECD countries, for holding debt for MNCs during our

sample period and, especially so, before the implementation of the WDC.

Under the WDC, for firms that failed the gateway test, the net-of-tax UK interest rate for

one additional pound of debt is simply i. This is higher than the net-of-tax UK interest rate

for firms that did not fail the gateway test. Also, it is likely to be substantially larger than

the net-of tax interest rate in other countries without interest deduction limitation, especially

those countries with a high statutory corporate income tax rate. Therefore, all else equal,

the direct effect of the WDC is that affected MNCs should lower their UK borrowing. If

debt shifting carries little costs, to offset the impact of the WDC on tax payments in the

UK, MNCs could reallocate debt elsewhere through its internal capital market so that the

overall tax payment of the group would be little affected. Since MNCs prefer to hold debt

11Data for tax rates comes from the OECD Tax Database and is the “statutory corporate income taxrate”. The interest rates come from OECD Monthly Monetary and Financial Statistics (MEI) and is theitem “short-term interest rate, percent per annum”.

12The average OECD interest rate was 2.74% and average corporate tax rate was 24%. This comparisonis even starker when we consider pre-reform year 2009, when net-to-tax cost of debt was 0.87 for the UKand 1.96 for the OECD countries.

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in high tax countries, the reallocation would likely flow in the same direction, if it was to

offset the effect of the UK tax reform.

The WDC can also lead to reallocation of real business activities. Assume that a firm’s in-

vestment at the margin is financed by a combination of equity and debt. Thus, the marginal

cost of capital is the weighted average of the cost of debt and the cost of equity. If the

WDC does not affect MNCs’ business risks, the marginal cost of capital for UK operations

should increase for affected MNCs for two reasons. First, the restriction on debt deductibil-

ity directly increases the net-of-tax cost of debt, because a fraction of debt is no longer tax

deductible. Second, the lower level of UK debt reduces the weight of debt relative to equity

capital for investment financing.13 In contrast, as the level of debt increases in non-UK sub-

sidiaries due to debt shifting, the marginal cost of capital should decrease in those locations.

This relative change in the cost of capital implies that capital should flow from MNCs’ UK

subsidiaries to non-UK ones, until the marginal return equals the marginal cost of capital in

both types of subsidiaries. If labour is complementary to capital, we should also observe a

flow of employment in the same direction.14

Further, with restrictions on interest deductibility, the sensitivity of investment towards

corporate tax rate would be substantially magnified.15 Hence, debt shifting induced by the

WDC may additionally negatively affect investment and employment of MNCs in the UK,

even though the UK government lowered the statutory corporate income tax rate after the

implementation of the WDC. Regulations such as the thin capitalization rules (TCRs), which

exist in many countries, may further reinforce reallocation of real business activities induced

by the WDC. For example, if a country implements a fixed debt-to-equity or debt-to-asset

ratio TCR, debt shifting to subsidiaries located in this country needs to be accompanied by

an increase in equity or total assets.

To offset the impact of the WDC, MNCs are especially likely to shift debt into subsidiaries

located in countries with a high corporate income tax rate. Whether capital and employment

would also flow to those high tax rate jurisdictions is worth further discussion. On one

hand, the lower net-of-tax cost of debt financing should induce capital and employment to

13The decline in leverage also lowers the cost of equity, but its overall effect on the weighted average costof capital is positive.

14Here, we assume that MNCs allocate resources in a rational way to maximize firm value. A streamof finance literature argues that MNCs may allocate resource among their establishments in an irrationalmanner. For example, Kruger et al. (2015) suggest firms use a single discount rate to to evaluate allinvestment projects across establishments.

15Buettner et al. (2012) consider the impact of thin capitalization rules on foreign direct investment, andthey show that the tax-rate sensitivity of FDI is about twice as large with limitation on interest deductibility.

9

flow to those locations. On the other hand, the high corporate income tax rate implies a

high user cost of equity capital, which may offset the attractiveness of these jurisdictions

as destinations for capital and labour. However, we consider this offsetting effect to be of

second-order importance for two reasons. First, when investment at the margin is financed

mainly by debt, a smaller part of investment return is subject to corporate tax and hence,

the corporate tax rate would have a smaller impact on investment (Buettner et al., 2012).

Second, if MNCs can shift profits across jurisdictions with different corporate tax rates to

minimize their tax burden, the income-shifting adjusted user cost of equity capital would be

much lower than the unadjusted one (Grubert and Slemrod, 1998; Mintz and Smart, 2004;

Serrato, 2018). This, in turn, should moderate the negative impact of the high corporate tax

rate on investment and employment. Hence, we expect to observe the reallocation of capital

and employment to be more prominent among MNCs’ non-UK subsidiaries facing a higher

corporate income tax rate.

4 Data and Empirical Strategy

4.1 Sample construction

To examine the effects of the WDC on MNCs’ debt and real activity allocations, we collect

data for a large sample of multinational parent companies matched with their subsidiaries.

Several data sources are utilized. First, we use Osiris by the Bureau van Dijk (BvD) to

extract a sample of MNCs with operations in the UK. The WDC only applies to “worldwide

groups” that own a relevant UK subsidiary. Thus, using ownership information from the

2010 Osiris, we require each MNC to own 75% or more shares of at least one UK subsidiary in

2010, when the WDC became effective. We exclude MNCs in the financial services industries

and firms with below 43m balance sheet total assets, because the WDC did not apply to

them. We then use the 2005-2014 CDs of Osiris to extract subsidiaries of those MNCs year

by year. We focus only on subsidiaries which are 50% or more owned and thus effectively

controlled, as they are more likely to be utilized for debt shifting purposes by MNCs. As

ownership structures of MNCs change frequently, our unique data allows us to have a more

precise picture of MNCs’ organizational structures during the period 2005-2014.

We obtain consolidated financial data for the MNC groups from Osiris. This allows us

to construct group-level variables such as consolidated worldwide gross debt and group size.

We obtain unconsolidated and detailed financial data for MNCs’ UK subsidiaries from the

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second database FAME. FAME allows us to construct MNCs’ UK net debt as close to the

HMRC’s definition as possible, but the data that we collected starts in 2008. Thus, this

reduces our ability to analyze longer pre-reform trends. Our benchmark sample that we use

to analyse the effect of WDC on UK debt and UK operations covers financial data for the

MNCs, both at the group level and the UK subsidiary level, during the period 2008 – 2014.

To analyze debt and real activity allocations between UK and non-UK subsidiaries, we

use the third database, Orbis, to obtain financial data for the MNCs’ non-UK subsidiaries.

We combine Orbis data with consolidated financial information from Osiris and with the

treated and control MNCs dummies generated in the FAME data. The sample we use to

consider debt and real activity reallocation is larger and covers years 2005 - 2014. Note that

FAME has a more detailed coverage of UK firms than Orbis, and Orbis does not contain

variables that allow us to calculate the gateway ratio close to the HMRC’s definition. This

is why we use FAME data for the first part of the analysis. Since FAME does not include

non-UK subsidiaries, we rely on Orbis for the second part of our analysis.

We calculate the gateway ratio, as outlined by the HMRC, for MNCs in our sample. An

MNC failed the gateway test, if its gateway ratio exceeded 75% in 2010. Note that both the

numerator and the denominator in the gateway ratio are two-year averages. Hence, the 2010

gateway ratio takes into account the 2009 financial data for the MNC. These MNCs form our

treatment group. Since the distribution of the gateway ratio for firms in our sample is rather

skewed towards the left, we take the logarithms of the ratio to make the distribution closer

to a normal one. In total, 197 MNCs in our sample failed the gateway test, 148 of which

are headquartered in the UK and the rest are headquartered elsewhere. MNCs that did not

fail the gateway test form our control group. For these 197 MNCs, we observe 1,176 unique

subsidiaries in the UK and 668 subsidiaries abroad for which we have financial data in Orbis.

Almost 50% of all foreign affiliates in our sample are located in European countries, such as,

France, Germany, Belgium, Italy, Spain, Norway and Sweden.

To account for the different characteristics of MNCs, we perform propensity score match-

ing. The reason why matching is important is that we want to compare the evolution of

debt and real business operations for a set of firms with most comparable characteristics

in 2010. If firms in treatment and control groups are very different from each other, we

would expect them to react to other concurrent events in different ways that are not re-

lated to WDC. Hence, in the robustness section we further evaluate the matching approach

by providing results using the unmatched sample, different matching methods and different

matching variables.

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Our control group MNCs are much smaller and represent a different set of countries

where the headquarters lie. Thus, we match MNCs by their global ultimate owners’ (GUO)

industries, location and group size. We apply the one-to-one nearest neighbor matching

algorithm without replacement. After matching, we obtain 188 MNCs that failed the gateway

test in 2010 and 188 MNCs that did not fail the gateway test.16 In Table 1, we provide

descriptive statistics for key variables for the treated and control groups before and after

matching. We show that matching significantly reduces differences in size, profitability,

gross debt and employment between treated and control groups. After matching, treatment

and control group MNCs are more comparable across most dimensions.

4.2 Who are the failed MNCs?

The 188 MNCs in the matched sample that failed the gateway test constitute about 12%

of all MNCs in the UK, and they own 13% of all UK subsidiaries in 2009. Before matching,

treated MNCs are smaller and less profitable compared with untreated MNCs. They hold

more total assets and employ more people in the UK. Specifically, they held 21% of total

assets and 17% of total employees in the UK among all MNCs in the sample. Treated MNCs,

on average, held $13.8 million in total assets in the UK and employed on average 4,987 people

in the UK (Table 1). Given the large sizes of the treated MNCs and their significant presence

in the UK, if the WDC affects real business activities, the impact on the UK economy will

not be trivial.

In Table 1, we describe the properties of key variables from the FAME data used in the

UK debt and real activities analysis in the year 2009. MNCs that failed the gateway test had

on average much lower worldwide gross debt, around $510 ($580) million, relative to $900

($2,700) million that control group had in the matched (unmatched) sample. In contrast,

treated MNCs had almost twice the amount of net UK debt relative to those in the control

group. It is worth noting that even after matching, treated MNCs had higher levels of UK

net debt and gateway ratios than the control group. While we cannot differentiate between

external and internal debt for the majority of UK subsidiaries, the average ratio of internal

debt in relevant UK assets is around 61% for a sub-sample of treated UK subsidiaries with

available information (around 50% of original sample). These statistics imply that treated

MNCs were very active in using their internal capital market, especially through debt, to

finance their subsidiaries.

16We do not find a match for every affected MNCs in our sample. For some MNCs, one or more matchingvariable is missing. We also failed to find any comparable for some treated MNCs.

12

In Table A1 we describe the properties of key variables used in the analysis of reallocation

of debt and real activities in the year 2009. Treated MNCs had a slightly lower UK ETR on

average than the control group before matching. After matching, this difference is no longer

statistically significant (Table 1). In Table A1 we show the average non-UK statutory CIT

rate faced by treated MNCs was 26.0% in 2009, while that faced by the control group was

25.4%. Within the treatment group, the average non-UK CIT rate faced by domestic MNCs

is 25.8%, while that faced by the foreign MNCs is 26.3%. This suggests that the treated

MNCs were exposed to a similar overall corporate tax burden to those in the control group.

MNC groups that failed the gateway test represent all industries. 121 of them are service

firms, 37 are in manufacturing, 18 are in wholesale, and the remainder is in miscellaneous

industries. The most represented industries are drug manufacturing industry with 16 MNC

groups, and computer programming and data processing services industry with 15 MNC

groups. There is also some geographical clustering in that the majority of the subsidiaries of

the treated MNCs are located in London (135 subsidiaries) with smaller clustering in other

major industrial cities in the UK, such as Wolverhampton (32), Leeds (12), Aberdeen (11),

Maidenhead (11) and Manchester (10).

4.3 Empirical strategy

We use the difference-in-differences approach to investigate the responses of MNCs to the

2010 UK worldwide debt cap. MNCs that failed the gateway test in 2010 are in our treated

group, while those that passed the test are in the control group. We adopt the difference-

in-differences approach instead of the regression discontinuity design for two reasons. First,

the reform disallows the excess interest deductions above the 75% threshold. This means

that firms just above the gateway threshold are less affected by the WDC rule than those

further away. Thus, this is not a discontinuity, but rather a kink. Second, we have very few

observations around the threshold. In the unreported exercises, we show that our results are

primarily driven by firms with gateway test ratios far above the threshold.

More specifically, to investigate the effects of the WDC on debt policies of MNCs as a

group, we use the following general specification:

Y UKi,t = α + β × Failedi × Postt + δ ×X ′

it + ηt + ψi + εi,t (1)

Where Y UKi,t is the outcome variable at the group level. We first consider the gateway

ratio, which is the natural logarithm of the ratio of the MNCs’ UK net debt and the con-

13

solidated gross debt17; Failedi is a dummy variable that equals one if MNC i failed the

gateway test in 2010, and zero otherwise; Postt is a dummy variable that equals one from

2010 onwards; X′it is a set of group-level control variables, such as group size, UK size and

UK profitability18; ηt is the time fixed effect, ψi is the group-specific fixed effect, and εi,t is

the error term. The parameter of interest is β, which captures the effect of the WDC on

MNCs’ UK gateway ratio. If the high levels of UK debt observed among affected MNCs, rel-

ative to their worldwide gross debt, are mainly tax-driven, we should observe a decline in the

gateway ratio after the implementation of the WDC. In this case, we expect the coefficient

β to be negative.

An MNC can reduce the gateway test ratio by reducing its UK net debt, or by increasing

its worldwide gross debt, or by a combination of the two adjustments. We therefore use the

net UK debt and worldwide gross debt (in logarithms) as outcome variables in Equation 1

separately. If a treated MNC reduced its UK net debt, the coefficient β should be negative.

Analysing changes in MNCs’ UK net debt also informs whether the WDC achieved its

intended goal of reducing MNCs’ excess interest expenses in the UK, mainly via the use of

internal debt. One criticism of the “worldwide approach” as an anti-debt shifting measure is

that it may lead to a higher level of external borrowing. If the WDC did lead to an increase

in external borrowing by the MNCs as groups, we should estimate a positive β when the

dependent variable is MNCs’ worldwide gross debt.

We further use this framework to study the effects of the WDC on MNCs’ tax payments

and real activities in the UK. To examine changes in total UK tax payment, we use the

natural logarithm of total tax paid to the UK tax authority, which is obtained by aggregating

tax payment across MNCs’ UK subsidiaries, as the dependent variable. We use three proxies

for MNCs’ UK operation, total assets, fixed assets and employment (number of employees),

all are aggregated across UK subsidiaries and expressed in logs.

To understand the pattern of debt and real activity reallocation outside of the UK, we

use subsidiary-level data from Orbis and estimate Equation 2:

Y nonUKi,j,s,t = α + β × Failedi × Postt + δ ×X ′

i,j,s,t + ηt + ψi + εi,j,s,t (2)

17Note that using the logarithm function means that we set all the negative and zero values of net debtto missing. We have experimented with specifications in levels and tried using logarithm of 1 plus level.The results remain significant using those various specifications. Hence, for consistency purposes acrossspecifications we use the log transformation.

18In the robustness section we discuss the choice of these controls and show how our results are robust toincluding more control variables.

14

where Y nonUKi,j,s,t is the outcome variable for non-UK subsidiary j that belongs to multinational

i, located in host country s in year t and X′i,j,s,t is a set of subsidiary and group-level control

variables, such as group size, subsidiary size and subsidiary profitability. In these regressions

we also control for country-year specific fixed effects. This ensures that we account for

cross country differences between locations. To investigate debt shifting following the WDC,

we use non-UK subsidiaries’ net-of-cash leverage ratio as the outcome variable in Equation

2.19 In this specification, debt-shifting induced by the WDC would be consistent with a

positive estimate for β. To understand whether debt shifting is tax sensitive, we interact

Failedi × Postt with the statutory corporate income tax rate that the non-UK subsidiary

j faces in year t in country s CITjst. Most likely, the affected MNC would shift debt to

a subsidiary facing a high corporate income tax rate. In this case, we expect the estimate

coefficient on the interaction between CITjst and Failedi×Postt to be positive. To examine

the effects of the WDC on non-UK subsidiaries’ tax burden and real activities, we use

additional outcome variables in Equation 2. These include the non-UK subsidiaries’ tax

payment, the level of total assets, fixed assets, and number of employees (all in logs).

5 Results

5.1 Graphical evidence

We first present graphical evidence summarizing the evolution of key debt related vari-

ables around the time of the WDC reform. Figure 1 plots one year averages for net UK

debt, worldwide gross debt and the ratio of the two across all firms together with confidence

intervals for the treated and the control groups during the period 2008-2014, controlling for

industry fixed effects. Here, we opt for one year averages, which allows us to include an

additional pre-reform year to evaluate the parallel trends assumption.

In Figure 1a we show that there were no substantial changes in the ratio of net UK debt

to worldwide gross debt ratio before the reform. However, the treated MNCs reduced the

ratio in 2011 and then again substantially in 2013. In contrast, MNCs in the control group

did not experience a significant change in their test ratios throughout the post-2010 sample

period. Note that despite the WDC, treated MNCs still have a higher gateway ratio than

the control group in 2014. There might be a couple of reasons for this. First, it may take

19Note that Orbis dataset does not include all the variables used by the HMRC to calculate net UK debt.Hence, our analysis for non-UK subsidiaries using Orbis data will be restricted to considering leverage andmay not precisely match the results for the UK.

15

time to adjust external borrowing, given the fixed borrowing terms set in the contract with

a third party. Second, some of the internal borrowing may not be for tax avoidance purposes

but for real financial considerations.

We plot the natural logarithms of average UK net debt and worldwide gross debt respec-

tively in Figures 1b and 1c. First, MNCs that failed the gateway test had on average more

UK net debt and less worldwide debt than MNCs that did not fail the test. These figures

show that treated MNCs reduced their UK net debt gradually after the 2010 reform, while

the control group kept a stable level of UK net debt. There is a parallel trend in MNCs’

worldwide gross debt until 2010. While affected MNCs increased their worldwide gross

debt significantly during 2011-2014, unaffected MNCs’ worldwide gross debt has grown at

much slower rate. Overall, Figure 1 provides graphical evidence that the WDC significantly

changed the debt holdings of multinationals that used to hold high level of debt in the UK,

relative to their worldwide external debt.

In Figure 2, we distinguish between domestic and foreign MNCs. Figures 2a and 2b

present domestic MNCs while Figures 2c and 2d report foreign MNCs. In each of those

figures, we compare treatment and control MNCs belonging to the same category. Both

types of MNCs that failed the gateway ratio test reduced the UK net debt relative to the

control group. The downward adjustment in the UK net debt is more prominent for foreign

MNCs. Affected domestic MNCs did not significantly change their worldwide debt after

2010 relative to industry means (Figure 2b). In contrast, affected foreign MNCs sharply

increased their worldwide debt since 2011, while the control group maintained a relatively

stable level of worldwide debt. Figure 2 provides first evidence that domestic and foreign

MNCs responded to the worldwide debt cap in different ways.

5.2 Impact of the WDC on MNCs’ debt policies

5.2.1 Gateway ratio, UK net debt and worldwide gross debt

Table 2 reports the estimated effects of the WDC on MNCs’ gateway ratio, UK net debt,

and worldwide gross debt based on Equation 1, using the matched sample. In each speci-

fication, we control for MNCs’ group size proxied by the natural logarithm of consolidated

group-level total assets, as well as the size and profitability of MNCs’ UK subsidiaries. We

include a common set of year dummies to control for business cycle effects in each specifi-

cation. In the odd numbered columns, we control for industry-specific fixed effects, while

in the even numbered columns we control for group-level fixed effects. In Columns 1 and 2,

16

the dependent variable is the logarithm of the gateway ratio. Estimated results in Column 1

confirm that before the reform, treated MNCs had a significantly higher gateway ratio than

the control group. The gateway ratio of an average treated MNC dropped by around 33 per-

cent following the WDC.20 Controlling for group fixed effects in Column 2, we continue to

find that treated MNCs significantly reduced their gateway test ratio relative to the control

group after the reform. Based on Column 2, MNCs that failed the gateway test on average

reduced the gateway ratio by about 29 percent.

We focus on the amount of UK net debt (in logs) in Columns 3 and 4. Column 3 shows

that the pre-WDC level of UK net debt is significantly higher for the treated MNCs, and

it was substantially lowered following the WDC. Similar results are obtained in Column 4

with group-specific fixed effects. The reduction in UK net debt is large: the coefficient of

-1.35 implies a reduction in the net UK debt of 74% of the pre-reform level for treated MNCs

relative to the control group based on Column 4.21 In unreported exercises, we find that

this reduction in UK net debt was mainly driven by a reduction in MNCs’ relevant liabilities

rather than a change in relevant assets.

Columns 5 and 6 reveal that the WDC also caused treated MNCs to raise their gross

debt relative to the control group, consistent with the evidence from Figure 1c. In both

columns, the point estimates on the interaction term between Failedi × Postt are positive

and statistically significant and Column 6 implies the increase in the logarithm of gross debt

of 37.5 percent for the treated firms. This result supports the criticism that the WDC would

encourage MNCs to increase external borrowing.22

Figure 2 suggests that domestic and foreign multinationals responded differently to the

WDC. To formally test this, we split the sample into two sub-samples: UK headquartered

MNCs (i.e., domestics MNC) and non-UK headquartered MNCs (i.e., foreign MNC). We

report the estimated treatment effects in Table 3. Throughout Table 3, we control for

group-specific fixed effects, a common set of year dummies and group-level characteristics

as in Table 2. While both domestic and foreign affected MNCs significantly reduced their

gateway ratio relative to the control group, this adjustment is achieved in slightly different

ways. The affected domestic MNCs reduced their UK net debt by 79 percent (Column 3),

with a 28.5 percent increase in their worldwide gross debt (Column 5). In contrast, foreign

MNCs reduced their UK net debt by 63 percent (Column 4) but increased their worldwide

20With β of -0.406, one-unit change in x is associated with an exp(-0.406)-1=-0.333 change in y.21With β of -1.35, one-unit change in x is associated with an exp(-1.35)-1=-0.74 change in y.22In unreported analyses, we find that the increase in gross debt is mainly driven by increasing private

borrowing rather than public borrowing.

17

gross debt by 64 percent (Column 6). The differences between the domestic and foreign

multinationals are also statistically significant with p-values of 0.012 and 0.000, respectively.

What may explain this heterogeneity? Note that the worldwide debt consists of external

borrowing from third parties. Companies tend to borrow externally using the headquarter

(Kolasinski, 2009) 23 rather than their affiliates. This is because headquarters usually have

higher credit rating than affiliates and hence are more able to obtain financing with most

favourable terms. Under this situation, a foreign MNC can complement the reduction of its

UK net debt by increasing external debt elsewhere, possibly with a low level of adjustment

costs. In contrast, domestic MNCs are relatively limited in reducing their gateway ratios

by borrowing more externally in the UK, since doing so would increase their UK net debt.

While domestic MNCs can borrow externally via foreign subsidiaries, the cost of doing so is

likely to be higher.

In Figures 3 and 4 we plot the difference-in-differences coefficients from estimating a

dynamic version of equation 1. Instead of using Postt dummy to indicate all periods after

the reform, we interact Failedi with year dummies for each year separately to see how

the gateway test ratio, net UK debt and worldwide gross debt changed year by year. All

coefficients are plotted relative to 2009, the year before the reform went into effect. Figure

3a and 3b suggest that the reductions in gateway test ratios and net UK debt were gradual

as both were falling for the treated group until 2014. Figure 3c indicates that the change in

worldwide gross debt was quicker, as most of it occurred in 2011, just one year after the reform

went into effect. After 2011, the evolution path for the difference in the worldwide gross

debt between treatment and control groups is quite flat, indicating there was no downward

adjustment back.

In Figure 4, we distinguish between domestic and foreign MNCs. Figures 4a and 4b

present dynamic regression coefficients for domestic MNCs, while Figures 4c and 4d report

those for foreign MNCs. In each of those figures, we compare treatment and control MNCs

belonging to the same category. Here, we observe a gradual decline in net UK debt for

both domestic and foreign treated MNCs after 2010. However, this downward adjustment

was more substantial among treated foreign MNCs. In Figures 4b and 4d we observe that

domestic and foreign MNCs adjusted their worldwide debt differently. While both types of

treated MNCs adjusted their gross debt upward relative to 2009, such increase was again

more prominent for treated foreign MNCs. For these MNCs, their gross debt was increased

23Kolasinski (2009) documents that subsidiary debt issues account for around 13% of total US non-financialcorporate debt proceeds. As mentioned in (Kolasinski, 2009), SP’s suggested that “a strong subsidiary ownedby a weak parent is generally rated no higher than the parent”.

18

sharply in 2011 and then again in 2013 (Figure 4d). .

5.2.2 Debt reallocation across subsidiaries

To offset the impact of the WDC, an affected MNC can reallocate debt across affiliates

via its internal capital market. In this section, we examine this. First, since only subsidiaries

at least 75% owned by the MNC are considered “relevant” in the gateway test, MNCs that

failed the gateway test could reallocate debt from the 75% owned UK subsidiaries to UK

subsidiaries that are less than 75% owned. In unreported exercises, we find a positive effect

of the WDC on the leverage ratio of the 50%-75% owned UK subsidiaries owned by the

affected MNCs relative to that of those owned by unaffected MNCs. However, this effect

is not statistically significant. The reason for this result may be twofold. First, the sample

of 50%-75% owned UK subsidiaries is rather small and consequently, the coefficient may be

estimated imprecisely. Second, reallocating debt to subsidiaries within the UK may bring

smaller benefits to affected MNCs than moving debt to more tax advantageous location

outside of the UK, which is especially true considering the UK significantly lowered its

corporate income tax rate soon after the WDC.

Since the WDC raised the cost of debt in the UK, MNCs were likely to shift debt to

non-UK subsidiaries to minimize their overall tax burden. If this is the case, we expect the

leverage ratio of the affected MNCs’ non-UK subsidiaries to increase on average. Further, this

increase in the leverage ratio should be more substantial in subsidiaries located in countries

with higher corporate income tax rates. We test these hypotheses by estimating Equation

2 where the dependent variable is the net-of-cash leverage ratio of each non-UK subsidiary.

The results are reported in Table 4. Throughout all columns in Table 4, we control for

common business cycle effects, and subsidiary-specific fixed effects. In Columns 1-4, we use

the sample of all MNCs’ subsidiaries. In Column 1, we estimate Equation 2 without adding

any control variables. We find that on average the leverage ratio of affected MNCs’ non-UK

subsidiaries increased by 18.6% after the WDC relative to the control group. Controlling for

subsidiaries’ size and profitability, group size (Column 2) and host country-year fixed effects

(Column 3), we obtain the same result. Column 3 suggests that the leverage ratio of affected

MNCs’ non-UK subsidiaries increased by around 13.6% following the WDC.

Next, we multiply Failedi × Postt by each host country’s statutory corporate income

tax rate.24 Result based on this specification is reported in Column 4. The point estimate

24We obtain each host country’s statutory corporate income tax rate from the Oxford University Centrefor Business Taxation.

19

for Failedi × Postt × CITjst is positive and statistically significant at the 1 percent level.

This suggests that affected MNCs shift more debt into non-UK subsidiaries facing a higher

corporate income tax rate. The coefficient of 0.522 means that leverage increased by 22

percent in non-UK subsidiaries with a tax rate of 40 percent.

We repeat the estimations based on the specifications in Columns 3-4 using the sub-

sample of subsidiaries that belong to domestic MNCs (Columns 5-6), and the sub-sample of

subsidiaries that belong to foreign MNCs (Columns 7-8). We find that both types of MNCs

shift debt to their non-UK subsidiaries following the WDC, in particular to host countries

with a higher tax rate. However, the estimated extent of debt shifting is much larger for

foreign MNCs. For domestic MNCs, while we also find evidence of debt shifting, the extent is

roughly half of that of foreign MNCs. This is unsurprising, as some of the non-UK affiliates of

the foreign MNCs are located in the MNCs’ headquarter countries. Therefore, these non-UK

affiliates can use external debt to adjust their leverage as we discussed previously.25

5.3 Reallocation of real activities

We have established that the WDC led to debt shifting across affiliates by affected MNCs.

An important question that has been rarely asked previously is whether anti-tax avoidance

measures also trigger reallocation of real business operations. We first explore whether the

WDC prompted MNCs to adjust their operations in the UK, due to an increased cost of

capital as our conceptual framework indicates. To proxy for the size of UK operation, we use

three indicators: total assets, fixed assets, and employment (all in logs), aggregated across

all UK subsidiaries.26 We chose these three variables, because they reflect the adjustment

in business operations. The reason why we do not analyse investment directly is because

that information is not reported in either Fame or Orbis data. Using the growth rate of

fixed assets will not reflect the true investment, due to the fact that BvD reports fixed asset

figures net of depreciation and asset disposal.

Estimation results using these indicators as the dependent variable in Equation 1 are

reported in Table 5. We find strong evidence for shrinking UK operation by all affected

MNCs (Columns 1-3), controlling for MNCs’ group size. However, this is mainly driven

by foreign MNCs. We find that affected foreign MNCs reduced their total assets by more

25We test for this by interacting the Failedi × Postt dummy with a dummy indicating that an affiliate islocated in the same country as the foreign MNCs headquarter. The estimated coefficient on that interactionterm is large in magnitude and statistically significant in a specification similar to that in Column 3 in Table4

26We obtain similar results using UK subsidiary-level data.

20

than a third (Column 7). While changes in total assets may include the change in debt, we

examine the fixed asset and find a similar reduction in foreign MNCs’ fixed assets in the

UK. There is also an 11 percent reduction in the UK employment by affected foreign MNCs,

which is statistically significant at the 1 percent level. These effects are large, but they are

accumulated since 2010, which implies an average reduction in fixed assets of about 6% each

year and 2% average annual adjustment in employment. In contrast, while we find a negative

impact of the WDC on affected domestic MNCs’ UK operation, the point estimates are not

statistically significant. This result may be related to a strong home bias for real business

operations despite a higher cost of capital following the WDC. This is consistent with the

fact that a typical domestic treated MNC in our sample held around 81% of its total assets

in the UK, while a foreign one held only 42% (Table A1).

In Table 6, we examine changes in MNCs’ non-UK operations. Panel A considers the

effects averaged across all non-UK subsidiaries. We do not control for group size in Table

6 since we find a strong collinearity between group size and non-UK operation size for for-

eign MNCs. For domestic MNCs, controlling for group size does not materially change the

estimated coefficients. For both domestic and foreign MNCs, we find a significant expan-

sion of their non-UK operations. The percent increase in non-UK operations of domestic

MNCs is marginally smaller than that of foreign MNCs for total and fixed asset measures.

However, the difference between the two is not statistically significant. The effect of WDC

on employment is significantly larger for foreign MNCs than for domestic ones. In Panel

B, we interact Failedi × Postt with host countries’ statutory corporate income tax rate.

Consistent with our theoretical argument, we find that more capital and employment were

reallocated to countries with a higher tax rate, as the estimated coefficient on the interaction

term is positive and statistically significant.27 These results suggest that reallocation of real

business activities in response to the UK’s anti-tax avoidance rule is in the same direction

as that of debt.

Our estimates of the effects of WDC on real operations can be converted into aggregate

magnitudes. Using our average estimates and back of the envelope calculations, we show the

extent to which the reform affected the overall business activities of MNCs in the UK and

in foreign countries. Affected foreign MNCs held $32.1 billion in total assets, $15.1 billion in

fixed assets and employed 35,966 people in the UK during the pre-reform years (see Panel A

Table A1). Based on the estimates in Columns 7-9 in Table 5, the WDC led to a reduction

27Similar to results from Table 5, results from Table 6 can be aggregated to parent-foreign country ofoperation-year level. Results from this aggregation show the same pattern as observed in Table 6

21

in their UK total assets by 10.7 billion, in fixed assets by 5.5 billion and in loss of 4,064

job positions by 2014. Affected foreign MNCs held a total of 54.6 billion of dollars in total

assets, 39.4 billion in fixed assets and employed 49,178 people in their non-UK subsidiaries

during the pre-reform years (see Panel B Table A1). Based on estimates in Table 6, the

increase in business operations in non-UK subsidiaries of foreign MNCs was 12.5 billion, 6.9

billion and 11,463 in those respective categories by 2014. Since most of foreign subsidiaries

in our sample are located in high tax European countries, such as France, Germany or Italy,

our results suggest reallocation assets and labour towards high tax European countries.

We find that domestic MNCs did not significantly change their UK operations, but

expanded outside of the UK. Affected domestic MNCs held 279 billion of dollars in total

assets, 214 billion in fixed assets and employed 148,681 people in their non-UK subsidiaries

in 2009. Based on the estimates in Table 6 and statistics from Panel A in Table A1, the

WDC led to an increase in business operations in non-UK subsidiaries of domestic MNCs by

59 billion, 29.5 billion and 10,500 respectively for total assets, fixed assets and the number of

employed people by 2014. One reason for this may be that the WDC may have discouraged

domestic firms from expanding their activities in the UK. Instead, those firms chose to

expand abroad. This would explain the increase in their real business operations abroad

without significant change to their UK operations.

Our analysis indicates unintended consequences of anti-tax avoidance measures on real

business activities, which has not been widely discussed in the literature before. Unlike

Serrato (2018) who finds that the anti-tax avoidance measure led to business activity reallo-

cation away from the US by US MNCs, we do not find that the WDC significantly reduces

domestic MNCs’ home operations. One possible explanation for this difference may be that

the MNCs headquartered in the US have weaker home bias than the MNCs headquartered

in the UK. Using aggregate BEA statistics, we find that US MNCs hold about 57% of their

total assets in the US in 2017, while UK MNCs in our sample held close to 81% of their total

assets in the UK in 2010. This does suggest substantially lower home bias for US MNCs and

explains why our results differ from Serrato (2018).

MNCs may also adjust their organizational structures as a more aggressive response to

offset the impact of the WDC. The gateway test requires calculating the UK net debt ratio

using relevant UK subsidiaries. Hence, if a relevant subsidiary had a high level of UK net

debt, an MNC can reduce share holdings of this UK subsidiary to exclude it from the gateway

test. A more extreme response would be to completely sell or shut down this UK subsidiary

and perhaps to acquire new affiliates elsewhere. If we assume that debt shifting to existing

22

non-UK subsidiaries may violate thin capitalization rules in the host countries, setting up

new subsidiaries there may also be a way to circumvent the regulation.

Changes in the organizational structure have rarely been examined in the previous stud-

ies for two reasons. First, organizational structure adjustment is more costly than simple

debt and real business activity reallocation across existing subsidiaries. Hence, it has been

considered to be less likely to occur in response to a tax reform. Second, time-varying own-

ership structures of the MNCs are required to conduct such an analysis. Our unique data

permits us to do this novel test. In particular, we estimate the effect of the reform on the

time-varying percentage of relevant UK subsidiaries that belong to group in the MNC’s total

number of subsidiaries.28 To facilitate debt shifting, a group may also increase the number

of subsidiaries located in high tax countries, which is reasonable considering thin capital-

ization rules imposed on each subsidiary. We therefore use the percentage of subsidiaries in

high (low) tax countries as the dependent variable to examine organizational changes in this

dimension.

In Column 1 in Table 7,29 we calculate the ratio of controlled UK subsidiaries relative to

all of MNC’s controlled subsidiaries (%UK 50+). In the difference-in-differences estimation,

we do not find that affected MNCs reduced the percentage of UK subsidiaries. In Column

2, we use the percentage of relevant UK subsidiaries relative to MNC’s total number of

subsidiaries as the dependent variable (%UK 75+). We find weak evidence that MNCs

reduced the share of relevant UK subsidiaries, suggesting some adjustment at this margin.

In Columns 3 and 4, we consider the ratio of non-UK subsidiaries located in countries with

a higher or lower statutory corporate tax rate than that in the UK. We show that treated

MNCs increased the fraction of their subsidiaries located in higher tax regimes by 4.2 percent

and reduced the fraction of subsidiaries located in lower tax regimes by 3.7 percent. These

changes are statistically significant in 1 percent level. Taken together, these results suggest

that affected MNCs did restructure their subsidiaries in response to the WDC, in addition

to the intensive-margin adjustments in real business activities.

28Note that we do not analyze the absolute number of multinational subsidiaries. This is because therehas been a change in the way that Orbis records subsidiaries during our sample period.

29Note that we use all multinational groups with at least one relevant subsidiary in the UK in 2010 andtrace them across the 10 years sample period here, 2005 – 2014. Using the much smaller (220 groups)matched sample yields negative but insignificant point estimates.

23

5.4 Impact of the WDC on MNCs’ tax burden

The purpose of the WDC was to raise tax revenue in the UK. Therefore, we investigate

whether this has been achieved. Moreover, it is possible that the WDC had a spillover effect

on other countries’ tax revenue due to debt and real business reallocation. We start with

the question whether the WDC increased MNCs’ tax payments to the UK tax authority.

We aggregate the tax payments across all UK subsidiaries of each MNC.30 Then, we use the

natural logarithm of MNCs’ total UK tax payment as the dependent variable in Equation

1. We report the estimated results in Panel A in Table 8. We find that following the WDC,

the UK tax payments of domestic MNCs increased by 25% (Column 2).31 In contrast, the

UK tax payments of foreign MNCs did not significantly change (Column 3). This result is

less surprising considering that foreign MNCs shrank their tax base in the UK. Thus, the

WDC did achieve the goal of raising tax revenues to the HMRC, but only from domestic

MNCs. Our results are consistent with Miller (2017) who shows that anti-tax avoidance

policies, especially those related to interest deductibility restrictions, are the only recent UK

tax policy leading to positive revenues to the HMRC. In our sample, domestic MNCs in

2009 had around 2.3 billion pounds of positive tax liability in the UK. A 25% increase in

tax liability for the affected domestic MNCs would lead to 575 million pounds increase in

tax liability.32 Miller (2017) suggests that UK has gained 1.2 billion pounds from all of the

anti-avoidance measures announced between 2010 and 2015. Our estimates are well within

her calculations.

As affected MNCs shift debt away from the UK and increase debt in non-UK affiliate,

the WDC may have spill-over effect on other countries’ tax revenue. In Panel B of Table

8, we test whether the WDC affected the tax burden for non-UK subsidiaries of affected

MNCs. Throughout different columns of Table 8, we find no effect for subsidiaries of either

domestic or foreign MNCs. It appears that domestic MNCs did not offset the tax hike in

the UK by reducing tax payment abroad. For foreign MNCs, results in Table 8 suggest that

the WDC did not affect their tax burden either in the UK or elsewhere. These results are

30Results using UK effective tax rates (ETRs) as a dependent variable are similar.31The UK corporate tax revenues as reported by the HMRC have increased from GBP 30.8 billion in

2009/10 to GBP 35.3 billion in 2010/2011 (excluding revenues from North Sea oil companies). The HMRCdoes not report the breakdown of corporate tax receipts by ownership type of companies. Evidence fromBilicka (2019) suggests that net tax payments of multinational firms has increased between the two tax years.

32The additional tax revenue for the period 2010- 2014 should equal to (total UK net debt in 2009) x(average interest rate in 2009-2014) x (reduced UK net debt: coefficient from column 4 Table 2) x (averagetax rate in 2009 -2014). These are 1.5 billion, 0.78, -1.35, 0.25, respectively, which gives 400 million. Theseresults are in line with the regression estimates, especially since here we assume the short-term interest rateis the same for everyone, which would not be true in reality.

24

perhaps less surprising, since we find that foreign MNCs reallocated real activities away from

the UK, which implies a larger tax base in other countries. This, in turn, should have offset

the negative impact of debt shifting on MNC’s tax liability outside of the UK.

Our analysis suggests that the UK’s new anti-tax avoidance policy may have created

competitive disadvantage for domestic MNCs. As domestic MNCs had fewer options to

circumvent the WDC, their overall tax burden increased. In contrast, affected foreign MNCs’

worldwide tax liability was unaffected. This is another unintended consequence of the WDC.

5.5 Potential threats to our identification strategy

In this section we discuss several potential threats to our identification strategy and

what we do to reduce possible bias coming from those. Several factors may challenge our

identification, including the 2008 financial crisis, the UK corporate tax rate cuts and the

territorial tax system reform. Our difference-in-differences research design helps alleviate

these concerns to some extent, because each of those events, in principle, affects all MNCs in

the UK. However, each of those events might potentially have a larger effect on our treated

group – highly leveraged firms – than on our control group.

First, if firms in our treated group –those with higher debt ratio – were exposed to higher

financial distress risks, they could have reduced debt more than the control group following

the financial crisis in 2008. As shown in Table 1, the average worldwide debt of treated

MNCs is actually smaller than that of the control group. Therefore, it is unlikely that the

MNCs that failed the gateway ratio test had higher default risks. In addition, the financial

crisis occurred in 2008, but we do not observe any changes in the treated MNCs’ gateway

ratios, net UK debt and worldwide debt until 2011 (see Figure 1a). The gateway test ratio

for the treated group actually peaks in 2010. This is another reason why the 2008 financial

crisis is unlikely to confound our estimated treatment effect.

The second potential confounding factor is the declining corporate income tax rate in

the UK, which reduces the attractiveness of debt financing, all else equal. The initial UK

corporate tax cuts package was announced in 2007 to reduce the tax rate from 30% to 28%

effective in April 2008. In 2009 the UK has announced additional tax cut to lower the rate

to 20% by 2015. These tax cuts have later been extended. The tax rate cut may have a

larger impact on treated MNCs, if the UK had a relatively higher tax rate than that faced

by their non-UK subsidiaries before these tax cuts. To address this concern, we calculate

the average non-UK statutory corporate income tax rate for MNCs in our sample. We find

that the average non-UK CIT rate was 26.0% and 25.4% in 2009 for treated and control

25

MNCs, respectively. Therefore, the UK should have been an equally attractive destination

for debt for both types of MNCs before the WDC, and the UK tax rate cut should have

similar impact on debt financing considerations by the two types of MNCs.

A related concern is that firms in our treated and control groups could be different in

terms of their effective tax rates and profitability in the UK. If this is the case, they were

likely to react differently to the corporate tax rate cuts in the UK. For example, if treated

MNCs had higher effective tax rates and profitability in the UK than the control group, the

cut in the UK statutory rate may generate more tax savings for them. If MNCs use tax

savings to substitute for debt financing, we should observe treated MNCs to reduce debt

more than the control group. However, evidence from Table 1 suggest that in our matched

sample the UK ETR in 2009 was 15% for treated firms and 14.4% for control firms. These

were not statistically significantly different from each other. Also, treated and control groups

in the matched sample had similar levels of UK profitability. This suggests that the treated

and control MNCs should not in principle differ in terms of their response to corporate tax

rate cuts. As a further check, we conduct a robustness test in which we match treated and

control groups based on their UK effective tax rates and profitability. This, however, does

not affect our main result.

The third potential confounding factor for our results is the UK’s transition from the

worldwide to the territorial tax system in 2009. The territorial tax system reform encouraged

MNCs to repatriate dividends from overseas. Consequently, the UK parents may switch

away from debt financing, as they now receive more repatriated profits. It is possible that

MNCs with more UK debt holdings faced more frictions before the territorial tax system

reform (that is, it was more costly for them to repatriate profits before 2009) and hence, the

territorial reform would have a larger impact on these MNCs than those with a lower level of

UK debt. To be consistent with the conjecture, the former type of MNCs should repatriate

more dividends following the territorial tax system reform.

We thus compare the dividend repatriation patterns between the treated and control

groups in Table 9. Since the territorial reform should mainly affect domestic MNCs, we use

this subsample for the comparison. In Column 1 of Table 9, the dependent variable is the

total dividends received by UK subsidiaries. In Column 2, the dependent variable is dividends

paid out by the MNCs’ non-UK subsidiaries. In these columns, we find no difference between

affected and non-affected MNCs. Therefore, any substitution between debt and repatriated

profits as a way to finance investment projects should be similar between the treated and the

control groups. This result should further reduce the concern that the territorial tax system

26

reform may confound our difference-in-difference estimation results.

More, the territorial tax reform should have had smaller impact on foreign MNCs. It

is thus reassuring that we see stronger effects for foreign MNCs in terms of both debt and

real operation reallocation. This suggests that our results are unlikely to be driven by the

territorial tax reform concerns.

5.6 Robustness tests

We further conduct a host of robustness tests to examine whether our results are sen-

sitive to the matching method, matching set of variables or control variables included in

the specifications. First, we compare results with and without matching, and those using

different matching methods. In Appendix we provide baseline results analogous to those

in Table 2 when we use the unmatched full sample (Table A2) and a sample matched by

the alternative kernel matching technique (Table A3). Results are broadly similar based on

these alternative samples. Note, however, that the coefficients in Table A2 are much smaller

than those in Table 2.

Second, in Table A4, using the benchmark one-to-one nearest neighbourhood matching

method, we consider how using a different set of matching variables changes our main result.

In all specifications we match the treated and the control groups on the MNCs’ GUO industry,

location and size in 2010, as we did previously. Here, we extend the set of matching variables

to include MNCs’ UK profitability (Column 1), UK effective tax rates (UK ETRs) (Column

2), the ratio of UK total assets to the group total assets (Column 3), the difference in UK

total assets between 2008 and 2009 (Column 4), the difference in MNCs assets between 2008

and 2009 (Column 5) and finally, all of these together (Column 6).

The inclusion of UK profitability, UK ETRs, and the size of the UK operations relative

to the MNCs’ worldwide operations allows us to match on potential firm characteristics that

could confound our previous results. Specifically, matching on UK profitability and ETRs

helps us address concerns that our treatment and control groups may be different when it

comes to tax aggressiveness, and consequently may have been affected by the UK corporate

tax cuts differently. Matching on the relative size of MNCs’ UK operations addresses the

concern that the treated and control groups may have different exposure to the UK and

hence, may respond differently to the UK’s anti-tax avoidance measure. Further, matching

on the difference in UK and MNC total assets between 2008 – 2009 allows us to address

concerns about differential pre-trends between treatment and control groups. Results from

Table A4 suggest that changing the set of matching variables does not significantly affect

27

either the magnitude or the statistical significance of our main results.

Third, prior studies examining debt policies of MNCs may include additional control

variables, such as dividend payments, RD, depreciation, market-to-book, effective tax rates,

and more (Faulkender and Smith, 2016). To check whether our results are different when

we use alternative controls, in Table A5 we include dividend payments, MNCs’ UK and

overall ETRs, and their market capitalization. Inclusion of these controls limits the sample

size substantially, especially when we control for market capitalization. Nevertheless, the

majority of our results still hold, with some coefficients loosing significance possibly due to

the shrinking sample size .

Further, to attenuate the problem that the levels of debt between the treated and control

groups are rather different, we include firms with gateway test ratios of 0.5 and above in

the control group. This does not change our benchmark results and we do not report these

results for a succinct presentation. Finally, we test whether our results are driven by the

MNCs closer to the 75% gateway threshold or those further away from it. As mentioned

in the empirical design strategy, MNCs just above the 75% gateway ratio may not find it

worthy to relocate debt since the tax saving of doing so would be small. This also explains

why the regression discontinuity design is not appropriate in our setting. In contrast, those

further away from the 75% gateway test ratio might have greater incentives to adjust their

debt policies. We compare the effect of the reform for firms with gateway test ratio below

90% to those with the ratio above 90%. Consistent with our hypothesis, we find that the

results are mainly driven by firms with very large gateway test ratios.

6 Conclusions

Tackling debt shifting for tax avoidance purposes by multinational firms is high on the

agenda of many national governments. In this paper, we analyze how a new form of debt-

related anti-tax avoidance policy affects multinationals’ debt and real activities allocations.

We use the UK worldwide debt cap reform in 2010 as a quasi-natural experiment, which

restricted the MNC’s interest expense deductions for tax purposes in the UK to be below a

fixed ratio relative to the MNC’s worldwide debt holdings. Unlike the widely adopted thin

capitalization rule, the worldwide approach should be more difficult to circumvent and thus,

should have a more substantial effect on earning stripping by MNCs. We provide causal

evidence for a negative and substantial effect of the UK worldwide debt cap on MNCs’ debt

allocation across subsidiaries. While the anti-tax avoidance policy was effective in curbing

28

excessive borrowing in the UK, one unintended consequence is an increase in multinational

groups’ external debt. This could possibly affect firms’ credit risk. We leave this to future

research.

The worldwide debt cap also led to reallocation of real activities among affected foreign

MNCs. We show that affected multinationals shrank their business operation in the UK,

while expanding it elsewhere. This has further offset the amount of potential tax revenue that

could have been raised from foreign MNCs as a result of the WDC. Our findings contribute

to the growing literature on how anti-tax avoidance measures may affect real economic

activities. Combining the effects of the anti-tax avoidance policy on debt holding and real

activities, we find that the worldwide debt cap allowed the UK tax authority to collect more

tax revenue, but only from domestic MNCs.

Finally, our analysis has broader implications for implementing anti-tax avoidance mea-

sures without international cooperation. We show that this may have unintended conse-

quences on MNCs operations that go beyond debt reallocation. The WDC lead to reallo-

cation of debt and real business activities away from the UK, especially for foreign MNCs.

Hence, it imposed an additional tax burden on domestic MNCs relative to foreign MNCs.

Such unilateral moves may be harmful to domestic MNCs, as they may lose their competitive

advantage relative to foreign MNCs, if the tax burden is too large. Our analysis suggests

that international cooperation in matters of anti-tax avoidance policies is crucial to avoid

such unintended consequences.

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Figure 1: Time-series evolution of the gateway test ratio, net UK debt and worldwide grossdebt–comparing the treated and control groups.

02

46

8M

ean

2008 2009 2010 2011 2012 2013 2014Year

Failed gateway test Did not fail gateway test

a Gateway test ratio

23

45

67

Mea

n

2008 2009 2010 2011 2012 2013 2014Year

Failed gateway test Did not fail gateway test

b Logarithm of total UK net debt

99.

510

10.5

11M

ean

2008 2009 2010 2011 2012 2013 2014Year

Failed gateway test Did not fail gateway test

c Logarithm of worldwide gross debt

Note: Gateway test ratio is the ratio of total UK net debt to worldwide gross debt. TotalUK net debt and worldwide gross debt are calculated on the annual basis. The figure plotsmean logarithms of each of those variables respectively for the treatment and control groups.

33

Figure 2: Time-series evolution of the gateway test ratio, net UK debt and worldwide grossdebt–comparing domestic and foreign MNCs.

23

45

67

Mea

n

2008 2009 2010 2011 2012 2013 2014Year

Failed gateway test Did not fail gateway test

a UK net debt: domestic MNCs

99.

510

10.5

Mea

n

2008 2009 2010 2011 2012 2013 2014Year

Failed gateway test Did not fail gateway test

b Worldwide gross debt: domestic MNCs

02

46

8M

ean

2008 2009 2010 2011 2012 2013 2014Year

Failed gateway test Did not fail gateway test

c UK net debt: foreign MNCs

89

1011

1213

Mea

n

2008 2009 2010 2011 2012 2013 2014Year

Failed gateway test Did not fail gateway test

d Worldwide gross debt: foreign MNCs

Note: Total UK net debt and worldwide gross debt are calculated on the annual basis. Thefigure plots mean logarithms of each variable respectively for treatment and control groups.

34

Figure 3: Dynamic effects of the WDC— coefficients from firm fixed effects regressions.-.8

-.6-.4

-.20

.2

Pred

icte

d lo

g ga

tew

ay ra

tio(in

tera

ctio

n co

effic

ient

)

2010 2011 2012 2013 2014

Year

a Logarithm of gateway test ratio

-2-1

01

Pred

icte

d lo

g ne

t UK

debt

(inte

ract

ion

coef

ficie

nt)

2010 2011 2012 2013 2014

Year

b Logarithm of total UK net debt

-.20

.2.4

.6.8

Pred

icte

d lo

g gr

oss

debt

(inte

ract

ion

coef

ficie

nt)

2010 2011 2012 2013 2014

Year

c Logarithm of worldwide gross debt

Note: The figure plots the difference-in-differences regression coefficients (the blue dots), βts,and 95% confidence intervals (the blue vertical lines) from a specification: Y UK

i,t = α +∑2014κ=2009 βt × Failedi × 1[t = κ] + δ × X

′it + ηt + ψi + εi,t; Failedi is a dummy variable that

equals one if MNC i failed the gateway test in 2010, and zero otherwise;∑2014

κ=−2009 1[t = κ]is a series of year dummies that equal one in each of the κ years that go from 2009 to2014; X

′it is a set of group-level control variables, such as group size, UK size and UK prof-

itability; ηt is the time fixed effect, ψi is the group-specific fixed effect, and εi,t is the er-ror term. We use 2009 as the base year in this fixed-effects estimation. Gateway test ra-tio is the ratio of two-year average net UK debt and two-year average worldwide gross debt.Total UK net debt and worldwide debt are logarithms of two-year averages, respectively.

35

Figure 4: Dynamic effects of the WDC—comparing domestic and foreign MNCs.

-4-3

-2-1

01

2

Pred

icte

d lo

g ne

t UK

debt

(inte

ract

ion

coef

ficie

nt)

2010 2011 2012 2013 2014

Year

a UK net debt: domestic MNCs

-1-.5

0.5

11.

52

Pred

icte

d lo

g gr

oss

debt

(inte

ract

ion

coef

ficie

nt)

2010 2011 2012 2013 2014

Year

b Worldwide gross debt: domestic MNCs

-4-3

-2-1

01

2

Pred

icte

d lo

g ne

t UK

debt

(inte

ract

ion

coef

ficie

nt)

2010 2011 2012 2013 2014

Year

c UK net debt: foreign MNCs

-1-.5

0.5

11.

52

Pred

icte

d lo

g gr

oss

debt

(inte

ract

ion

coef

ficie

nt)

2010 2011 2012 2013 2014

Year

d Worldwide gross debt: foreign MNCs

Note: The figure plots the difference-in-differences regression coefficients (the blue dots), βts, and95% confidence intervals (the blue vertical lines) from a specification: Y UK

i,t = α +∑2014

κ=2009 βt ×Failedi×1[t = κ]+δ×X ′

it+ηt+ψi+εi,t; Failedi is a dummy variable that equals one if MNC i failedthe gateway test in 2010, and zero otherwise;

∑2014κ=−2009 1[t = κ] is a series of year dummies that

equal one in each of the κ years that go from 2009 to 2014; X′it is a set of group-level control variables,

such as group size, UK size and UK profitability; ηt is the time fixed effect, ψi is the group-specificfixed effect, and εi,t is the error term. We use 2009 as the base year in this fixed-effects estimation.Panels A and B plot these coefficients for domestic MNCs, Panels C and D plot these for foreignMNCs. Total UK net debt and worldwide debt are logarithms of two-year averages, respectively.

36

Table 1: Matching properties: means of treatment and control groups in 2009.

Variable Treated Control T-statistics % bias % biasreduction

MNC log assets Unmatched 12.32 13.68 -19.73 -57.4Matched 12.27 12.38 -0.47 -4.7 91.9

MNC total assets Unmatched 2,681 9,058 -7.37 -25.5Matched 2,690 3,527 -0.46 -3.3 86.9

MNC log gross Unmatched 9.4 11.45 -17.25 -54.7debt (wwgb) Matched 9.23 10.33 -3.55 -30.2 44.8MNC gross debt Unmatched 580 2700 -5.92 -22.2

Matched 510 900 -0.96 -4.1 81.6MNC ETR Unmatched .064 .043 0.97 8.5

Matched .064 0.050 0.46 5.8 31.7UK total assets Unmatched 13.8 4.36 6.35 8.3

Matched 13.7 6.5 0.62 6.4 23.5UK employment Unmatched 4,886 1,444 5.33 6.4

Matched 4,987 5,710 -0.30 -1.3 79.0UK fixed assets Unmatched 9.64 2.62 6.76 8.4

Matched 9.95 3.90 0.69 7.3 13.8UK log net debt Unmatched 10.03 5.09 31.03 110.9

Matched 10.70 4.41 14.51 141.6 -27.7UK log gateway Unmatched 0.92 -1.56 37.63 134.3test ratio Matched 1.29 -0.92 15.30 120.1 10.5UK profitability Unmatched -0.07 0.003 -8.03 -19.7

Matched -0.05 -0.04 -0.37 -4.0 79.5UK ETR Unmatched 0.128 0.167 -5.6 -0.68

Matched 0.15 0.14 1.0 0.09 82.9

Note: This table reports the matching properties for key firm-level financial variables used in theanalysis of the effects of WDC on UK debt and UK real activities based on Fame data. Treatedgroup includes firms that failed the gateway ratio test in 2010. Control group contains firms thatdid not fail the gateway ratio in 2010. We match the two groups of firms based on GUO indus-try, location and size, using the one-to-one nearest neighbor matching technique without replace-ment. % bias reduction is calculated as (% bias of unmatched sample-% bias of matched sam-ple)/(% bias of unmatched sample). MNC total assets, MNC gross debt, UK total assets andfixed assets are reported in $ millions. Employment is measured in number of people employed.

37

Table 2: Impact of the worldwide debt cap on MNCs’ group-level debt holdings.

Dep. Var. Log Gateway Ratio Log UK Net Debt Log Gross Debt(1) (2) (3) (4) (5) (6)

Failedi 1.682*** 5.651*** -0.588***(0.094) (0.245) (0.120)

Failedi × Postt -0.406*** -0.341*** -1.480*** -1.349*** 0.297** 0.319***(0.108) (0.079) (0.274) (0.196) (0.134) (0.084)

Group size -0.059*** -0.567*** 0.128* 0.032 0.913*** 0.991***(0.021) (0.078) (0.071) (0.196) (0.037) (0.091)

UK size -0.246*** 0.056 0.875*** 0.540*** 0.160*** -0.023(0.028) (0.054) (0.055) (0.138) (0.026) (0.054)

UK profitability 0.198** 0.168* -2.368*** -0.231 -0.616*** -0.134(0.093) (0.091) (0.271) (0.257) (0.142) (0.117)

Industry FE YES NO YES NO YES NOYear FE YES YES YES YES YES YESGroup FE NO YES NO YES NO YESNo. of groups 376 376 376 376 376 376Observations 2,054 2,054 2,054 2,054 2,054 2,054

Note: This table reports the estimated effects of the WDC on MNCs’ gateway ratio, UKnet debt and worldwide gross debt. We match the treated and the control groups on theMNCs’ GUO industry, location and size. Gross Debt is the worldwide gross debt of themultinational group; UK Net Debt is UK relevant liability minus UK relevant assets, ag-gregated across the MNCs’ UK subsidiaries; and Gateway Ratio is UK net debt divided bygross debt. Group Size is the logarithm of total assets for the whole group, and UK Size isthe logarithm of total assets summed across all UK subsidiaries belonging to the same par-ent. UK Profitability is the ratio of profit and loss before taxes and total assets, whereboth numerator and denominator are summed across all UK subsidiaries belonging to thesame parent. Standard errors are robust and two-way clustered over MNC group and year.

38

Tab

le3:

Impac

tof

the

wor

ldw

ide

deb

tca

pon

MN

Cs’

grou

p-l

evel

deb

thol

din

gs–h

eadquar

ter

het

erog

enei

ties

.

Dep

.V

ar.

Log

Gat

eway

Rat

ioL

ogU

KN

etD

ebt

Log

Gro

ssD

ebt

(1)

(2)

(3)

(4)

(5)

(6)

Dom

esti

cM

NC

For

eign

MN

CD

omes

tic

MN

CF

orei

gnM

NC

Dom

esti

cM

NC

For

eign

MN

C

Failed

i×Post t

-0.2

84**

*-0

.539

***

-1.5

40**

*-0

.989

***

0.25

1***

0.49

6**

(0.0

84)

(0.1

91)

(0.2

30)

(0.3

76)

(0.0

93)

(0.1

93)

Gro

up

size

-0.5

33**

*-1

.126

***

-0.1

24-0

.148

0.89

0***

1.70

8***

(0.0

80)

(0.1

74)

(0.2

13)

(0.3

71)

(0.0

99)

(0.2

44)

UK

size

0.24

2***

-0.0

291.

243*

**0.

112

0.00

5-0

.088

(0.0

79)

(0.0

65)

(0.2

37)

(0.1

15)

(0.1

06)

(0.0

61)

UK

pro

fita

bilit

y0.

040

0.18

0-0

.342

-0.6

43**

*-0

.065

-0.2

11(0

.101

)(0

.164

)(0

.357

)(0

.245

)(0

.141

)(0

.205

)Y

ear

FE

YE

SY

ES

YE

SY

ES

YE

SY

ES

Gro

up

FE

YE

SY

ES

YE

SY

ES

YE

SY

ES

No.

ofgr

oups

278

9827

898

278

98O

bse

rvat

ions

1,53

152

31,

531

523

1,53

152

3

Note

:T

his

tab

lere

port

sth

ees

tim

ated

effec

tsof

the

WD

Con

gate

way

rati

o,U

Kn

etd

ebt

and

wor

ldw

ide

gros

sd

ebt

for

dom

esti

can

dfo

reig

nM

NC

s,re

spec

tivel

y.W

em

atch

the

trea

ted

and

the

contr

olgr

oup

son

the

MN

Cs’

GU

Oin

du

s-tr

y,lo

cati

on

and

size

.G

ross

Deb

tis

the

wor

ldw

ide

gros

sd

ebt

ofth

em

ult

inat

ion

algr

oup

;U

KN

etD

ebt

isU

Kre

l-ev

ant

liab

ilit

ym

inu

sU

Kre

leva

nt

ass

ets,

aggr

egat

edac

ross

the

MN

Cs’

UK

sub

sid

iari

es;

and

Gate

way

Rati

ois

UK

net

deb

td

ivid

edby

gro

ssd

ebt.

Gro

up

size

isth

elo

gari

thm

ofto

tal

asse

tsfo

rth

ew

hol

egr

oup

,U

Ksi

zeis

the

loga

-ri

thm

of

tota

lass

ets

sum

med

acro

ssal

lU

Ksu

bsi

dia

ries

bel

ongi

ng

toth

esa

me

par

ent,

UK

pro

fita

bili

tyis

the

rati

oof

pro

fit

and

loss

bef

ore

taxes

an

dto

tal

asse

ts,

wh

ere

bot

hnu

mer

ator

and

den

omin

ator

are

sum

med

acro

ssal

lU

Ksu

b-

sid

iari

esb

elon

gin

gto

the

sam

ep

aren

t.S

tan

dar

der

rors

are

rob

ust

and

two-

way

clu

ster

edov

erM

NC

grou

pan

dye

ar.

39

Tab

le4:

Impac

tof

the

wor

ldw

ide

deb

tca

pon

non

-UK

subsi

dia

ries

’le

vera

gera

tio.

Dep

.V

ar.

All

MN

CD

omes

tic

MN

CF

orei

gnM

NC

Lev

ijst

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Failed

i×Post t

0.18

6***

0.15

2***

0.13

6***

0.07

4**

0.16

0**

(0.0

30)

(0.0

29)

(0.0

30)

(0.0

35)

(0.0

68)

Failed

i×Post t×CITst

0.52

2***

0.24

8**

0.57

6***

(0.1

03)

(0.1

21)

(0.2

18)

Gro

up

size

-0.0

17-0

.021

-0.0

15-0

.069

-0.0

96**

0.07

20.

152*

(0.0

42)

(0.0

40)

(0.0

42)

(0.0

47)

(0.0

48)

(0.0

86)

(0.0

85)

Subsi

dia

rysi

ze0.

182*

**0.

183*

**0.

183*

**0.

196*

**0.

201*

**0.

180*

**0.

171*

**(0

.030

)(0

.028

)(0

.030

)(0

.034

)(0

.037

)(0

.052

)(0

.049

)Subsi

dia

rypro

fita

bilit

y-0

.003

-0.0

03-0

.003

-0.0

03-0

.003

-0.1

34-0

.148

*(0

.002

)(0

.002

)(0

.002

)(0

.002

)(0

.002

)(0

.091

)(0

.086

)Y

ear

FE

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

Hos

tco

untr

y-y

ear

FE

NO

NO

YE

SN

OY

ES

NO

YE

SN

OSubsi

dia

ryF

EY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SN

o.of

grou

ps

1,92

61,

792

1,79

21,

791

1,04

91,

048

744

744

Obse

rvat

ions

11,8

2711

,198

11,1

9811

,193

6,69

36,

691

4,50

54,

502

Note

:T

his

tab

lere

por

tsth

ees

tim

ated

effec

tof

the

WD

Con

the

leve

rage

rati

oof

MN

Cs’

non

-UK

sub

sid

iari

es.

Levijst

isth

en

et-o

f-ca

shle

ver

age

rati

oof

sub

sid

iary

j,w

hic

hb

elon

gsto

MN

Ci

and

islo

cate

din

cou

ntr

ys,

inye

art.

CITst

isth

est

atu

tory

corp

orat

ein

com

eta

xra

tein

cou

ntr

ys

inye

art.

We

mat

chth

etr

eate

dan

dth

eco

ntr

olgr

oup

son

the

MN

Cs’

GU

Oin

du

stry

,lo

cati

onan

dsi

ze.

Gro

up

Siz

eis

the

loga

rith

mof

tota

las

sets

for

the

wh

ole

grou

p,

Su

b-si

dia

ryS

ize

islo

gari

thm

of

tota

las

set

for

each

sub

sid

iary

,an

dS

ubs

idia

ryP

rofi

tabi

lity

isth

era

tio

ofp

rofi

tan

dlo

ssb

e-fo

reta

xan

dto

tal

ass

ets

for

each

sub

sid

iary

.Sta

nd

ard

erro

rsar

ero

bu

stan

dtw

o-w

aycl

ust

ered

over

sub

sid

iary

and

year

.

40

Tab

le5:

Impac

tof

the

wor

ldw

ide

deb

tca

pon

MN

Cs’

UK

oper

atio

ns

All

MN

Cs

Dom

esti

cM

NC

sF

orei

gnM

NC

s(1

)(2

)(3

)(4

)(5

)(6

)(7

)(8

)(9

)D

ep.

Var

.as

sets

fxas

sets

emp

asse

tsfx

asse

tsem

pas

sets

fxas

sets

emp

Failed

i×Post t

-0.0

75**

-0.1

14**

-0.0

39*

-0.0

06-0

.066

-0.0

12-0

.344

***

-0.3

63**

-0.1

13**

*(0

.037

)(0

.057

)(0

.021

)(0

.033

)(0

.058

)(0

.025

)(0

.113

)(0

.152

)(0

.039

)G

rou

psi

ze0.

409*

**0.

490*

**0.

583*

**0.

299*

**0.

388*

**0.

572*

**0.

977*

**1.

137*

**0.

614*

**(0

.049

)(0

.065

)(0

.030

)(0

.041

)(0

.059

)(0

.036

)(0

.150

)(0

.152

)(0

.056

)Y

ear

FE

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SG

rou

pF

EY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

No.

ofgr

oup

s37

637

123

027

827

717

198

9459

Ob

serv

atio

ns

2,05

42,

009

1,25

91,

531

1,52

194

252

348

831

7

Note

:T

his

tab

lere

port

sth

ees

tim

ated

effec

tsof

the

WD

Con

MN

Cs’

UK

oper

atio

n,

pro

xie

dby

thei

rU

Kto

tal

as-

sets

(ass

tes)

,fi

xed

ass

ets

(fx

ass

ets)

,an

dem

plo

ym

ent

(em

p)

aggr

egat

edac

ross

all

UK

sub

sid

iari

es(a

llin

nat

ura

llo

ga-

rith

m).

Colu

mn

s1-

3co

nsi

der

all

MN

Cs,

Col

um

ns

3-6

con

sid

erd

omes

tic

MN

Cs,

and

Col

um

ns

7-9

con

sid

erfo

reig

nM

NC

s.W

em

atc

hth

etr

eate

dan

dth

eco

ntr

olgr

oup

son

the

MN

Cs’

GU

Oin

du

stry

,lo

cati

onan

dsi

ze.

Gro

up

size

isth

elo

ga-

rith

mof

tota

las

sets

for

the

wh

ole

grou

p.

Sta

nd

ard

erro

rsar

ero

bu

stan

dtw

o-w

aycl

ust

ered

over

MN

Cgr

oup

and

year

.

41

Tab

le6:

Impac

tof

the

wor

ldw

ide

deb

tca

pon

MN

Cs’

non

-UK

oper

atio

ns

Panel

A:

Avera

ge

Eff

ect

s

All

MN

Cs

Dom

esti

cM

NC

sF

orei

gnM

NC

s(1

)(2

)(3

)(4

)(5

)(6

)(7

)(8

)(9

)D

ep.

Var

.as

sets

fxas

sets

emp

asse

tsfx

asse

tsem

pas

sets

fxas

sets

emp

Failed

i×Post t

0.16

5***

0.11

3***

0.10

4***

0.21

1***

0.13

8***

0.07

1**

0.22

9***

0.17

5*0.

233*

**(0

.027

)(0

.039

)(0

.027

)(0

.032

)(0

.046

)(0

.031

)(0

.062

)(0

.092

)(0

.063

)Y

ear

FE

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SG

roup

FE

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SN

o.of

grou

ps

2,02

61,

924

1,63

61,

184

1,13

596

284

579

267

5O

bse

rvat

ions

12,8

2012

,056

8,72

47,

598

7,16

95,

219

5,22

24,

887

3,50

5

Panel

B:

Corp

ora

teta

xra

tein

tera

ctio

ns

All

MN

Cs

Dom

esti

cM

NC

sF

orei

gnM

NC

s(1

)(2

)(3

)(4

)(5

)(6

)(7

)(8

)(9

)D

ep.

Var

.as

sets

fxas

sets

emp

asse

tsfx

asse

tsem

pas

sets

fxas

sets

emp

Failed

i×Post t×CITst

0.59

3***

0.37

6**

0.36

4***

0.81

5***

0.45

2**

0.23

8**

0.73

3***

0.55

5*0.

825*

**(0

.104

)(0

.149

)(0

.104

)(0

.125

)(0

.179

)(0

.119

)(0

.241

)(0

.336

)(0

.244

)Y

ear

FE

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SSubsi

dia

ryF

EY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

YE

SY

ES

No.

ofgr

oups

1,83

41,

753

1,48

61,

057

1,01

686

877

873

861

9O

bse

rvat

ions

10,1

189,

525

7,07

45,

965

5,63

34,

247

4,15

33,

892

2,82

7

Note

:T

his

tab

lere

port

sth

ees

tim

ate

deff

ects

ofth

eW

DC

onM

NC

s’n

on-U

Kop

erat

ion

s,p

roxie

dby

non

-UK

sub

sid

iary

j’s

tota

las

sets

(ass

ets)

,fi

xed

asse

ts(f

xas

sets

),an

dem

plo

ym

ent

(em

p),

all

inn

atu

ral

loga

rith

m.

Col

um

ns

1-3

con

-si

der

all

MN

Cs,

Col

um

ns

4-6

con

sid

erd

omes

tic

MN

Cs,

and

Col

um

ns

7-9

consi

der

fore

ign

MN

Cs.

InP

anel

BCITst

isth

est

atu

tory

corp

ora

tein

com

eta

xra

tein

cou

ntr

ys

inye

art.

We

mat

chth

etr

eate

dan

dth

eco

ntr

olgr

oup

son

the

MN

Cs’

GU

Oin

du

stry

,lo

cati

onan

dsi

ze.

Sta

nd

ard

erro

rsar

ero

bu

stan

dtw

o-w

aycl

ust

ered

over

sub

sid

iary

and

year

.

42

Table 7: Impact of the worldwide debt cap on MNCs’ organizational structures.

Dep. Var. (1) (2) (3) (4)%UK 50+ %UK 75+ %High Tax %Low Tax

Subs Subs

Failedi × Postt -0.002 -0.016* 0.042*** -0.037***(0.009) (0.009) (0.007) (0.006)

Year FE YES YES YES YESParent FE YES YES YES YESNo. of groups 1,306 1,306 1,306 1,306Observations 11,983 11,983 11,983 11,983

Note: This table reports the estimated effects of the WDC on MNCs’ organizational struc-tures. %UK 50+ is the proportion of controlled UK subsidiaries (shares holding is above50%); %UK 75+ is the proportion of UK subsidiaries with 75% or more shares controlledby the MNC; %High Tax Subs is the proportion of subsidiaries in countries with a statu-tory corporate income tax rate higher than that in the UK; %Low Tax Subs is the pro-portion of subsidiaries in countries with a statutory corporate income tax rate lower thanthat in UK. Standard errors are robust and two-way clustered over MNC group and year.

43

Table 8: Impact of the worldwide debt cap on tax payments.

Panel A: UK subsidiaries

Dep. Var. All MNC Domestic MNC Foreign MNCln UK taxpaidit (1) (2) (3)

Failedi × Postt 0.168* 0.252*** -0.044(0.088) (0.097) (0.207)

Group size 0.204* 0.240** 0.008(0.106) (0.121) (0.347)

UK size -0.011 0.006 0.018(0.094) (0.154) (0.141)

UK profitability 1.807*** 1.690*** 1.733**(0.458) (0.566) (0.805)

UK turnover 0.739*** 0.808*** 0.632***(0.110) (0.156) (0.177)

Year FE YES YES YESGroup FE YES YES YESNo. of groups 317 237 80Observations 1,338 1,010 328

Note: This table reports the estimated effects of the WDC on MNCs’ UK tax payment.lnUKtaxpaidit is the natural logarithm of total tax payments aggregated across all UKsubsidiaries of MNC i in year t. Column 1 considers all MNCs, Column 2 considers do-mestic MNCs, and Column 3 considers foreign MNCs. We match the treated and thecontrol groups on the MNCs’ GUO industry, location and size in 2010. Group size is thelogarithm of total assets for the whole group, UK size is the logarithm of total assetssummed across all UK subsidiaries belonging to the same parent, UK profitability is theratio of profit and loss before taxes and total assets, where both numerator and denomi-nator are summed across all UK subsidiaries belonging to the same parent. UK turnoveris the logarithm of turnover summed across all UK subsidiaries belonging to the sameparent. Standard errors are robust and two-way clustered over MNC group and year.

44

Panel B: Non-UK subsidiaries

Dep. Var. (1) (3) (5)ln non-UK taxpaidit All Domestic MNC Foreign MNC

Failedi × Postt 0.003 0.010 -0.151(0.058) (0.066) (0.148)

Group size 0.297*** 0.254*** 0.431***(0.058) (0.079) (0.112)

Subsidiary size 0.488*** 0.597*** 0.400***(0.044) (0.057) (0.062)

Subsidiary profitability 0.874*** 1.452*** 0.580*(0.308) (0.343) (0.318)

Subsidiary turnover 0.300*** 0.261*** 0.328***(0.038) (0.049) (0.057)

Observations 8,432 4,862 3,570No. of groups 1,636 948 689Matching YES YES YES

Note: This table reports the estimated effects of the WDC on MNCs’ non-UK tax pay-ment. ln non-UK taxpaidit is the natural logarithm of total tax payments aggregatedacross all non-UK subsidiaries of MNC i in year t. We match the treated and the con-trol groups on the MNCs’ GUO industry, location and size in 2010. Group size is thelogarithm of total assets for the whole group, subsidiary size is logarithm of total assetfor each subsidiary, subsidiary profitability is the ratio of profit and loss before tax andtotal assets for each subsidiary, subsidiary turnover is the logarithm of revenue for eachsubsidiary. Standard errors are robust and two-way clustered over subsidiary and year.

45

Table 9: Territorial tax system reform and dividend repatriation.

(1) (2)Dep. Var. Dividend received by UK Dividend paid by

subsidiaries non-UK subsidiaries

Failedi × Postt 0.162 0.075(0.236) (0.189)

Group size -0.177 0.580**(0.223) (0.231)

Subsidiary size 0.303* 0.500***(0.156) (0.107)

Subsidiary profitability 1.445* 0.006(0.763) (0.013)

Year FE YES YESSubsidiary FE YES YESNo. of groups 1425 988Observations 6,230 5,710

Note: This table compares dividend repatriations of treated and untreated domestic MNCs. InColumn 1, the dependent variable is the natural logarithm of one plus dividends that are receivedby the MNCs’ UK subsidiaries, where dividends are defined as the difference between 2008 and2009 shareholder funds available for distribution (equity) calculated after current profits. If divi-dends calculated in this way are negative, we set them to zero. In Column 2, the dependent vari-able is the natural logarithm of one plus dividends payout by MNCs’ non-UK subsidiaries. Wematch the treated and the control groups on the MNCs’ GUO industry, location and size. Groupsize is the logarithm of total assets for the whole group, subsidiary size is logarithm of total assetfor each subsidiary, subsidiary profitability is the ratio of profit and loss before tax and total assetsfor each subsidiary. Standard errors are robust and two-way clustered over subsidiary and year.

46

Appendices

Table A1: Summary statistics of key variables.

Variable All MNCs domestic MNCs foreign MNCstreated control treated control treated control

Panel A: UK key characteristics: FAMEAggregated across MNCs:UK total assets 2,514.47 498.82 2,482.37 453.96 32.10 44.87UK employment 563,466 301,667 527,500 277,035 35,966 24,632UK fixed assets 1,815.81 314.80 1,800.69 292.65 15.12 22.15

Panel B: non-UK key characteristics: ORBISAveraged across MNCs:ETR 0.171 0.203 0.164 0.200 0.186 0.205CIT 0.26 0.254 0.258 0.249 0.263 0.257Leverage -0.138 -0.233 -0.125 -0.229 -0.168 -0.236% of domestic assets 74% 53% 81% 74% 42% 24%(calculated within MNE)Aggregated across MNCs:Total assets 333.96 163.53 279.35 46.60 54.62 116.94Employment 197,859 207,244 148,681 69,906 49,178 137,338Fixed assets 253.22 91.90 213.81 22.19 39.41 69.71

Note: This table reports the aggregate summary statistics of selected variables for treated and con-trol groups after propensity score matching has been performed. The statistics are for 2009 andare in billions of pounds for total assets and fixed assets, in units for employment and are ratiosfor leverage and ETRs. To obtain total assets, employment and fixed assets we sum across all UK(Panel A) and non-UK (Panel B) subsidiaries belonging to corresponding MNC types. The treatedgroup includes firms that failed the gateway ratio test in 2010. The control group contains firmsthat did not fail the gateway ratio in 2010. We match the two groups of firms based on GUOindustry, location and size, using the one-to-one nearest neighbor matching technique without re-placement. ETR is the effective tax rate, calculated as a ratio of tax expense to profit and lossbefore taxes. CIT is the statutory corporate income tax rate. Leverage is the net-of-cash lever-age ratio for all subsidiaries belonging to a particular MNC. The average % of domestic assets hasbeen calculate at the each MNC level and averaged across all MNCs. Hence, this number does notcorrespond to simply dividing UK total assets by the sum of UK and non-UK assets.

47

Table A2: Estimation results based on the full sample.

Dep. Var. Log Gateway Ratio Log UK Net Debt Log Gross Debt(1) (2) (3) (4) (5) (6)

Failedi 1.790*** 4.999*** -0.806***(0.085) (0.159) (0.101)

Failedi × Postt -0.240** -0.124** -0.798*** -0.865*** 0.110 0.039(0.099) (0.062) (0.187) (0.132) (0.117) (0.066)

Group size -0.401*** -0.553*** 0.115*** 0.160 1.084*** 1.064***(0.012) (0.055) (0.027) (0.112) (0.010) (0.070)

UK size -0.098*** -0.079*** 1.009*** 0.444*** 0.048*** 0.065***(0.009) (0.028) (0.021) (0.065) (0.006) (0.016)

UK profitability 0.493*** 0.244*** -3.225*** -0.814*** -0.211*** -0.076*(0.067) (0.065) (0.161) (0.148) (0.062) (0.042)

Industry FE YES NO YES NO YES NOYear FE YES YES YES YES YES YESGroup FE NO YES NO YES NO YESNo. groups 1,609 1,609 1,609 1,609 1,609 1,609Observations 9,631 9,631 9,631 9,631 9,631 9,631

Note: This table reports the estimated effects of the WDC on MNCs’ gateway ratio, UKnet debt, and worldwide gross debt, based on the full sample. Gross Debt is the worldwidegross debt of the multinational group; UK Net Debt is UK relevant liability minus UK rel-evant assets, aggregated across the MNCs’ UK subsidiaries; and Gateway Ratio is UK netdebt divided by gross debt. Group size is the logarithm of total assets for the whole group;UK size is the logarithm of total assets summed across all UK subsidiaries belonging to thesame parent; and UK profitability is the ratio of profit and loss before taxes and total assets,where both numerator and denominator are summed across all UK subsidiaries belonging tothe same parent. Standard errors are robust and two-way clustered over MNC group and year.

48

Table A3: Estimation results based on the kernel-matched sample.

(1) (2) (3)Dep. variable Log Gateway ratio Log UK net debt Log Gross debt

Failedi × Postt -0.387*** -1.255*** 0.277***(0.068) (0.169) (0.075)

Group size -0.565*** 0.042 1.028***(0.070) (0.170) (0.086)

UK size -0.038 0.451*** 0.053(0.053) (0.129) (0.050)

UK profitability 0.120 -0.227 -0.187*(0.097) (0.217) (0.111)

Industry FE NO NO NOYear FE YES YES YESGroup FE YES YES YESNo. of groups 1,373 1,373 1,373Observations 7,785 7,785 7,785

Note: This table reports the estimated effects of the WDC on MNCs’ gateway ratio, UK net debt,and worldwide gross debt, based on an alternative matched sample using the kernel-matching tech-nique. Gross Debt is the worldwide gross debt of the multinational group; UK Net Debt is UK rel-evant liability minus UK relevant assets, aggregated across the MNCs’ UK subsidiaries; and Gate-way Ratio is UK net debt divided by gross debt. Group size is the logarithm of total assets for thewhole group; UK size is the logarithm of total assets summed across all UK subsidiaries belong-ing to the same parent; and UK profitability is the ratio of profit and loss before taxes and totalassets, where both numerator and denominator are summed across all UK subsidiaries belongingto the same parent. Standard errors are robust and two-way clustered over MNC group and year.

49

Table A4: Robustness tests: various matching variables.

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

Dependent variable: Log Gateway Ratio

Failedi × Postt -0.292*** -0.339*** -0.286*** -0.365*** -0.399*** -0.403***(0.082) (0.083) (0.076) (0.078) (0.077) (0.083)

Dependent variable: Log UK Net Debt

Failedi × Postt -1.622*** -1.294*** -1.177*** -1.257*** -1.098*** -1.456***(0.204) (0.215) (0.203) (0.203) (0.202) (0.212)

Dependent variable: Log Gross Debt

Failedi × Postt 0.226*** 0.139* 0.213*** 0.273*** 0.272*** 0.226***(0.082) (0.083) (0.082) (0.083) (0.079) (0.085)

Year FE YES YES YES YES YES YESGroup FE YES YES YES YES YES YESNo. of groups 322 324 372 372 371 318Observations 1,790 1,796 2,043 2,047 2,043 1,769

Note: This table reports the estimated effects of the WDC on MNCs’ gateway ratio, UK net debt,and worldwide gross debt using alternative matching variables. In all specifications we match thetreated and the control groups on the MNCs’ GUO industry, location and size. We in additionmatch on UK profitability in column (1), UK effective tax rates in column (2), the ratio of UKtotal assets to worldwide total assets in column (3), the difference in MNCs’ UK assets between2008 and 2009 in column (4), the difference in MNCs’ total assets between 2008 and 2009 in col-umn (5), and all of these together in column (6). Matching is based on the nearest-neighbor one-on-one matching technique without replacement. Gross Debt is the worldwide gross debt of themultinational group; UK Net Debt is UK relevant liability minus UK relevant assets, aggregatedacross the MNCs’ UK subsidiaries; and Gateway Ratio is UK net debt divided by gross debt.In each regression we control for the following variables, but do not report regression coefficientsfor brevity: MNCs’ group size proxied by the logarithm of total assets for the whole group; UKsize proxied by the logarithm of total assets summed across all UK subsidiaries belonging to thesame parent; UK profitability proxied by the ratio of profit and loss before taxes and total as-sets, where both numerator and denominator are summed across all UK subsidiaries belonging tothe same parent. Standard errors are robust and two-way clustered over MNC group and year.

50

Tab

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80.

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size

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51