studiul pietei

The Effects on American Foreign DirectInvestment in the United Kingdom from NotAdopting the Euro*jcms_2124 463..484

MARCOS SANSO-NAVARROUniversidad de Zaragoza

Abstract

The decision of the United Kingdom not to adopt the common European currency canbe understood as a policy intervention in a single country within the European Union.The aim of this article is to analyse the consequences of this decision on the foreigndirect investment received by this country. This is done by the application of asynthetic control method designed for policy evaluation. As a result, evidence of asignificant cost in terms of inward foreign direct investment from the United States isobtained.

Introduction

There has been growing interest in analysing the effects of euro adoptionon European monetary union (EMU) member countries in recent years.Although a wide array of variables have been considered, interest has mainlyfocused on aspects related to investment and trade issues: foreign exchangerisk exposures (Bartram and Karolyi, 2006), financial market dependence(Bartram et al., 2007), firms’ investment rates (Bris et al., 2006), trade flows(Baldwin and Taglioni, 2007; Brouwer et al., 2008) and foreign direct invest-ment (FDI) (Petroulas, 2007; Schiavo, 2007; Taylor, 2008; Brouwer et al.,

* The author has benefited from the helpful comments of an anonymous referee. Financial support fromMinisterio de Educación y Ciencia (SEJ2006-14397 project) and the Regional Government of Aragón(ADETRE Research Group) is acknowledged.

JCMS 2011 Volume 49. Number 2. pp. 463–483DOI: 10.1111/j.1468-5965.2010.02124.x

© 2011 The Author(s)JCMS: Journal of Common Market Studies © 2011 Blackwell Publishing Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 MainStreet, Malden, MA 02148, USA

2008; De Sousa and Lochard, forthcoming). This article aims to contribute tothe literature on the relationship between EMU membership and FDI from adifferent perspective. The main difference with respect to existing studies isthat this article focuses on the consequences of not adopting the euro in asingle country. Using a comparative case study, the assessment of the effectson inward FDI from the United States is made for the most controversial euronon-enrolment case: the United Kingdom.

The importance of the relationship between EMU membership and theFDI received by the United Kingdom can be inferred from the Five EconomicTests (Her Majesty’s Treasury, 1997, 2003; see also Artis, 2006) conductedby the British authorities in order to decide whether or not to adopt the euro.They consisted of answering the following questions:

1. Were the business cycles and economic structures of all potential memberscompatible enough to evolve comfortably with a common interest rate ona permanent basis?

2. Was there sufficient flexibility to deal with future problems?3. Would joining the EMU create better conditions for firms making long-

term decisions to invest in Britain?4. What impact would EMU membership have on the competitive position of

the United Kingdom’s financial services industry?1

5. Summarizing, will joining the EMU promote higher growth, stability andemployment?

The third test is directly related to the question posed in this article, and wasmainly motivated by the fact that Britain received the highest FDI inflows asa percentage of the GDP among the European Union (EU) members, espe-cially for inward FDI coming from outside Europe. According to the recentlyestablished ‘Export-Platform’ FDI patterns (Ekholm et al., 2007), the deci-sion not to join the EMU should have dissuaded American and Japaneseinvestors from considering the United Kingdom as a gateway into the Euro-pean market. Furthermore, the impact of the EMU on FDI became one of thekey issues in the economic debate2 between those who saw major advantagesin the ‘outs’ adopting the euro and those who saw more costs than benefits(Barr et al., 2003).

Our approach considers the decision adopted by the British authorities ofnot joining the euro as a policy intervention in a single country within the EU.This perspective allows us to assess the effects on FDI by means of a syntheticcontrol method (Abadie and Gardeazábal, 2003; Abadie et al., 2010) that is

1 Particularly thinking of the City’s wholesale markets.2 Some examples of related independent reports are Layard et al. (2002), Begg et al. (2003) and thereferences therein.

464 MARCOS SANSO-NAVARRO

© 2011 The Author(s)JCMS: Journal of Common Market Studies © 2011 Blackwell Publishing Ltd

suitable for the evaluation of policy measures implemented at a countrylevel.3 The main result of this assessment is that there exists a significant costderived from this decision in terms of inward FDI from the United States. Themagnitude of this estimated effect is compared and integrated with studiesabout the influence of EMU membership on FDI that have been carried outwith different methodologies and data sources.

The rest of this article is structured as follows. Section I briefly reviews theliterature on the relationship between EMU membership and FDI. Section IIdescribes the main features of the synthetic control method applied, whilesection III deals with its empirical implementation in our context. Section IVdevelops a preliminary analysis of FDI flows time-series for selected EUcountries, presents the results obtained from the policy evaluation and drawsinferences about their significance. Finally, the article concludes with a dis-cussion of the estimated effects.

I. EMU and FDI: The Background

Early assessments of the effects of not joining the euro on Britain’s inwardFDI appeared around four years after the start of the third stage of the EMU.Their main limitation was that data availability did not allow strong conclu-sions to be drawn. This was aggravated by the fact that FDI flows are highlyvariable. A summary of the studies dealing with the relationship between theEMU and FDI reviewed in this section is reported in Table 1.

In the evaluation of the Five Economic Tests conducted by the BritishTreasury (Her Majesty’s Treasury, 2003), it was recognized that Britain’sshare of FDI flows from the rest of the world to the EU decreased after thestart of the EMU. In addition, it was emphasized that this fall coincided withan increase in the flows received by the EMU member countries. Similararguments were put forward by Layard et al. (2002) who argued that theabove-mentioned share had more than halved in the period 1999–2001 withrespect to the two previous years. Another study reaching the same conclu-sion is Begg et al. (2003). Furthermore, Barr et al. (2003) concluded that halfof this fall was related to an increase in the relative investment costs of theUnited Kingdom but did not attribute any effect to being outside the EMU.Given that these studies analysed the shares of total FDI received by the EU,they reflected worse behaviour than the EMU countries.

Empirical studies about the positive effects of the EMU on the FDIreceived by its member countries have appeared in recent years. De Sousa and

3 Another recent study analysing the economic consequences of not joining the euro is Pesaran et al.(2007). These authors estimate the effects on output and prices in the United Kingdom and Sweden usinga Global VAR framework.

THE EFFECTS ON AMERICAN FOREIGN DIRECT INVESTMENT IN THE UNITED KINGDOM 465


Tabl

e1:

Sum

mar

yof

the

Lite

ratu

reE

xam

inin

gE

MU

Eff

ects

onFD

I

Aut

hors

FD

Im

easu

reD

ata

sour

ces

Sam

ple

peri

odH

ome

coun

trie

sH

ost

coun

trie

sM

etho

dolo

gyE

MU

effe

ct(%

)

Lay

ard

etal

.(2

002)

Shar

eof

flow

sin

toE

UE

urop

ean

Com

mis

sion

and

Eur

osta

t19

97–2

001

All

UK

Des

crip

tive

anal

ysis

-54

Bar

ret

al.

(200

3)Sh

are

ofst

ocks

inE

UU

NC

TAD

1998

–200

1A

llU

KD

escr

iptiv

ean

alys

is-1

1Sh

are

ofU

Sflo

ws

into

EU

Bur

eau

ofE

cono

mic

Ana

lysi

s19

98–2

001

US

UK

-29

Beg

get

al.

(200

3)Sh

are

offlo

ws

into

EU

Eur

osta

t19

98–2

001

All

UK

Des

crip

tive

anal

ysis

-60

All

EM

U75

Her

Maj

esty

’sT

reas

ury

(200

3)Sh

are

offlo

ws

into

EU

UN

CTA

D19

99–2

001

All

UK

Des

crip

tive

anal

ysis

-43

Eur

osta

t19

98–2

001

Non

-EU

UK

-50

Shar

eof

flow

sw

ithin

EU

Eur

osta

t19

95–2

001

EU

UK

No

effe

ct

De

Sous

aan

dL

ocha

rd(2

009)

Bila

tera

lst

ocks

Inte

rnat

iona

lD

irec

t19

92–2

005

EM

UE

MU

Gra

vity

spec

ifica

tion

Pane

l‘w

ithin

’es

timat

ion

31In

vest

men

tD

atab

ase

62B

ilate

ral

flow

s

Petr

oula

s(2

007)

Inw

ard

flow

sE

uros

tat

1992

–200

1E

MU

EM

UG

ravi

tyre

gres

sion

sD

iffe

renc

es-i

n-di

ffer

ence

s16

EM

UN

on-E

MU

11N

on-E

MU

Non

-EM

U8

Schi

avo

(200

7)B

ilate

ral

flow

sIn

tern

atio

nal

Dir

ect

Inve

stm

ent

Dat

abas

e19

80–2

001

OE

CD

EM

UG

ravi

tysp

ecifi

catio

n‘F

ixed

effe

cts’

pane

les

timat

ion

Tobi

tm

odel

Posi

tive

EM

UE

MU

Posi

tive

OE

CD

UK

and

Den

mar

kN

oef

fect

Bro

uwer

etal

.(2

008)

Out

war

dst

ocks

Inte

rnat

iona

lD

irec

tIn

vest

men

tD

atab

ase

1990

–200

4O

EC

DE

Uen

tran

tsin

2004

Err

or-c

ompo

nent

grav

itym

odel

sSi

mul

ated

scen

ario

s18

.5–3

0

Tayl

or(2

008)

Bila

tera

lflo

ws

Eur

osta

t19

94–2

003

EM

UE

MU

Des

crip

tive

anal

ysis

80–2

82N

on-E

MU

EM

U22

7–51

7Fl

ows

as%

ofG

DP

1980

–200

3E

MU

EM

UE

xtra

pola

ted

log-

linea

rtr

ends

-12–

70N

on-E

MU

EM

U95

–263

OE

CD

and

UK

Offi

ceof

Nat

iona

lSt

atis

tics

EM

UU

K11

2N

on-E

MU

UK

-28

Sour

ce:A

utho

rs’

own

data

.



Lochard (forthcoming) developed a theoretical model for bilateral FDI stocksthat led to a gravity-like specification made up of four components: inwardeffect (origin), outward effect (destination), bilateral effect (transaction costs)and multilateral effect (alternative locations). Using data from 21 OECDcountries in the period 1992–2005 and panel estimation techniques, theyestablished that the adoption of the euro increased intra-EMU FDI stocks byaround 31 per cent. According to Barr et al. (2003), the corresponding effecton FDI flows is more than double (62 per cent) that on stocks. Moreover, theyfound that the magnitude of these positive effects was higher in the peripheralcountries. Using the same specification, Petroulas (2007) obtained a positiveeffect of the EMU on inward FDI flows of 16 per cent within the eurozoneusing a sample of 18 developed countries for the years 1992–2001 and adifferences-in-differences approach. Furthermore, spillover effects to andfrom non-EMU countries were found. Thus, these two studies have estab-lished the global effects of the euro on FDI.

Schiavo (2007) studied the link between currency unions and cross-borderinvestment through the reduction in exchange rate uncertainty. He found apositive effect of the EMU on FDI flows – not only for its members – evenafter controlling for exchange rate volatility in an empirical linear gravitymodel. The sample consisted of 22 OECD countries in the period 1980–2001.In addition, he did not find any adverse effect on the inward investmentflows received by the United Kingdom and Denmark as a consequence oftheir decision to stay outside the euro. A similar specification augmented withdistance-related variables was used by Brouwer et al. (2008) in order topredict the implications on (trade and) FDI of a potential EMU enlargementto the countries that joined the EU in 2004. Using an unbalanced panel ofoutward bilateral FDI stocks for 29 countries in 1990–2004, the simulatedeffects were between 18.5 and 30 per cent.

A recent exhaustive analysis using several data sources and a time span ofmore than 20 years is carried out in Taylor (2008) who reports a broad array ofimpact magnitudes for the 12 EMU countries, the United Kingdom, Japan andthe United States. Among many other conclusions, this author states that mostof the FDI inflows within the eurozone after 1999 were a consequence of theend-of-century takeover boom. However, he also recognizes that the EMU hasstimulated FDI inflows in the eurozone from the other major investing coun-tries. In addition, it is established that Britain’s inflows from countries otherthan the EU members were 28 per cent below trend after the introduction of theeuro. The main caveat is that this author calculated these trends with data priorto 1999 using log-linear trends from a standard OLS fit. Resulting estimates areused as a counterfactual for the subsequent years. In addition, there are noinferences about the significance of the reported effects.



This article aims to contribute to this literature by assessing the effects ofthe United Kingdom not joining the euro on the FDI received from the UnitedStates using a comparative case study. To do so, the British decision isconsidered as a policy intervention in a single country within the EU. For thisreason, the consequences derived are estimated by the application of a syn-thetic control method for policy evaluation described in the following section.

II. Policy Evaluation Using Synthetic Controls

Comparative case studies are commonly used to estimate the effects of policyinterventions. These studies compare the evolution of the variables underscrutiny in the case of one agent affected by the policy (‘treated’) with theevolution of the same variables in a group of unaffected agents (‘controls’).4

The main difficulties when applying this approach are, first, how to choosethe units of comparison, and second, the uncertainty related to the abilityof the controls to reproduce the counterfactual situation of interest.

The proposal in Abadie and Gardeazábal (2003) is an appealing data-driven procedure to build a control group for the study of policies imple-mented at country level. Its main idea is that a combination of countries isexpected to provide a better counterfactual for the treated country than asingle one. In the rest of this section, the model used by Abadie et al. (2010)to explain the applicability of synthetic controls in comparative case studiesis briefly described as well as its empirical implementation.

Assume that we have information about J + 1 (i = 1, . . . , J + 1) countriesduring T time periods. The first of them (i = 1) is the one to which theintervention analysed has been applied after a certain date T0 (1 � T0 < T).Therefore, we have J countries that can be labelled as potential controls. LetYit

N be the variable of interest observed in absence of policy intervention forcountry i at period t and Y t

I1 its corresponding values for the treated country

during the implementation period (t ∈ {T0 + 1, . . . , T}). Assuming that theintervention has no effect before its implementation, α1 1 1t t

ItNY Y= − is the

policy effect in the treated country. This allows us to express the observedoutcome Yit for country i in period t as:

Y Y D

Di t T

it itN

it it

it

= +

== >⎧

⎨⎩

α

1 1

00if and

otherwise

(1)

4 In fact, our case is the study of a no intervention policy. The difference is established by the group ofcomparison (the ‘donor pool’).



We want to estimate α1 1 1t t tNY Y= − , which is equivalent to estimating Y t

N1

.With this objective in mind, a factor model is specified for Yit

N:

Y ZitN

t i t t i it= + + +δ θ λ μ ε (2)

where: dt is an unknown common factor with the same effect on all countries;Zi(1 ¥ r) are the observed explanatory factors; qt(r ¥ 1) includes unknownparameters; lt(1 ¥ F) are the unobserved common factors; mi(F ¥ 1) are theunknown loadings of the unobserved common factors; and eit is the errorterm, assumed to have a zero mean for all i.

This structure is used to propose ˆ *α1 12

1

t t j jtj

J

Y w Y= −=

+

∑ as an estimator for a1t

(t ∈ {T0 + 1, . . . , T}), where wj* denotes the j - th element of a (J ¥ 1) vectorW* of weights. Therefore, an estimation of the counterfactual situation for thetreated country in the post-intervention period is obtained as a linear combi-nation of the outcomes in the potential controls:

ˆ * ; , ,Y w Y t T TtN

j jtj

J

1 02

1

1= ∈ +{ }=

+

∑ … (3)

This estimator will be unbiased if W* is obtained solving the followingoptimization problem:

min ( ) ( )W VX W X W V X W1 0 1 0 1 0− = − ′ −χ χ χ (4)

subject to the following constraints on the weights:

w j J

w w

j

J

* ; , ,

* *

≥ = +

+ + =+

0 2 1

12 1

for …

…(5)

where:

X Z Y Y

X X X X Z Y Y i

M

J i i i iM

1 1 11

1

0 2 3 11 2

= ′

= = =+

( , , , )

( , , , ); ( , , ); ,

…

… … …χ ,,

* , , * *

J

w Y Y w Y Y w Zj jj

J

j jM

j

JM

j jj

J

+

= = ==

+

=

+

=

+

∑ ∑ ∑

1

1

2

1

11

2

1

12

1

… and ZZ1

(6)

X1 is a (k ¥ 1) vector of pre-intervention (t � T0) characteristics in thetreated country, c0 its equivalent (k ¥ J) matrix for the potential controls andYi

1 , . . . , YiM are M linear functions of the outcomes before the policy was



implemented in a given country i satisfying M � F. V is a diagonal, positiveand semidefinite (k ¥ k) matrix determined by the predictive power of theexplanatory variables during the pre-intervention period.

In the application below, we assume the presence of a single unobservedcommon factor with different effects on each country and that the linearfunction of the pre-intervention outcomes in (6) is the simple average(M = F = 1). W in (4), conditional on V, is searched for among all the pos-sible combinations using a fully nested optimization procedure.5 Three dif-ferent starting points for V have been considered in order to avoid localminima: equal-weighted, regression-based and determined by maximumlikelihood.

The measure of FDI inflows from the US into a given country (Yi) willbe introduced in the following section. Moreover, a justification of the vari-ables included in the vector of observed explanatory factors (Zi) will also begiven in accordance with existing empirical studies and evidence about FDIdeterminants.

III. FDI Determinants: Data Sources and Variable Construction

Traditional theoretical models of FDI distinguished between vertical(Helpman, 1984) and horizontal (Markusen, 1984) motivations for the behav-iour of multinational enterprises. These two approaches were later reconciledin the ‘knowledge-capital’ model (see Markusen, 2002) and more complexstrategies have recently appeared in the literature (see Baltagi et al., 2007, fora review).

An empirical literature on FDI determinants has developed on the basis ofall these theoretical models. The exhaustive survey on this issue in Blonigen(2005) contains two ideas that will be useful for the purpose of this article.First, it is observed that FDI tends to be horizontal and between industrializedcountries. Second, a gravity specification fits cross-sectional FDI flows dataquite accurately.

The measure of FDI that will be analysed below is the American capitaloutflows to the United Kingdom and the potential control countries as apercentage of their GDP. These FDI flows data have been obtained from theBureau of Economic Analysis and refer to the period 1986–2006.6 Theyinclude equity capital transactions, reinvested earnings and intercompany

5 This methodology has been applied in the subsequent analysis using the Stata version of the relatedsoftware provided by Jens Hainmueller in his homepage.6 Two missing values for Portugal (1989 and 1990) and one for Spain (1995) have been interpolated usingthe TRAMO/SEATS Econometric Package.



debt transactions and are measured on an historical-cost basis.7 CurrentGDPs, in PPP terms, have been extracted from the World Bank’s WorldDevelopment Indicators database.

The variables used as FDI determinants have been selected according tothe modified gravity specification in Blonigen et al. (2007). First, the hostcountry’s GDP and population have been included in order to reflect itspotential market size. These data have also been extracted from the WorldDevelopment Indicators database. In addition, note that GDP data areexpressed in constant 2005 PPP terms. Openness has been included as ameasure of trade costs. It is equal to the sum of exports plus imports overGDP, is expressed in constant terms and has been extracted from the PennWorld Table (v.6.2). Educational skills in the host country have beenproxied by the average years of schooling for people over 25 from theBarro and Lee (2001) database.8 The distance to the United States has alsobeen considered and comes from the Centre d’Etudes, Prospectives etd’Informations Internationales. Finally, a variable reflecting the EU sur-rounding market potential of a country has also been included. For a givenyear, it has been calculated as an inverse-distance weighted-sum of theGDPs in other EU countries.

Summarizing, the variables of interest that will be analysed below are theAmerican FDI flows to a given country as a percentage of its GDP. Theexplanatory factors in Zi are the following variables referring to the hostcountry: constant GDP in PPP terms, population, distance to the UnitedStates, openness, educational skills and a measure of the EU surroundingmarket potential.

IV. Assessing the Effects on American FDI Flows to the UnitedKingdom Derived from Euro Non-adoption

Preliminary Analysis: Testing for a Break in Trend

Before applying the policy evaluation method to the FDI flows data, theirtime-series properties, both in the United Kingdom and its potential controls,have been analysed. The latter are the EU members in 1986 that joined the

7 This is the only way that detailed data by country are provided by the Bureau of Economic Analysis(BEA). As can be observed in Table 1, there are other databases from which American FDI outflows to agiven country can be obtained (Eurostat and International Direct Investment Database). However, the datacompiled by the BEA allow us to work with a balanced panel with the least need for interpolation andthe greatest number of potential controls.8 This variable is reported in the database every five years. Following Blonigen et al. (2007), it has beentransformed to a yearly frequency using linear interpolation.



third stage of the EMU in 1999.9 We test for the presence of a single break inthe trend of the American FDI inflows as a percentage of GDP. Three differenttechniques have been applied with this aim.

The first one is the SupF test for a structural change of unknown date inregression models developed by Andrews (1993). The second one follows Baiand Perron (1998) and determines whether or not a trend shift is present bythe use of information criteria. In order to apply these two methods, thedeterministic component has been considered to be made up of a constant anda trend. The statistical significance of a change in the coefficient of the latterterm is analysed. An interesting alternative technique has been recently pro-posed by Perron andYabu (2009). It consists of a powerful test for a structuralchange in the trend of a univariate time-series that does not depend on itsorder of integration. In line with the two methods previously described, it hasbeen applied looking for a structural change in slope. Structural break testingresults are found in Table 2.

The SupF test statistic for each country is reported in the second columnof Table 2. There is evidence of a break in the trend only for Belgium and theUnited Kingdom. These breaks are statistically significant at the 1 per centlevel. Therefore, the null hypothesis of no structural break cannot be rejectedin the other cases at a significance level smaller than or equal to 10 per cent.These findings are corroborated by the application of both the Akaike andSchwartz information criteria. Results from the application of the Exp test byPerron and Yabu (2009)10 are reported in the fourth column. In line with theresults presented above, they also give evidence of a structural change inslope for both Belgium and the United Kingdom at the 1 per cent significancelevel. In addition, the null of no break in trend is rejected for Portugal at the5 per cent significance level.

Perron and Zhu (2005) demonstrated that a consistent estimation of thebreak dates can be obtained by the minimization of the sum of squaredresiduals. This has been done for a regression of the analysed series on aconstant, a time trend and a slope shift dummy. Estimated break dates arepresented in the sixth column of Table 2. All of them are located at the end ofthe sample period analysed, the earliest being one corresponding to theUnited Kingdom which is suggested to be the year 2000. Break dates forBelgium and Portugal are 2003 and 2002, respectively.

Once the presence of structural breaks has been tested for and their datesdetermined, the corresponding trends have been fitted using OLS regressions.

9 The exception is Luxembourg due to the lack of educational skills data. Therefore, the EMU donor poolis made up of Belgium, France, Germany, Ireland, Italy, the Netherlands, Portugal and Spain.10 The author acknowledges Tomoyoshi Yabu for allowing the use of his code.



Tabl

e2:

Stru

ctur

alB

reak

inT

rend

Test

ing.

US

FDI

Flow

sto

Sele

cted

EU

Cou

ntri

es(%

GD

P),1

986–

2006

SupF

test

AIC

/B

ICE

xp test

SSR

Bre

akda

teC

onst

ant

Tren

d1Tr

end2

Bel

gium

12.8

2***

16.

48**

*4.

6520

030.

250.

030.

43**

Fran

ce0.

710

0.69

––

0.18

***

1·1

0-3–

Ger

man

y0.

560

-0.1

5–

–0.

050.

01**

*–

Ital

y4.

080

0.17

––

0.09

3·1

0-3–

Irel

and

0.12

0-0

.11

––

1.11

0.21

**–

Net

herl

ands

2.74

00.

03–

–0.

790.

08–

Port

ugal

1.12

02.

86**

0.39

2002

0.14

*2

·10-6

3·1

0-3

Spai

n0.

750

-0.0

6–

–0.

090.

01–

Uni

ted

Kin

gdom

40.6

8***

148

.97*

**7.

0520

000.

180.

13**

*-0

.38*

**

Sour

ce:A

utho

r’s

own

calc

ulat

ions

.N

ote:

***,

**an

d*

stat

istic

ally

sign

ifica

ntat

the

1,5

and

10%

leve

ls,r

espe

ctiv

ely.



The results are in the last three columns of Table 2. It can be appreciated thatall of them are upward trends except that followed by the series of FDI flowsto the United Kingdom after the shift in the year 2000. In the latter case, theslope coefficient is negative and highly significant.

Both the observed American FDI flows to a given country as a percent-age of its GDP and their estimated trends are plotted in Figure 1. While theAmerican FDI flows to the selected EMU countries have maintained, if notincreased, their upward trend, this has not been the case for the UnitedKingdom. This variable has, in fact, followed a decreasing path after thethird stage of EMU started. In addition, an important increase in the trendof the FDI flows to Belgium is also observed in the final years of thesample period. The significance and magnitude of the Portuguese trend shiftis lower.

Finally, it should be noted that some of the estimated upward trends couldbe approximated by a shift towards a higher level in the aftermath of the euro.This seems to be the case for Germany and Ireland,11 but could perfectly applyto the Netherlands and Spain.

Results from the Synthetic Control Approach

As pointed out before, an estimation of the American FDI flows into theUnited Kingdom that would have taken place if it had adopted the euro can beobtained through the application of the synthetic control method. This sub-section presents the results.

Weights assigned to each country in the EMU donor pool when construct-ing the synthetic United Kingdom are found in Table 3. The counterfactualsituation that best resembles the evolution of observed American FDI flowsinto Britain before the third stage of the EMU is built as a linear combinationof those received by four countries. Not surprisingly, the highest weightcorresponds to Germany (0.43). The other three countries from which thesynthetic United Kingdom has been constructed are the Netherlands (0.22),Ireland (0.18) and France (0.17).

Apart from the countries selected and the weights assigned to them inorder to construct the synthetic control, the suitability of the applied tech-nique in this context can also be inferred from Table 4. Average values of theFDI determinants in the period 1986–98 for the United Kingdom and its EMUsynthetic counterpart are shown in its second and third columns, respectively.It can be observed that the synthetic control has mean values for the explana-tory variables relatively close to those in the United Kingdom before 1999.

11 The Irish government set up aggressive fiscal measures in order to attract FDI.



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This is especially true with regard to educational skills. The biggest differencein relative terms corresponds to openness.

The main results obtained from the synthetic control approach are dis-played in Figure 2 where the evolution of the observed values for AmericanFDI flows to the United Kingdom and those corresponding to its syntheticcounterpart are plotted. As mentioned before, these flows followed an upwardtrend in the period 1986–99 reaching several peaks in the years 1989, 1993and 1999. However, this increasing trend was reversed in 2000. To give anidea of the extent of this fall, the share of FDI inflows as a percentage of GDPin 2001 was almost the same as that received in 1991. Moreover, it should benoted that the percentage of FDI inflows at the end of the pre-interventionperiod has never been equalled since then.

Estimated FDI flows for the synthetic United Kingdom also follow anupward trend after 1990. Furthermore, they closely resemble the evolution ofthose really observed. There is a little difference since their values are slightlylower than the real ones and the last peak is reached one year earlier. Contraryto the experience of observed American FDI flows to the United Kingdom,those corresponding to the synthetic control maintain the steadily increasingpath that began in 1990 instead of changing their trend after 1999. This

Table 3: Weights Assigned to Selected EMU Countries in Order to Construct theSynthetic UK

Belgium France Germany Ireland Italy Netherlands Portugal Spain

0 0.17 0.43 0.18 0 0.22 0 0Root Mean Square Prediction Error (RMSPE) = 0.63

Source: Authors’ own calculations.

Table 4: Mean Values for the FDI Determinants in the UK and Its SyntheticControl in the Pre-intervention Period (1986–98)

United Kingdom Synthetic United Kingdomfrom EMU countries

GDP 1.35 · 1012 1.23 · 1012

Population 5.76 · 107 4.83 · 107

Distance to the US 5901.34 6282.61Openness 44.01 68.67Education 8.86 8.86EU surroundingmarket potential

1.28 · 1010 1.13 · 1010




impression is confirmed by the three methods described in the previoussubsection.12 As a result, the share of FDI flows as percentage of GDPcorresponding to the synthetic United Kingdom constructed from EMU coun-tries is generally higher than that really observed from the year 2000 onwards.

The exception is the year 2005 when the synthetic control experiences asharp drop. Although something similar happened in the United Kingdom, themagnitude was smaller. As can be observed in Figure 1, the American FDIflows received by several EMU countries also fell that year. These reductionswere especially important for Ireland and the Netherlands, but their causeswere different. While, in Ireland, it was a consequence of the reduction in theindebtness of Irish affiliates to their American parents, the fall in the Nether-lands was driven by the fact that reinvested earnings turned highly negative –a consequence of tax incentives provided by the American Job Creation Actof 2004 (Koncz and Yorgason, 2006). Moreover, it should be noted that thisdata point is considered to be an additive outlier13 in the corresponding

12 Obtained statistics are 1.42 and 0.30 for the supF and Exp tests, respectively. In neither of these two casescan the null of no structural break be rejected at a significance level lower than 10 per cent. Theseconclusions are corroborated by the Akaike and Schwartz information criteria.13 An aberrant data point with a cause outside the intrinsic economic environment that generates the timeseries data (Franses and Van Dijk, 2000).

Figure 2: US FDI Flows to the UK (% GDP, Bold) and Synthetic Control Constructedfrom Selected EMU Countries (Dotted)

3

2

1

0

−1

−21986 1991 1996 2001 2006




time-series of these two countries by the detection procedure proposed inChen and Liu (1993). This conclusion also applies to the synthetic UnitedKingdom and is reasonable since Ireland and the Netherlands account for 40per cent of it. However, this test does not detect any additive outlier in theobserved FDI flows to the United Kingdom.

The highest negative difference between the observed American FDI flowsinto the United Kingdom and those predicted by the synthetic control corre-sponds to the final year of the period analysed. While American FDI flows tothe United Kingdom represented 0.98 per cent of its GDP, the percentage forthe synthetic control was 2.78 per cent. This is equivalent to saying that thepolicy evaluation method applied suggests that British FDI inflows from theUnited States in 2006 are around 65 per cent lower than if the country hadadopted the euro. Taking into account the whole post-EMU period, the gapbetween the trends followed by the FDI flows to the United Kingdom and itssynthetic control increases after 2000. The average decrease for the years2000–06 is 15.40 per cent.14

It can be concluded from the results presented above that the decision notto join the third stage of the EMU has had an important negative effect onBritish inward investment from the United States in comparison to the 1986EU members that joined the European single currency in 1999. These resultscontrast with those by Schiavo (2007) who did not find any adverse effect onthe FDI flows received by the United Kingdom. This might be related both tothe different time span (1980–2001) and the origin of the FDI flows (OECDcountries) considered. However, the magnitude of this estimated effect is inline with the fall in the share of American flows into the EU corresponding tothe United Kingdom reported by Barr et al. (2003) until the year 2001 and theshare of FDI inflows from non-EMU countries into Britain as a percentage ofits GDP until 2003 in Taylor (2008).15 An important difference betweenTaylor’s article and this one is that he uses estimations up to a certain date inorder to construct counterfactual scenarios for future time periods. A casestudy seems to be a more appropriate framework with which to estimatecausal effects derived from a certain event. Moreover, the synthetic controlmethod applied in this article is valid under more flexible conditions thanalternative techniques like the differences-in-differences approach used inPetroulas (2007).

14 This average negative impact increases to 36.15 per cent if the outlier in 2005 is neglected.15 The average gap predicted by the synthetic control method after 1999 is equal to -25.48 per centuntil 2001 and -30.13 per cent until 2003. These figures should be compared with those reported inTable 1.



Evaluating the Robustness and Significance of the Estimated Effects

I should begin by noting that the use of total GDP as an FDI flows determinantwhen applying the synthetic control policy evaluation method could raiseconcerns. This is because this variable might have been affected by the policyintervention analysed and, hence, endogeneity problems could arise. As analternative, the same analysis as before has been carried out using GDP percapita. The reason is that this variable should be less influenced by the EMUthan total GDP itself. The results from this robustness check do not signifi-cantly change with respect to those previously presented.16 The first differ-ence found is that Belgium replaces France as a country from which thesynthetic control is constructed. Germany reduces its weight and represents62 per cent with Belgium. The remaining 38 per cent is also distributed evenlybetween Ireland and the Netherlands. In spite of this change in the composi-tion of the synthetic control, its evolution during the whole sample period isvery similar to that displayed in Figure 2. As was also the case before, theaverage estimated negative gap in 2000–06 is equal to 15 per cent with thisalternative specification.

One way of testing for the significance of the differences between theobserved series for the country studied and its synthetic control is by apply-ing the Matched-Pairs Signed-Ranks test by Wilcoxon (1945). This non-parametric test between two related samples is often used to compare scoresof data collected before and after an experimental manipulation. It is analternative to the paired Student’s t-test when the data cannot be assumed tobe normally distributed. Under the null hypothesis, the median of the differ-ences is expected to be zero. In our context, instead of comparing individuals,the observational units will be time periods.

Results obtained from the comparison of the observed values for AmericanFDI flows to the United Kingdom as a percentage of its GDP and thosepredicted by the synthetic control method are shown in Table 5. When con-sidering the whole post-intervention period, the null hypothesis cannot berejected at the 10 per cent significance level. Although this test can be usedwith sample sizes as small as the case analysed here, it is expected to have lowpower. This could be exacerbated in the presence of outliers. Because of this,the test has been applied to the whole post-intervention period excluding theyear 2005. Now, the null hypothesis of a median difference equal to zero isrejected at the 5 per cent significance level. Therefore, these findings allow usto state that the predicted values for American FDI flows to the UnitedKingdom by the synthetic control are significantly different to those reallyobserved in most of the years after the euro started.

16 Further details are available from the author upon request.



As an alternative, the observed FDI flows can be compared with theestimated trend of their synthetic control. These results are plotted in Figure 3.Bands representing �2 times the standard deviation of the estimation errorsare also reported. The observed flows are inside the bands in most of thepre-intervention period. The values outside the limits are always above theupper band and correspond to the peaks of the years 1989, 1993 and 1999. Inaddition, the FDI flows are generally above the trend because the estimatedslope for the synthetic control is less steep than that of the observed flowsbefore the break. These findings change in the post-intervention period, whenobserved FDI flows are systematically below the estimated trend after 2000.Moreover, they fall below the lower band in all the years except 2003 and 2004.

Table 5: Wilcoxon Matched-Pairs Signed-Rank Test. Differences betweenObserved US FDI Flows to the UK (% GDP) and Its Synthetic Control

Post-interventionperiod

Number of observations W+ W- Test statisticPositive Negative Total

All 2 5 7 8 20 -1.01Except 2005 1 5 6 1 20 -1.99**

Source: Author’s own calculations.Note: ** Statistically significant at the 5% level.

Figure 3: US FDI Flows to the UK (% GDP, Bold) and Fitted Trend for the SyntheticControl Constructed from Selected EMU Countries (Dotted, � 2 · serror Bands)

3.5

2.5

1.5

0.5

−0.51986 1991 1996 2001 2006




Nonetheless, they are very close to the lower limit in these two cases. Finally,it should also be noted that Figure 3 reflects the divergent trend followed afterthe start of the third stage of the EMU by the American FDI flows in the UnitedKingdom and that predicted by the policy evaluation method.

Summarizing, it can be concluded that the results presented throughoutthis subsection corroborate the robustness and significance of the estimatednegative effect on the FDI flows from the United States received by the UnitedKingdom after the launch of the euro derived from its decision to stay out.

Conclusions

This article has shown evidence of a structural break in the trend of FDI flowsreceived by the United Kingdom from the United States after the start of thethird stage of EMU. This break led the FDI flows to turn their upward trendin 2000 into a decreasing path. More interestingly, this observation is onlyfound for this country of all the selected countries that had been EU memberssince 1986. All these countries, that later joined the EMU, have maintained,if not increased, their upward trends.

The results obtained from the application of a synthetic control methoddesigned for policy evaluation suggest that, on average, the American FDIflows to the United Kingdom as a percentage of its GDP have been 15 per centsmaller than if this country had adopted the euro after 1999. The estimatedmagnitude of this effect is much higher in some periods, reaching 65 per centin the final year of the sample analysed.

The significance of the estimated effects has been analysed using formalstatistical tests. Moreover, its magnitude has been adequately compared andintegrated into the literature analysing the effects of the EMU on FDI. I findthat it is similar to some of those already established for FDI flows in theUnited Kingdom from the United States and other non-EMU countries. Inaddition to the wider sample period analysed, the main difference is that thisarticle uses a methodology that allows us to estimate causal effects undermore flexible conditions than alternative policy evaluation methods used inprevious studies.

Correspondence:Marcos Sanso-NavarroDepartamento de Análisis EconómicoFacultad de Ciencias Económicas y EmpresarialesGran Vía, 2. 50005, Zaragoza (Spain)Tel (+34) 976761000 Ext. 4629. Fax (+34) 976761996email [email protected]. Homepage http://dae.unizar.es/marcossn/index.html.



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