journal of common market studies, 2011

8/13/2019 Journal of Common Market Studies, 2011

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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 can

be 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 foreign

direct investment received by this country. This is done by the application of a

synthetic control method designed for policy evaluation. As a result, evidence of a

significant cost in terms of inward foreign direct investment from the United States is

obtained.

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(Bartramet al., 2007), firms investment rates (Bris et al., 2006), trade flows

(Baldwin and Taglioni, 2007; Brouweret 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 Educacin y Ciencia (SEJ2006-14397 project) and the Regional Government of Aragn(ADETRE Research Group) is acknowledged.

JCMS 2011 Volume 49. Number 2. pp. 463483

DOI: 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


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2008; De Sousa and Lochard, forthcoming). This article aims to contribute to

the 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 Majestys 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 ofthe United Kingdoms 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 recently

established 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(Barret 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 Gardeazbal, 2003; Abadie et al., 2010) that is

1 Particularly thinking of the Citys 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


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suitable for the evaluation of policy measures implemented at a country

level.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 Britains inward

FDI 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 Majestys Treasury, 2003), it was recognized that Britainsshare 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 19992001 withrespect to the two previous years. Another study reaching the same conclu-sion is Begget al. (2003). Furthermore, Barret 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



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Table1:Summa

ryoftheLiteratureExami

ningEMUEffectsonFDI

Authors

FDImeasure

Datasources

Sample

period

Home

countries

Host

countries

Methodology

EM

U

effect

(%)

Layardetal.

(2002)

ShareofflowsintoEU

European

Commission

andEuros

tat

19972001

A

ll

UK

Descriptiveanalysis

-5

4

Barretal.

(2003)

ShareofstocksinEU

UNCTAD

19982001

A

ll

UK

Descriptiveanalysis

-1

1

ShareofUSflowsinto

EU

Bureauof

Economic

Analysis

19982001

U

S

UK

-2

9

Beggetal.

(2003)

ShareofflowsintoEU

Eurostat

19982001

A

ll

UK

Descriptiveanalysis

-6

0

A

ll

EMU

7

5

HerMajestys

Treasury(2003)

ShareofflowsintoEU

UNCTAD

19992001

A

ll

UK

Descriptiveanalysis

-4

3

Eurostat

19982001

N

on-EU

UK

-5

0

Shareofflowswithin

EU

Eurostat

19952001

E

U

UK

Noeffect

DeSousaand

Lochard(2009)

Bilateralstocks

InternationalDirect

19922005

E

MU

EMU

Gravityspecification

Panelwithinestimation

3

1

Investmen

tDatabase

6

2

Bilateralflows

Petroulas(2007)

Inwardflows

Eurostat

19922001

E

MU

EMU

Gravityregressions

Differences-in-differences

1

6

E

MU

Non-EMU

1

1

N

on-EMU

Non-EMU

8

Schiavo(2007)

Bilateralflows

InternationalDirect

Investmen

tDatabase

19802001

O

ECD

EMU

Gravityspecification

Fixedeffectspanelestimation

Tobit

model

Positive

E

MU

EMU

Positive

O

ECD

UKand

Denmark

Noeffect

Brouweretal.

(2008)

Outwardstocks

InternationalDirect

Investmen

tDatabase

19902004

O

ECD

EUentrants

in2004

Error-componentgravitymodels

Simulatedscenarios

18.5

30

Taylor(2008)

Bilateralflows

Eurostat

19942003

E

MU

EMU

Descriptiveanalysis

80282

N

on-EMU

EMU

227517

Flowsas%ofGDP

19802003

E

MU

EMU

Extrapolatedlog-lineartrends

-1270

N

on-EMU

EMU

95263

OECDandUKOfficeof

NationalStatistics

E

MU

UK

11

2

N

on-EMU

UK

-2

8

Source:Authorsow

ndata.




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Lochard (forthcoming) developed a theoretical model for bilateral FDI stocks

that 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 19922005 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 19922001 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 even

after controlling for exchange rate volatility in an empirical linear gravitymodel. The sample consisted of 22 OECD countries in the period 19802001.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 19902004, the simulated

effects were between 18.5 and 30 per cent.A recent exhaustive analysis using several data sources and a time span of

more 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 Britains inflows from countries otherthan the EUmembers were 28per cent below trend after the introduction of theeuro. The main caveat is that this author calculated these trends with data priorto 1999using log-linear trends froma standardOLS fit. Resulting estimates areused as a counterfactual for the subsequent years. In addition, there are noinferences about the significance of the reported effects.




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This article aims to contribute to this literature by assessing the effects of

the 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 Gardeazbal (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 Abadieet 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 aboutJ+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

1 10

0if andotherwise

(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).




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We want to estimate 1 1 1t t tNY Y= , which is equivalent to estimating YtN1 .With this objective in mind, a factor model is specified for YitN:

Y ZitN

t i t t i it = + + + (2)

where:dtis an unknown common factor with the same effect on all countries;Zi(1 r) are the observed explanatory factors; qt(r1) includes unknownparameters;lt(1 F) are the unobserved common factors; mi(F1) are theunknown loadings of the unobserved common factors; and eitis the errorterm, assumed to have a zero mean for all i.

This structure is used to propose *1 12

1

t t j jt

j

J

Y w Y= =

+

as an estimator for a1t(t{T0+1, . . . ,T}), where wj*denotes thej- thelement of a (J1) 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:

* ; , ,Y w Y t T T tN

j jt

j

J

1 0

2

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 = (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

=

= = =+

( , , , )

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

,,

* , , * *

J

w Y Y w Y Y w Z j jj

J

j jM

j

J

Mj j

j

J

+

= = ==

+

=

+

=

+

1

1

2

1

11

2

1

1

2

1

and ZZ1

(6)

X1 is a (k1) vector of pre-intervention (t T0) characteristics in thetreated country,c0its equivalent (k J) matrix for the potential controls and

Yi1 , . . . , Yi

M are Mlinear functions of the outcomes before the policy was




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implemented in a given countryisatisfyingM F.Vis a diagonal, positive

and 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). Win (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 Vhave 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 Baltagiet 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 19862006.6 They

include 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.




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debt transactions and are measured on an historical-cost basis.7 Current

GDPs, in PPP terms, have been extracted from the World Banks WorldDevelopment Indicators database.

The variables used as FDI determinants have been selected according tothe modified gravity specification in Blonigen et al. (2007). First, the hostcountrys 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 dEtudes, Prospectives etdInformations 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 the

GDPs in other EU countries.Summarizing, the variables of interest that will be analysed below are the

American 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.




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third stage of the EMU in 1999.9 We test for the presence of a single break in

the 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 and Yabu (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 cent

level. 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.




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Table2:StructuralBreakinTrendTesting.USFDIFlowstoSelectedEUCountries(%GDP),

19862006

SupF

test

AIC/B

IC

Exp

test

SSR

Break

date

Constant

Trend1

Trend

2

Belgium

12.82***

1

6.48***

4.6

5

2003

0.25

0.03

0.43**

France

0.71

0

0.69

0.18***

110-3

Germany

0.56

0

-0.15

0.05

0.01***

Italy

4.08

0

0.17

0.09

310-3

Ireland

0.12

0

-0.11

1.11

0.21**

Netherlands

2.74

0

0.03

0.79

0.08

Portugal

1.12

0

2.86**

0.3

9

2002

0.14*

210-6

310

-3

Spain

0.75

0

-0.06

0.09

0.01

UnitedKingdom

40.68***

1

48.97***

7.0

5

2000

0.18

0.13***

-0.38***

Source:Authorsow

ncalculations.

Note:***,**and*

statisticallysignificantatthe1,5

and10%levels,respectively.




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The results are in the last three columns of Table 2. It can be appreciated that

all 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 ApproachAs 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 flows

into 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 198698 for the United Kingdom and its EMU

synthetic 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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Figure1:USFD

IFlowstoSelectedEUC

ountries(%GDP,Bold)an

dEstimatedTrend(Dotted

)

Source:Authorsow

ncalculations.




14/21

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 synthetic

counterpart are plotted. As mentioned before, these flows followed an upwardtrend in the period 198699 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 an

upward 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 the

Synthetic UK

Belgium France Germany Ireland Italy Netherlands Portugal Spain

0 0.17 0.43 0.18 0 0.22 0 0

Root Mean Square Prediction Error (RMSPE)=0.63

Source: Authors own calculations.

Table 4: Mean Values for the FDI Determinants in the UK and Its Synthetic

Control in the Pre-intervention Period (198698)United Kingdom Synthetic United Kingdom

from EMU countries

GDP 1.35 1012 1.23 1012

Population 5.76 107 4.83 107

Distance to the US 5901.34 6282.61

Openness 44.01 68.67

Education 8.86 8.86

EU surrounding

market potential

1.28 1010 1.13 1010





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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 a

sharp 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 this

data 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 Constructed

from Selected EMU Countries (Dotted)

3

2

1

0

1

2

1986 1991 1996 2001 2006





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time-series of these two countries by the detection procedure proposed in

Chen 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 years200006 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 on

British 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 (19802001) 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 Barret al. (2003) until the year 2001 and theshare of FDI inflows from non-EMU countries into Britain as a percentage of

its GDP until 2003 in Taylor (2008).15 An important difference betweenTaylors 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.




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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 200006 is equal to 15 per cent with thisalternative specification.

One way of testing for the significance of the differences between the

observed 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 Students 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 is

rejected 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.




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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 representing2 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 the

upper 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, theyfall below the lower band in all the years except 2003 and 2004.

Table 5: Wilcoxon Matched-Pairs Signed-Rank Test. Differences between

Observed US FDI Flows to the UK (% GDP) and Its Synthetic Control

Post-intervention

period

Number of observations W+ W- Test statistic

Positive Negative Total

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

Source: Authors own calculations.Note: ** Statistically significant at the 5% level.

Figure 3: US FDI Flows to the UK (% GDP, Bold) and Fitted Trend for the Synthetic

Control Constructed from Selected EMU Countries (Dotted, 2 serrorBands)

3.5

2.5

1.5

0.5

0.51986 1991 1996 2001 2006





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