impact of preferential trade agreements on fdi

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Beyond Trade: The Impact of Preferential Trade

Agreements on FDI Inflows

DENIS MEDVEDEV *

The World Bank, Washington, DC, USA

Summary. This paper investigates the effects of preferential trade agreements (PTAs) on net FDI inflows of member countries using acomprehensive database of PTAs in a panel setting. PTA membership is associated with a positive change in net FDI inflows and FDIgains increase with the market size of PTA partners and their proximity to the host country. The estimated relationship is driven by thedeveloping countries in the sample and agreements signed in the late 1990searly 2000s, a period when the majority of deep integrationPTAs have been advanced. 2011 Elsevier Ltd. All rights reserved.

Key words preferential trade agreements, foreign direct investment (FDI), world

1. INTRODUCTION

The prospects of increased foreign direct investment (FDI)are generally recognized as some of the more important rea-sons for entering preferential trade agreements (PTAs). Forexample, many observers viewed the expected post-NAFTAincrease in cross-border investment inflows as the main moti-vation of the agreement for Mexico (see Lederman, Maloney,& Serven, 2005, chap. 4). However, while the trade outcomesof PTAs have received extensive attention in the theoreticaland empirical literature, the link between PTAs and FDI isless well understood. This paper aims to add to the emerging

literature on the impacts of PTAs on FDI by combining anextensive sample of PTAs with a set of FDI determinants ina panel data framework.

The papers contribution is the identification of an empiricalrelationship between preferential liberalization and FDI in-flows through the size of the extended common market createdby a PTA and the average distance to the preferential tradingpartners. Although the increase in FDI inflows through join-ing a larger common market has already been identified inthe literature, the results have so far been limited to a fairlysmall sample of countries and PTAs. This paper aims tobroaden this result to nearly all countries and agreements inexistence, and also establishes an important role of distanceto ones preferential trading partners as a determinant of

FDI. Moreover, the paper identifies differential effects fordeveloping and developed PTA members, as well as for the1980searly 1990s and late 1990searly 2000s (the latter beingthe period when most deep integration PTAs have beensigned).

The paper is structured as follows. It begins with Section 2,which provides a brief review of the existing theoretical argu-ments and the empirical evidence on the relationship betweenPTAs and FDI. Section 3 estimates an empirical link betweenpreferential liberalization and net FDI inflows by country in alarge panel of high income and developing nations over thelast two decades. It also confirms the robustness of this rela-tionship to controlling for additional determinants of FDIand decomposes the FDI effect by time period and incomelevel of the host country. Section 4 provides the concluding

remarks.

2. THEORETICAL LINKS AND EMPIRICAL EVI-DENCE

The various ways in which preferential liberalization may af-fect FDI could be grouped into four distinct categories: the ef-fects of investment and other non-trade provisions (whichhave become more common in recent deep integrationPTAs), the effects of changes in trade flows, creation of an ex-tended market, and long-term growth effects. Table 1 summa-rizes these effects along with their transmission channels and aselection of papers identifying the impacts (although in mostpapers, the specific case of preferential liberalization is not

considered).With regard to the impact of non-trade provisions the most

relevant paper is Adams, Dee, Gali, and McGuire (2003), whostudied the impact of PTAs on stocks of outward FDI for apanel of high income and developing countries between 1988and 1997. The authors found that thedeep integration pro-visions of PTAs (investment, liberalization of trade in services,setting and harmonization of standards, competition policy,customs cooperation, dispute settlement, and IPR protection)were an important driver of FDI in five of the nine PTAsexamined. Moreover, the authors argue that the deep integra-tion provisions of these agreements have had a greater impacton FDI than the trade provisions. Other studies have alsolinked aspects of deep integration to increased FDI,

although not necessarily in the context of PTAs. For example,Lee and Mansfield (1996) and Maskus (1998) identify a posi-tive relationship between US-sourced FDI and IPR, but theresults are tentative and, for the latter paper, limited to devel-oping countries. 1 To the extent that PTAs can lower politicalrisk by locking-in reforms and improving the investment cli-mate, the results of Kolstad and Tondel (2002), who find apositive association between low political risk and largerFDI per capita in a cross-sectional study of 120 developingand industrialized countries, are also relevant.

* I am grateful to Robert Blecker, Jeffrey Lewis, Kara Reynolds, Hans

Timmer, and two anonymous referees for valuable comments and sugg-

estions and to Michiel Paris for excellent research assistance. All remai-

ning errors are my own. Final revision accepted: April 3, 2011.

World Development Vol. xx, No. x, pp. xxxxxx, 2011 2011 Elsevier Ltd. All rights reserved.

0305-750X/$ - see front matter

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Please cite this article in press as: Medvedev, D. Beyond Trade: The Impact of Preferential Trade Agreements on FDI Inflows, WorldDevelopment (2011), doi:10.1016/j.worlddev.2011.04.036
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Moving to the relationship between investment and tradeflows, the early literature on the subject conceptualizedthe two as different modes of reaching foreign markets(Blomstrom & Kokko, 1997). Chapter 3 of World Bank(2002) cites studies confirming that high tariff rates on im-ported goods induced FDI inflows into the United Kingdom(Dunning, 1958), Canada (Horst, 1972), and Australia (Brash,

1966). If FDI is indeed tariff-jumping, these studies wouldsuggest that preferential liberalization removes incentives toinvest. On the other hand, more recent literature (e.g., Caves,1996; Markusen, 2002; Globerman, 2002) has emphasized thecomplementarities between trade and investment owing to thegrowing importance of MNE production networks andintra-industry and intra-firm trade. This view is supportedby a review of cross-country regressions on the determinantsof FDI by Chakrabarti (2001), who notes that after marketsize, openness to trade has been the most reliable indicatorof the attractiveness of a location for FDI (see also Kolstad& Tondel, 2002). Thus, the net change in FDI flows as a resultof preferential trade liberalization could be either positive ornegative, depending on the type of FDI and whether PTAs

are on average trade-creating or trade-diverting.While the direction of the relationship between trade andFDI may be unclear, the connection between host market sizeand FDI is well established. In a literature review, Lim et al.(2001) cites both survey and econometric evidence that con-firms market size as the most robust determinant of FDI. Infact, virtually all studies of FDI find a highly significant posi-tive effect of the size of the host market on FDI inflows (seealso Kolstad & Tondel, 2002; Chakrabarti, 2001). To the ex-tent that a PTA creates an extended market through closerintegration of PTA partners, this channel suggests a positiverelationship between PTAs and FDI. Blomstrom and Kokko(1997) argue that this effect works through increased firmsizea larger market may allow some firms to grow beyondwhat they would have been able to achieve in segmented na-

tional markets, or the competitive pressures of a larger mar-

ketplace may force some firms to expand through mergersand acquisitions of former competitors. 2

In addition to the more static channels above, PTAs mayalso affect FDI through more dynamic means by generatingadditional growth. The complementarities between FDI andgrowth have been well documented in the empirical literature.A number of studies, including World Bank (2001) and

UNCTAD (1998), have shown that, controlling for other fac-tors, FDI flows are positively associated with economicgrowth. Unfortunately, the direction of causation is not clear:while a large literature documents the growth-enhancingknowledge and efficiency spillovers from FDI (see, e.g., thereview in Lim et al., 2001), other studies, most notably Ro-drik (1999), have suggested that FDI tends to be located inmore productive and faster-growing economies. Althoughthe link between PTAs and growth is much more tentative,Berthelon (2004) does find a positive correlation betweenregional integration and growth in a panel of high incomeand developing countries between 1960 and 1999 with thecaveat that the relationship is significant only for the largercountries in the sample.

Overall, the studies cited above and in Table 1 suggest thatthere are multiple channels through which PTAs could affectFDI. However, they do not answer the question of what couldbe the average or expected effect of preferential liberalizationon FDI as this would depend on which individual channelsare present for each country and agreement as well as on theinteractions between these channels. Clearly, the sign andstrength of the final impact as well as its persistence in thepresence of other determinants of FDI is an empirical ques-tion. In this regard, the empirical work on the relationship be-tween PTAs and FDI can be separated into two maincategories: case studies/time series analysis of large, well-known agreements (such as the European Union, NAFTA,or MERCOSUR) and, more recently, analysis using paneldata. A selection of most relevant studies and their main find-

ings are summarized in Table 2.

Table 1. Potential links between preferential liberalization and FDI

Impact area Transition channel Evidence

Services liberalization,investment, and other non-trade provisions

PTA provisions related to services andinvestment can directly stimulate FDI

Adams et al. (2003) find a significant impact of non-tradeprovisions on investment flows

Increased IPR protection in some PTAs maystimulate FDI

Lee and Mansfield (1996) and Maskus (1998) find apositive relationship between FDI and IPR, but

Mansfield (1993), Maskus and Eby-Konan (1994), andPrimo Braga and Fink (1998) cannot establish any link

PTAs may lower political risk by improving theinvestment climate and therefore stimulate FDI

Kolstad and Tondel (2002) find a positive associationbetween low political risk and larger FDI per capita

Merchandise tradeliberalization

Trade and investment are substitutes (tariff-jumping FDI)

High tariff rates on imported goods induced FDI inflowsinto the United Kingdom (Dunning, 1958), Canada(Horst, 1972), and Australia (Brash, 1966)

Trade and investment are complements Markusen (2002) and Globerman (2002) show a positiveassociation between trade and FDI based on MNEproduction structure

Extended market PTAs could st imulate FDI by creating a largerhost market

Lim et al. (2001) cites both survey and econometricevidence that confirms market size as the most robustdeterminant of FDI (see also Kolstad and Tondel, 2002;Chakrabarti, 2001)

Growth PTAs may accelerate growth, which in turn

attracts FDI

World Bank (2001), UNCTAD (1998), and others show

that, controlling for other factors, FDI flows arepositively associated with economic growth, whileBerthelon (2004) finds a positive correlation betweenregional integration and growth

2 WORLD DEVELOPMENT

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Studies of individual agreements generally find an increasein FDI following preferential liberalization. This has been doc-umented for Spain and Portugal after EU accession (Limet al., 2001; Lederman et al., 2005), Brazil and Argentina afterMERCOSUR (Blomstrom & Kokko, 1997; Lim et al., 2001;Chudnovsky & Lopez, 2001), Mexico after NAFTA (Limet al., 2001; Lederman et al., 2005; Monge-Naranjo, 2002),and Canada (Blomstrom & Kokko, 1997; Buckley, Clegg,Forsans, & Reilly, 2000; Globerman, 2002) after CUFTA

and NAFTA. Similarly, the implementation of the EU Inter-nal Market Program (IMP) in 1986 led to an increase in in-tra-EU FDI (Pain, 1997; Pain & Lansbury, 1997). However,the same studies caution that the increase is not automatic(e.g., Lederman et al. (2005) find no accession impact forGreece) and that in a number of instances the increase wasessentially a one-time stock adjustment (e.g., Lederman et al.(2005) and Monge-Naranjo (2002) for Mexico). In some cases,these studies also find that the FDI responded more to theconcurrent policy reforms rather than the preferential liberal-ization per se. For example, Graham and Wada (2000) showthat US FDI to Mexico began to grow rapidly in the late1980s, much earlier than the implementation of NAFTA,and attribute the increase to Mexicos unilateral policy re-forms. For MERCOSUR, Blomstrom and Kokko (1997)

show that extra-PTA FDI responded more strongly to the

macroeconomic stabilization programs than the early stagesof the Southern Cone project, although the creation of the cus-toms union during the later stages was associated with largeFDI gains.

Results of cross-country analyses support the positive asso-ciation between preferential liberalization and FDI identifiedby the individual agreement studies above. Using gravity-typeapplications, Levy Yeyati, Stein, and Daude (2003) andAdams et al. (2003) find positive effects of preferential liberal-

ization on bilateral FDI stocks. Turning to net effects, bothLederman et al. (2005) and Jaumotte (2004) find a positive ef-fect of extended market size on FDI inflows and FDI stocks,respectively. In the case of Lederman et al. (2005), the authorsfind an insignificant coefficient on the PTA membership dum-my but a significant positive effect of the expectation of joininga PTA and the size of common market; the former increasesFDI flows by more than one-third, while joining a commonmarket twice as large as the host country can raise FDI flowsby 20% or more.

Regarding the contributions of different transmission chan-nels identified in Table 1, Adams et al. (2003) and Blomstromand Kokko (1997) provide some evidence to support theinvestment provisions/non-trade channel. In many cases theadditional investment originates from outside the PTA, giving

support to the trade and extended market size hypotheses (the

Table 2. Empirical evidence on the impact of preferential liberalization on FDI

Methodology Paper Findings

Case studies/time seriesanalysis

Lim et al. (2001) FDI-to-GDP more than doubled in the four-year post-PTA period forPortugal and Spain (EU accession), Brazil (MERCOSUR), and Mexico(NAFTA), and increased by 70% for Argentina (MERCOSUR)

Lederman et al. (2005) Similar to Lim et al. (2001) for Spain and Portugal, but no change in FDIinflows for Greece following EU accession. FDI into Mexico increased in

the first two years following NAFTA, but leveled off soon afterwards,similar to a stock adjustment experienced by the new EU entrants

Pain (1997) Sharp increase in intra-EU FDI following the implementation of theInternal Market Program in 1986

Pain and Lansbury (1997) Similar to Pain (1997) for German investment into the rest of the EuropeanUnion

Blomstrom and Kokko (1997) Intra-PTA FDI into Canada declined following the CanadaUSA FTA(CUFTA), but extra-PTA FDI increased just enough to offset the decrease.In the United States, net FDI rose as a result of CUFTA, but this wasachieved through a large increase in FDI from outside CUFTA. Extra-PTAFDI responded more strongly to the macroeconomic stabilizationprograms than the early stages of MERCOSUR, but subsequent deeperintegration with the establishment of the customs union resulted insignificant increases in the US investment position

Globerman (2002) Following CUFTA and subsequently NAFTA, European FDI to Canada

increased much more than FDI from the United StatesBuckley et al. (2000) US FDI into Canada was encouraged by CUFTA and NAFTAMonge-Naranjo (2002) Positive effect of NAFTA on US-sourced FDI in Mexico only during the

first twothree years of the agreementChudnovsky and Lopez (2001) MERCOSUR led to a significant increase in FDI, but most of it came from

outside the PTA

Panel analysis Yeyati et al. (2003) Joining a PTA increases bilateral FDI stocks between members by 27%,while a larger common market affects hosts FDI with an elasticity of 0.1

Adams et al. (2003) Six of the nine sample PTAs (including the European Union) areinvestment-creating, one investment-diverting, and two have no observableimpact

Lederman et al. (2005) The expectation of joining a PTA can increase FDI flows by more than one-third, while joining a common market twice as large as the host country canraise FDI flows by 20% or more

Jaumotte (2004) Significant positive effect of the beginning-of-period extended market sizeon end-of-period FDI stocks

BEYOND TRADE: THE IMPACT OF PREFERENTIAL TRADE AGREEMENTS ON FDI INFLOWS 3

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latter is identified explicitly by Yeyati et al. (2003), Ledermanet al. (2005), & Jaumotte (2004)). No studies have attemptedto focus on the growth channel, and the empirical identifica-tion is likely to be very difficult due to the large number of po-tential growth determinants.

A major shortcoming of the existing studies lies in theirsmall sample sizes, both in terms of country coverage and

the number of PTAs considered. The latter is a particularhandicap, since the coefficient on the extended market variablewill be significantly biased if only some PTAs of which a par-ticular country is a member are included. Furthermore, allexisting studies focus on large, well-known agreements, and,therefore, address neither the question of the average or ex-pected impact of PTAs on FDI, nor the FDI gains that anew signatory to a PTA may expect to receive. In contrast, thispaper explicitly takes into account all PTAs in existence bydrawing on an extensive database of both WTO-notified andun-notified PTAs (Medvedev, 2010). 3 Moreover, this paperuses the largest sample of countries (153) of all existing studies,therefore, making an attempt at covering both the universe ofcountries and PTAs in order to identify whether and how theexplosion in the number of PTAs over the last twenty-some

years has affected the evolution of FDI flows.

3. MODEL SETUP AND ESTIMATION RESULTS

(a) Baseline model

This section estimates an empirical relationship betweenpreferential trade liberalization and net FDI inflows using apanel of 153 countries over the 19802004 period. 4 Net FDIinflows correspond to the increase in holdings of foreign enter-prises inside a country less the decreases in domestic assetholdings by the same enterprises. 5 The choice of the depen-dent variable is driven by both theory and data considerations.

Globerman and Shapiro (2002) point out that the use of FDIflows is preferable to stocks because the calculation of FDIstocks is often not homogeneous across countries and, tothe extent that inward and outward FDI have been going onfor a long time, recent and relatively large changes in FDIbehavior may not be apparent if FDI stock figures are used.The choice of net FDI inflows as the dependent variable pre-cludes the estimation of bilateral flows, but these data arequite scarce and usually limited to high income countries asthe FDI source; thus, the use of total net FDI inflows allowsfor inclusion of a larger number of countries and also implic-itly takes into account South-South FDI flows.

The set of country-level control variables is similar to thoseused in Lederman et al. (2005): to PTA membership, the log ofnet FDI inflows into country i in time period t is a function of

that countrys size, openness, rate of growth, and inflation.6

With regard to market size, Chakrabarti (2001) cites over adozen papers that found a positive effect of market size (de-fined as absolute GDP, GDP per capita, GNI, or GNI percapita) on FDI and concludes that market size has, by far,been the single most widely accepted . . .significant determi-nant of FDI flows. I define market size as iGDPi;tlnGDPi;t FDIi;t in order to avoid the endogeneity problemof FDI being included in the measurement of GDP.

I use the trade-to-GDP ratio as a measure of openness,calculated as iOPENi;t

Xi;tMi;tGDPi;tFDIi;t

, where Xi;t and Mi;t are mer-

chandise exports and imports, respectively. While the trade-to-GDP ratio does not necessarily reflect the extent of aneconomys outward orientationamong other things, it could

be measuring country size(inversely)datafor alternative mea-

sures such as tariff levels are more scarce with less time-seriesvariability. Furthermore, according to the ranking of the mostrobust determinants of FDI by Chakrabarti (2001), the trade-to-GDP ratio places five positions above tariff levels. A poten-tial concern here is the possibility that GDP and opennessmay be collinear because smaller countries tend to have largertrade-to-GDP ratios. However, the within-sample correlation

of these variables is very low: in a regression of openness onGDP (controlling for country and year fixed effects) the overallR2 is just under 3%, while the within R2 is around 1%.

I calculate growth rates as annual percentage changes in theGNI per capita (GNIGRO) in order to avoid the previouslymentioned endogeneity problem with GDP and also to avoidGDP appearing too many times on the right-hand side. Theendogeneity issue may still be relevant, however, because thedirection of causation is not clearly established: some studiesargue that FDI generates growth, while others suggest thatFDI tends to be located in faster-growing economies. But thisproblem is likely to be less of an issue here because the modelallows previous growth to affect FDI, but the reverse causalityis unlikely unless current levels of FDI affect growth rates in theearlier period. 7 Another reason to be optimistic is that the cau-

sal links from FDI to growth are usually envisioned as a long-run phenomenon, and, therefore, are less likely to be problem-atic in annual data. Finally, inflation CPIGRO, used more gen-erally as a measure of macro instability, is calculated as theannual percentage change in the consumer price index.

In addition to these control variables, I include twovariables to capture potential effects of PTA membership onnet FDI inflows. First, to capture the potential FDI gains fromobtaining access to a larger market by joining a PTA,I define a common market size variable PTAGDPi;t

lnPN

j GDPi;j;t

8ij, where j ranges over all of the PTA part-

ners of country iin time t for all countries that are members ofat least one PTA. In the case of overlapping agreements (i.e.,when the same country pair appears in more than one PTA) Iadd a given partners GDP to the PTAGDP variable in theyear in which the earlier of the two (or more) agreements en-ters into force while for countries that are not members of asingle PTA in a given year, PTAGDP is equal to zero.

Second, economic and geographic proximity to PTA part-ners may also be an important determinant of FDI. On theone hand, similar to gravity models of trade, greater distancecould be associated with higher transaction costs and thereforelower FDI. On the other hand, to the extent that trade vol-umes are negatively related to distance and trade and FDImay be substitutes, we could see a positive relationship be-tween distance and net FDI inflows. Therefore, while the ex-pected sign of this variable is not clear and likely dependson the purpose of investment (i.e. whether FDI is market-seek-

ing, tariff-jumping, etc.), in either case it could be an importantdeterminant of net FDI inflows between PTA partners. Tocapture this effect, I define the second PTA-related variable,

DIST ln 1N

PNj distij

, as the log of average great circle dis-

tance between country i and all of its PTA partners at timet. This variable is equal to zero when a country is not a mem-ber of any PTAs, and has a time series dimension since its va-lue is updated every time a country enters into a newpreferential agreement.

Data on PTA membership by country have been obtainedfrom Medvedev (2010), who provides a comprehensive ac-count of all PTAs in force. 8 Overall, the sample includes180 preferential agreements (both regional and bilateral),many of which overlap and which encompass the vast majority

of sample countries. As pointed out in the literature on prefer-

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ential trade, e.g., Baier and Bergstrand (2004) and Magee(2003), PTA membership may be endogenous as the likelihoodof entering into a PTA is significantly affected by variablesthat also influence bilateral trade and investment, such as eco-nomic size and distance. However, both Baier and Bergstrand(2004) and Magee (2003) have been unable to come up withinstruments that, on the one hand, significantly determine

the likelihood of forming a PTA, and, on the other hand,are uncorrelated with the error term in the gravity equation(i.e., do not affect bilateral trade). More recently, Baier andBergstrand (2007) have pointed out that the use of panel data,either with fixed effects or in first difference form, adequatelyaddresses the endogeneity problem as long as the unobserva-bles determining the likelihood of forming a PTA are nottime-dependent. This is the assumption adopted by this paper,which leads to the following specification:

FDIi;t a ci ht b1iGDPi;t b2iOPENi;t

b3GNIGROi;t b4CPIGROi;t b5PTAGDPi;t

b6DISTi;t i;t 1

In order to simultaneously account for heteroscedasticityacross panels (BreuschPagan v2 239:38; p 0:00) and seri-al correlation within panels (Wooldridge F 103:032;p 0:00), I use a three-step feasible generalized least squares(FGLS) estimator. The advantage of this approach is that itallows estimation in the presence of AR(1) autocorrelationwithin panels and cross-sectional correlation and/or hetero-

scedasticity across panels. 9The results of estimating equation (1) are shown in col-

umn (1) of Table 3. With the exception of GDP, all ofthe control variable coefficients are significant at the 1% le-vel and carry the expected sign. Openness and growth havea positive effect on net FDI inflows, while the impact ofinflation is negative. The GDP coefficient carries the ex-pected sign and is significant at the 8% level, but the impliedelasticity of net FDI inflows with respect to market size(GDP) is substantially below estimates found in other stud-ies. 10 For example, Kolstad and Tondel (2002) obtain anelasticity estimate of slightly higher than one using grossFDI per capita as a dependent variable, while Coughlinand Segev (2000) estimate a similar elasticity with gross

FDI data for China.

11

Table 3. Baseline and additional variables estimation results, net FDI inflows

Variables (1) (2) (3) (4) (5) (6)

iGDP 0.139* 0.618*** 0.201** 0.025 0.133* 0.142*

(0.078) (0.063) (0.093) (0.118) (0.078) (0.078)iOPEN 0.114*** 0.176*** 0.100*** 0.083*** 0.113*** 0.113***

(0.025) (0.027) (0.025) (0.016) (0.025) (0.025)

GNIGRO 0.762*** 0.446*** 0.855*** 0.523** 0.762*** 0.772***

(0.154) (0.147) (0.201) (0.227) (0.153) (0.156)CPIGRO 0.022*** 0.022*** 0.016*** 0.039*** 0.022 *** 0.022***

(0.004) (0.004) (0.005) (0.010) (0.004) (0.004)

PTAGDP 0.053*** 0.079*** 0.042** 0.149*** 0.057*** 0.053***

(0.018) (0.017) (0.021) (0.037) (0.018) (0.018)DIST 0.176*** 0.244*** 0.148** 0.503*** 0.175*** 0.177***

(0.058) (0.057) (0.067) (0.149) (0.058) (0.058)

PSTAB 0.205***

(0.054)GOVEFF 0.005

(0.087)REGQ 0.505***

(0.065)ROLAW 0.008

(0.097)

CONCOR 0.118(0.081)

WLDGRO 0.628**

(0.252)WLDFDI 0.544***

(0.028)RERGRO 0.148

(0.131)PTAEXP 0.162

(0.106)CU 0.932

(1.428)CUGDP 0.026

(0.049)

Observations 2,778 2,778 1,803 798 2,778 2,778Countries 153 153 99 146 153 153

Standard errors in parentheses.The dependent variable is expressed in natural logarithms* p < 0.1.

** p < 0.05.***p < 0.01.


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Both of the PTA-related variables are significant at the 1%level and show that net FDI inflows respond positively tothe size of the PTA common market and negatively to the dis-tance to preferential trading partners. The PTAGDP coeffi-cient suggests that a 1% increase in the size of a countrysextended market tends to expand net FDI inflows by an aver-age of 0.05%. This elasticity is below the 0.1 value estimated by

Lederman et al. (2005), but the order of magnitude is similar.To quantify this, consider the example of Costa Rica. By 2004,the country was a member of several PTAs, including the Cen-tral American Common Market, Association of CaribbeanStates, and bilateral agreements with Argentina, Chile,Dominican Republic, Mexico, Panama, Venezuela, and Can-ada. If Costa Rica were to join DR-CAFTA (which includesthe United States) in the same year, the model would predictan 11.5% increase in its net FDI inflows. 12 On the other hand,were it instead to join a PTA with Ecuador, Costa Rica couldonly expect its net FDI inflows to rise by 0.08%.

The negative estimated elasticity of net FDI inflows with re-spect to average distance to PTA partners suggests thatincreasing this distance by 1% lowers net FDI inflows by0.18%. To continue with the example of Costa Rica, account-

ing for the fact that joining DR-CAFTA would increase thecountrys average distance to PTA partners lowers the ex-pected FDI benefit from 11.5% to 11.1%. On the other hand,if the United States were as far from Costa Rica as, say, Ger-many, the expected increase in net FDI inflows would be lim-ited to 9.6%.

(b) Additional variables

In this section, I test the robustness of the estimated PTAFDI relationship to the inclusion of some additional vari-ables, such as global growth and FDI, real exchange rate,institutional quality, the expectation of joining a PTA, andmembership in a currency union, using Eq. (1) as the starting

point. I begin by incorporating global effects into the modelsimilar to the approach of Lederman et al. (2005), whoshowed that country-level FDI inflows respond positively toincreases in global FDIreflecting aggregate FDI trendsand globalization effectsand negatively to increases inglobal growth because faster growth in the rest of the worldmakes the host country a less appealing FDI recipient. Be-cause of the endogeneity of global FDI, which isdetermined by a combination of left-hand side values for allsample countries, I measure this variable as WLDFDIi;tln

PiFDIi;t FDIi;t. Similarly, global growth is calculated

as WLDGROi;t 100

PiGDPi;tGDPi;tP

iGDPi;t1GDPi;t1

1

.

The results of estimating Eq. (1) with global FDI andgrowth variables are shown in column (2) of Table 3. In thiscase, I have to estimate Eq. (1) without time fixed effects toensure that the global variables are identified: because bothglobal FDI and growth have very low within-year variation,they are highly collinear with time effects. The estimatedcoefficients on the global variablesworld growth andworld FDIare consistent with expectations and show thatfaster growth in the rest of the world (controlling for homecountry growth) makes a particular nation a less attractivelocation for FDI, while rising total world FDI tends to in-crease net FDI inflows for an average host country.Although the estimated coefficients on other model variables(except inflation) are substantially different from the baselineestimates in column (1), all of them (including the PTA-related variables) retain their expected signs and statistical

significance.

Next is the exchange rate, which many studies cite as animportant determinant of FDI (see, e.g., Chakrabarti, 2001).The most basic theories of the relationship between exchangerate movements and FDI argue that a real depreciation ofhome currency reduces production costs for foreign investorsand therefore attracts FDI inflows (see, for instance, Cush-man, 1985). In addition, a real depreciation lowers foreigners

costs of acquiring domestic assets, which should also stimulateFDI. In other theoretical models, the link between exchangerate movements and FDI is assumed to work through capitalmarket imperfections, since the stream of income in a weakcurrency is subject to greater risk and is, therefore, capitalizedat a higher rate. For instance, Froot and Stein (1991) suggestthat under information asymmetries, monitoring costs causeexternal financing to be more expensive than internal financ-ing. In this situation, depreciation of the domestic currencynot only increases the relative wealth of foreigners, but also in-creases the relative rate of return for foreign firms that can in-vest in domestic assets without incurring the monitoringpenalty, therefore encouraging additional FDI. Blonigen(1997) also proposes a positive link between exchange ratedepreciation and FDI, although his reasoning differs from that

of the previous authors: even if domestic and foreign firmsmay have the same opportunities to purchase domestic assets,these assets can generate returns in currencies other than thoseused for purchase, which tends to favor foreign investors. Inorder to test the sensitivity of the PTA-FDI relationship tothe inclusion of the exchange rate variable, I define RERGROas the annual percentage change in the trade-weighted realeffective exchange rate (REER) of country i, with a positivenumber implying an appreciation.

The results of estimating Eq. (1) with the exchange rate var-iable are shown in column (3) of Table 3. Due to narrowerdata coverage of the REER variable, the number of observa-tions drops to 1,803 and the number of panels (countries) to99. Still, all control variables retain their significance and the

coefficient estimates are not very far from those shown in col-umn (1). The estimated elasticity of net FDI inflows with re-spect to RERGRO is negative, consistent with theoreticalexpectations, but the coefficient estimate is not significantlydifferent from zero. Finally, the PTAFDI relationship re-mains significant and its magnitude is similar to before evenafter controlling for exchange rate effects.

So far, the attempted specifications have not includedinstitutional quality variables because they substantially lim-it the sample size and have two other potential difficultiesaccording to Blonigen (2005): first, since the indices are usu-ally computed using survey responses, cross-country compa-rability is questionable when the composition of respondentsvaries across countries and second, since institutions arequite static, the amount of information that can be ex-

tracted from time-series variation in these variables is likelyto be negligible. Furthermore, using country fixed effectscontrols for a number of country-specific characteristics thatdisplay a lot of inertia, such as the quality of institutions.Still, to test whether institutions matter for the estimatedPTAFDI relationship, I add the following variables fromthe World Governance Indicators (WGI) dataset to Eq.(1): political stability and absence of violence, governmenteffectiveness, regulatory quality, rule of law, and controlof corruption.

The results of estimating the model with institutional vari-ables are shown in column (4) of Table 3. The number ofobservations falls to 798 but this is mainly due to the loss intime periods rather than countries, as the WGI data are onlyavailable from 1996 onwards. In the presence of institutional

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variablesof which political stability and regulatory qualitysignificantly and positively affect FDI while the others arenot significantthe GDP coefficient loses its significance andcoefficients on the PTA common market size and distance toPTA partners nearly triple in magnitude. However, they re-main significant at the 1% level, and the increase in magni-tudes (as well as the loss of significance on the GDP

coefficient) is due to restricting the sample to later years ratherthan the inclusion of institutional controls, a point I will re-turn to when discussing PTAs that have been signed sincethe mid-1990s in Section (c).

The fourth experiment, shown in column (5) of Table 3investigates the potential significance of the expectation of

joining a PTA. I create an expected PTA dummy, PTAEXP,which is equal to one for two years prior to a PTA coming intoforce and zero before and after those dates. Contrary to thefindings ofLederman et al. (2005), I cannot identify any signif-icant effects of the expectation of joining a PTA, although therest of the estimated coefficients are very similar to the baselinespecification. I also attempted alternative definitions of thisvariablefor example., extending its duration to three yearsprior to the PTAs entry into force as well as limiting it to

one yearbut the expected PTA dummy was never signifi-cantly different from zero.

There are several reasons why the expected PTA dummymay not be insignificant. First, since many countries havemore than one PTA and I do not rank PTAs in terms of theirpotential effect on FDI, it may be the case that the expectationof some agreements raises FDI but the expectation of othersdoes not. 13 Since the expected PTA variable is only definedfor the first agreement signed by a given country, identifyinga robust anticipation effect could be difficult. Furthermore, ifFDI responds to the investment provisions of an agreementor complements the increased trade flows, neither of thesecan increase before the agreement lifts the relevant barriers.Therefore, the PTA anticipation effect is likely to work

through only a subset of channels that link preferential liber-alization to FDI and its empirical contribution to the PTAFDI relationship is more difficult to capture.

Finally, I check whether the membership in a currency un-ion makes a difference to the estimated relationship. I addtwo variables to Eq. (1): a currency union dummy (CUd)and the combined market size of all members of the currency

union (CUGDP). The results of estimating this specificationare shown in column (6) of Table 3; although the coefficientestimates on all variables are very similar to those shown incolumn (3) of Table 3, neither the currency union dummynor the market size of the currency union appear to be signif-icant determinants of FDI in the presence of PTA-related vari-ables. 14

(c) Decomposition by income level and time period

In this section, I check whether the income level of desti-nation countries or the time period when the PTAs weresigned makes a difference for the estimated PTAFDI rela-tionship. I begin by testing if PTA membership has a largerimpact on net FDI inflows of a smaller, rather than a larger

country by interacting the PTA dummy variable with themarket size (iGDP) of the destination country in Eq. (1).The results of estimating this specification are shown in col-umn (1) of Table 4. Neither the PTA dummy nor the newinteraction variable are significantly different from zerowhile the other coefficient estimates are close to those shownin column (1) of Table 3. The only exception is the iGDPvariable, which becomes insignificantly different from zeroonce its interaction with PTA membership is added to thespecification.

The results of the second experimentwhich limit thesample to low- and middle-income countriesare shownin column (2) of Table 4. 15 The sample size falls to 2,244observations, representing an unbalanced panel of 130 coun-

Table 4. Estimation results by income level and time period, net FDI inflows

Variables (1) (2) (3) (4) (5)

iGDP 0.079 0.273*** 0.181 0.274** 0.167(0.088) (0.084) (0.310) (0.110) (0.117)

iOPEN 0.112*** 0.951*** 0.015 0.891*** 1.354***

(0.025) (0.098) (0.036) (0.140) (0.139)

GNIGRO 0.796*** 0.795*** 0.605 0.765*** 0.551***

(0.155) (0.158) (0.786) (0.189) (0.193)CPIGRO 0.022*** 0.020*** 3.051** 0.011** 0.031***

(0.004) (0.004) (1.356) (0.005) (0.011)

PTAGDP 0.048** 0.056*** 0.005 0.016 0.112***

(0.020) (0.020) (0.053) (0.027) (0.040)DISTA 0.238*** 0.200*** 0.015 0.049 0.386**

(0.070) (0.066) (0.154) (0.088) (0.165)

PTAd 0.574(0.973)

PTAd*iGDP 0.050(0.038)

Observations 2,778 2,244 534 1,084 1,149Countries 153 130 23 107 126

Standard errors in parentheses.The dependent variable is expressed in natural logarithms.Column (2) limits the sample to low and middle-income countries and column (3) shows only high income countries.Column (4) limits the sample to 198094, and column (5) shows the estimates for 19952004.* p < 0.1.

** p < 0.05.***

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tries between 1980 and 2004. The signs and significance ofall estimated coefficients remain unchanged from the base-line specification. Moreover, the coefficient magnitudes arequite close to the baseline estimates, with openness andGDP being the two exceptions. In contrast, the results forhigh-income countriesshown in column (3) of Table 4are very different. Only the inflation coefficient is signifi-

cantly different from zero, and it is of the wrong sign. Fur-thermore, neither the size of the extended common marketnor the average distance from PTA partners is a significantdeterminant of net FDI inflows for high income countries.Therefore, these results suggest that the model of net FDIinflows specified in Eq. (1)and, most importantly, the esti-mated link between preferential liberalization and net FDIinflowsapplies only to low- and middle-income FDI hostsand is therefore driven exclusively by North-South and/orSouth-South FDI. The next experiment is to divide thedeveloping country sample (since the estimated relationshiponly holds for these countries) into separate time periods:198094 and 19952004. The 1994 breakpoint was chosenfor two reasons: first, the mid-1990s witnessed an explosivegrowth in the number of PTAs and many of the agreements

signed in that time period and after have been of the thirdwave kind, putting much more emphasis on deep integra-tion than earlier PTAs. Second, this year splits the samplealmost evenly in two halves (1,084 observations in this per-iod versus 1,149 observations in the 19952004 time period).

Column (4) of Table 4 shows the estimated coefficients forthe 198094 sub-sample. The coefficients on all the controlvariables are significant and reasonably close to the esti-mates shown in column (2) for the full sample, but neitherthe extended common market nor the average distance toPTA partners is a significant determinant of FDI during thisperiod. On the other hand, model estimates for the 19952004 sub-sampleshown in column (5) of Table 4-providestrong support for the PTAFDI relationship, with both

PTA-related variables significant at the 1% and 2% level,respectively. Therefore, columns (2)(5) of Table 4 suggestthat the estimated link between preferential liberalizationand FDI is driven by FDI inflows into developing countriesowing to the effects of PTAs formed between 1995 and2004.

There are several potential reasons for this result. First, asmentioned earlier, PTAs signed over the course of the lastdecadeparticularly the North-South typehave generallyfocused on deep integration provisions much more heavilythan the earlier agreements. A particularly important linkbetween the new PTAs and FDI is the vast expansion intrade in services, to which FDI is a natural complement.As an example, consider the recent USSingapore FTA,which is unlikely to have a significant effect on merchandise

trade flows between the two partners (especially taking intoaccount Singapores very liberal MFN tariff schedule), but isexpected to have a much larger impact on the already sub-stantial trade in services between the two economies. Final-ly, studies such as World Bank (2002) have documented thetremendous expansion in FDI inflows into developing coun-tries during the late 1990s and early 2000s, and at least partof this expansion is potentially linked to the increased glo-bal integration brought about by the new deep integrationPTAs.

Despite these arguments, there also several reasons to becautious when interpreting the above results. First, causalityis much more difficult to establish than correlation. There-fore, even though both the number and scope of PTAs wereincreasing dramatically at the same time as average country

net FDI inflows were surging, it is impossible to know forcertain that the latter were directly caused by the former.It may even be the case that, as FDI increased globally inthe late 1990s, many countries actively pursued PTAs as astrategy to attract additional net FDI inflows. Second, theresults of Table 4 do not necessarily imply that the deepintegration provisions of later PTAs are responsible for

the empirical PTAFDI link, since the deep integration pro-visions are not the only feature differentiating the laterPTAs and some of the earlier ones also contained chaptersdealing with the liberalization of investment flows (e.g.,EFTA, MERCOSUR, and USIsrael FTA).

4. CONCLUSIONS

A large and growing body of literature has been devotedto understanding the trade creation and diversion effects ofpreferential trade agreements. On the other hand, the invest-ment consequences of preferential liberalization have re-ceived relatively little theoretical and empirical attention.This paper adds to the small but growing literature on the

links between PTAs and FDI by establishing a positive rela-tionship between preferential trade liberalization and netFDI inflows for a large panel of countries and preferentialagreements. There are three main messages emerging fromthe empirical results. First, the FDI benefits of preferentialliberalization are increasing in the size of PTA partnersand their proximity to the host country. Second, this rela-tionship is driven by the developing countries; and third,the link between preferential liberalization and FDI is onlyfound in the late 1990s and early 2000s, a period when mostdeep integration agreements have been signed but also atime of a global boom in FDI flows.

Overall, the results support the hypothesis that PTAs (anddeep integration PTAs in particular) are associated with sig-

nificant increases in the net FDI inflows of their partici-pants. The estimates of the FDI elasticity of a PTAextended common market are roughly similar to those ofLederman et al. (2005) and Yeyati et al. (2003), who obtainelasticities of approximately 0.1. I also identify significantproximity effects, although my estimates of the FDI-distanceelasticity are much lower than those in the bilateral gravityspecifications of Yeyati et al. (2003) and Adams et al.(2003). Estimates in this paper are particularly noteworthybecause I consider a very wide sample of PTAs, many ofwhich are small and/or poorly implemented. The heteroge-neity of PTAs is one possible reason why the estimates ofthe elasticity of FDI with respect to the size of commonmarket and distance to PTA partners are lower, althoughit is probably not the only reason.

There are a number of questions that the analysis heredoes not address. For example, I do not consider the sourceof net FDI inflows, and therefore cannot distinguish PTA-induced investment creation and diversion effects. I alsodo not distinguish between types of PTAsfor example,NorthSouth versus SouthSouth, bilateral versus regio-nalalthough different kinds of agreements may have vary-ing investment effects. Finally, I do not differentiate betweenPTAs that include explicit investment provisions and thosethat do not due to the lack of such data for the majorityof PTAs in existence. Answers to these questions are likelyto shed additional light on the empirical relationship be-tween preferential trade liberalization and FDI and there-fore represent promising directions for future research onthe subject.

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NOTES

1. On the other hand, Maskus (2000) cites Mansfield (1993), Maskus andEby-Konan (1994), and Primo Braga and Fink (1998), as examples ofstudies which could not establish a link between measures of IPR

protection and the distribution of FDI.

2. It should be noted that this version of the extended common markethypothesis relies on a certain geographic and economic proximity betweenPTA members.

3. The list of PTAs used in the analysis is provided in the Annex(Table 7).

4. The full list of countries is provided in the Appendix (Table 5).

5. This is in contrast to net FDI, which is the difference between net FDIinflows and net FDI outflows (the net increase in home country MNEassets abroad).

6. Variable definitions and sources are provided in the Appendix(Table 6).

7. This is consistent with the arguments of Rodrik (1999). The problemmay still arise if both series are highly autocorrelated, although anestimation approach that explicitly controls for serial correlation shouldminimize any adverse effects.

8. This dataset improves upon previous sources by including agreementsthat have not been notified to the WTO as well as PTAs found in the WTOdatabase. This addition is important since the PTAs that have not beennotified to the WTO account for more than 45% of the total number ofPTAs in force.

9. I do not iterate the third step to convergence because Greene (2000)notes that no asymptotic gains can be expected from iteration since theestimator is efficient at every step and, while the iterated FGLS estimator

converges to the maximum likelihood estimator (MLE) in models withoutserial correlation, the same does not hold when the disturbances areassumed to follow an AR(1) process.

10. The estimated elasticity is close to unity when time fixed effects areomitted from the model specification.

11. Other studies, such as Asiedu (2002) and Addison and Heshmati(2003), impose a unitary elasticity by moving GDP to the left-hand side.

12. This is equivalent to joining a bilateral PTA with the United States,since Costa Rica already has preferential access to all the other countriesin DR-CAFTA through its existing PTAs.

13. The same argument applies to attempts to estimate the model with avariable that captures a number of PTAs that a country has. Since theimpacts of PTAs are likely to be very heterogenousfor example, anagreement with a large partner is clearly more valuable than an agreementwith a small partnerit was not possible to estimate a robust relationshipbetween the number of PTAs and FDI.

14. The same results also hold if just the currency union dummy, or justthe market size of currency union members, are included in thespecification.

15. I define high income countries as 24 developed members of theOECD plus Liechtenstein.

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Blonigen, B. A. (2005). A review of the empirical literature on FDIdeterminants. NBER working papers 11299. National Bureau ofEconomic Research, Inc.

Brash, D. T. (1966). American investment in Australian industry.Canberra: Australian National University Press.

Buckley, P., Clegg, J., Forsans, N., & Reilly, K. (2000). United Statesforeign direct investment into Canada: An empirical analysis with

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Caves, R. (1996). Multinational enterprise and economic analysis. NewYork: Cambridge University Press.

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Globerman, S., & Shapiro, D. (2002). National political infrastructure andforeign direct investment. Working paper 37. Industry CanadaResearch Publications Program.

Graham, E., & Wada, E. (2000). Domestic reform, trade and investmentliberalization, financial crisis, and foreign direct investment intoMexico. World Economy, 23(6), 777797.

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Table 5. Included countriesAngola China, P.R. Ghana St. Kitts and Nevis Nicaragua SwazilandAlbania Cote dIvoire Gambia, The Korea, Rep. Netherlands SeychellesNetherlands Antilles Cameroon Guinea-Bissau Kuwait Norway Syrian Arab RepublicArgentina Congo, Republic Equatorial Guinea Lao Peoples Dem.Rep Nepal ChadArmenia Colombia Greece Lebanon New Zealand TogoAustralia Cape Verde Grenada Liberia Oman ThailandAustria Costa Rica Guatemala St. Lucia Pakistan TongaAzerbaijan Cyprus Guyana Sri Lanka Panama Trinidad and TobagoBurundi Czech Republic Hong Kong Lesotho Peru TunisiaBelgium Germany Honduras Lithuania Philippines TurkeyBenin Dominica Croatia Latvia Papua New Guinea TanzaniaBurkina Faso Denmark Hungary Morocco Poland UgandaBangladesh Dominican Republic Indonesia Moldova Portugal UkraineBulgaria Algeria India Madagascar Paraguay Uruguay

Bahamas Ecuador Ireland Maldives Romania United StatesBelarus Egypt Iran Mexico Russia St. Vincent & GrenadinesBelize Spain Iceland Macedonia Rwanda Venezuela, Rep. Bol.Bolivia Estonia Israel Mali Sudan VietnamBrazil Ethiopia Italy Mongolia Senegal VanuatuBarbados European Union Jamaica Mozambique Singapore SamoaBhutan Finland Jordan Mauritania Solomon Islands Yemen, Republic of Botswana Fiji Japan Mauritius Sierra Leone South AfricaCentral African Republic France Kazakhstan Malawi El Salvador Congo, Dem. Rep.Canada United Kingdom Kenya Malaysia Slovak Republic ZambiaSwitzerland Gabon Kyrgyz Republic Niger Slovenia ZimbabweChile Georgia Cambodia Nigeria Sweden

APPENDIX A. DATA DETAILS

.

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Table 6. Variable names and sources

Variable Name Source

FDI Foreign direct investment, net inflows (BoP, current US$) WDIGDP Gross Domestic Product (current US$) WDI

Exports Merchandise exports (current US$) WDIImports Merchandise imports (current US$) WDI

GNI Gross National Income (current US$) WDI

CPI Consumer price index (2000 = 100) WDIPTA PTA membership Medvedev (2010)DIST Great circle distance between largest or capital cities CEPII

REER Real effective exchange rate index (2000 = 100) WDIPSTAB Political stability and absence of violence WGIGOVEFF Government effectiveness WGIREGQ Regulatory quality WGI

ROLAW Rule of law WGICONCOR Control of corruption WGICU Strict currency union Rose (2004)

WDI: World Development Indicators, World Bank, http://data.worldbank.org.WGI: Worldwide Governance Indicators, World Bank, http://info.worldbank.org/governance/wgi/index.asp.CEPII: Centre dEtudes Prospectives et dInformations Internationales, http://www.cepii.fr.

Table 7. List of PTAs considered in the analysis

Agreement Year Notifiedto the WTO

AEC 1994 NoAFTA 1992 YesAghadir Agreement (Med-Arab FTA) 2003 NoAlbaniaMacedonia 2002 NoAndean CommunityArgentina 2000 NoAndean CommunityBrazil 1999 NoACC 1989 NoAMU 1989 NoArgentinaChile 2000 NoArgentinaCosta Rica 1983 No

ArgentinaCuba 1984 NoArgentinaEcuador 1993 NoArmeniaRussian Federation 1992 NoACS 1994 NoBAFTA 1994 YesBangkok Agreement 1976 YesBelarusUkraine 1992 NoBelarusUzbekistan 1993 NoBoliviaChile 1993 NoBoliviaCuba 1995 NoBoliviaMexico 1995 NoBosnia-HerzegovinaMacedonia 2002 NoBosnia-HerzegovinaYugoslavia 2002 NoBotswanaZimbabwe 1988 NoBrazilCuba 1987 No

BulgariaCroatia 2001 NoBulgariaEstonia 2002 YesBulgariaIsrael 2002 YesBulgariaLatvia 2003 YesBulgariaLithuania 2002 YesBulgariaMacedonia 2000 YesBulgariaTurkey 1999 YesBurkina FasoCuba 1987 NoBurkina FasoKorea 1998 NoBurkina FasoTunisia 1993 NoBurkina FasoIndia 1995 NoCACM 1961 YesCACMDominican Republic 2001 NoCACMVenezuela 1993 No

Table 7 continued


CAN 1988 YesCanadaAustralia (CANATA) 1960 NoCanadaChile 1997 YesCanadaCosta Rica 2002 YesCanadaIsrael 1997 YesCARICOM 1973 YesCARICOMColombia 1995 NoCARICOMDominican Republic 1999 NoCARICOMVenezuela 1993 NoCEFTA 1993 YesCEMAC 1999 YesCER 1983 YesChileCosta Rica 2002 YesChileCACM 2002 NoChileColombia 1994 NoChileEcuador 1995 NoChileEFTA 2004 NoChileKorea 2004 NoChileMERCOSUR 1996 NoChileMexico 1999 YesChilePeru 1998 NoChileVenezuela 1993 NoCIS 1994 YesChinaMacao 2004 NoChinaHong Kong 2004 NoColombiaCACM 1985 NoColombiaCuba 1988 NoColombiaPanama 1995 NoCOMESA 1994 YesCEN-SAD 1998 NoCroatiaBosnia and Herzegovina 2001 YesCroatiaHungary 2002 NoCroatiaMacedonia 1997 NoCBI 1998 NoCubaChile 1998 NoCubaEcuador 1995 NoCubaUruguay 1987 NoCzechMacedonia 1997 NoCzech RepublicEstonia 1998 Yes


http://data.worldbank.org/http://info.worldbank.org/governance/wgi/index.asphttp://www.cepii.fr/http://dx.doi.org/10.1016/j.worlddev.2011.04.036http://dx.doi.org/10.1016/j.worlddev.2011.04.036http://www.cepii.fr/http://info.worldbank.org/governance/wgi/index.asphttp://data.worldbank.org/


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Table 7 continued


Czech RepublicIsrael 1997 YesCzech Republic - Latvia 1997 YesCzech RepublicLithuania 1997 YesCzech RepublicSlovak Republic 1993 YesCzech RepublicTurkey 1998 YesEAC 2000 YesEAEC 1997 YesECLebanon 2003 YesECO 1992 YesECCAS 1995 NoCEPGL 1977 NoECOWAS 1975 NoEEA 1994 YesEFTACroatia 2002 YesEFTAJordan 2002 YesEFTABulgaria 1993 YesEFTACzech Republic 1992 YesEFTAEstonia 1996 YesEFTAHungary 1993 YesEFTAIsrael 1993 YesEFTALatvia 1996 YesEFTALithuania 1996 YesEFTAMacedonia 2001 YesEFTAMexico 2001 YesEFTAMorocco 1999 YesEFTAPalestinian Authority 1999 YesEFTAPoland 1993 YesEFTARomania 1993 YesEFTASingapore 2003 YesEFTASlovak Republic 1992 YesEFTASlovenia 1995 YesEFTATurkey 1992 YesEFTA (Stockholm Convention) 1960 Yes

El SalvadorGuatemala 1991 NoEstoniaFaroe Islands 1998 YesEstoniaTurkey 1998 YesEstoniaUkraine 1996 YesEuropean UnionCroatia 2002 YesEuropean UnionJordan 2002 YesEuropean UnionMacedonia 2001 YesEuropean UnionAlgeria 1976 YesEuropean UnionAndorra 1991 YesEuropean UnionAzerbaijan 1997 NoEuropean UnionBulgaria 1993 YesEuropean UnionChile 2003 NoEuropean UnionCyprus 1973 YesEuropean UnionCzech Republic 1992 YesEuropean UnionEgypt 1977 Yes

European UnionEstonia 1995 YesEuropean UnionFaroe Islands 1997 YesEuropean UnionHungary 1992 YesEuropean UnionIceland 1973 YesEuropean UnionIsrael 2000 YesEuropean UnionKyrgyz Republic 1998 NoEuropean UnionLatvia 1995 YesEuropean UnionLithuania 1995 YesEuropean UnionMalta 1971 YesEuropean UnionMexico 2000 YesEuropean UnionMorocco 2000 YesEuropean UnionNorway 1973 YesEuropean UnionOCTs 1971 YesEuropean UnionPalestinian Authority 1997 YesEuropean UnionPoland 1992 Yes

Table 7 continued


European UnionRepublic of San Marino 1992 NoEuropean UnionRomania 1993 YesEuropean UnionSlovak Republic 1992 YesEuropean UnionSlovenia 1997 YesEuropean UnionSouth Africa 2000 YesEuropean UnionSwitzerland and Liechtenstein 1973 YesEuropean UnionSyria 1977 YesEuropean UnionTunisia 1998 YesEuropean UnionTurkey 1996 YesEuropean UnionUzbekistan 1999 NoEuropean Union (Treaty of Rome) 1958 YesFaroe IslandsIceland 1993 YesFaroe IslandsNorway 1993 YesFaroe IslandsSwitzerland 1995 YesFijiPapua New Guinea 1996 NoGCC 1982 YesGeorgiaArmenia 1998 YesGeorgiaAzerbaijan 1996 YesGeorgiaKazakhstan 1999 YesGeorgiaRussian Federation 1994 YesGeorgiaTurkmenistan 2000 YesGeorgiaUkraine 1996 YesGreater Arab Free Trade Area 1998 NoGroup of Three 1995 NoGSTP 1989 YesGuineaMorocco 1997 NoHungaryEstonia 2001 YesHungaryIsrael 1998 YesHungaryLatvia 2000 YesHungaryLithuania 2000 YesHungaryTurkey 1998 YesIndiaBangladesh 1980 NoIndiaSri Lanka 2001 Yes

IndiaBhutan 1995 NoIndiaNepal 1991 NoIGAD 1986 NoIranSwitzerland 2001 NoIraqEgypt 2001 NoIsraelJordan 1996 NoIsraelTurkey 1997 YesJapanSingapore 2002 YesJordanMorocco 1994 NoJordanSyria 2001 NoKyrgyz RepublicArmenia 1995 YesKyrgyz RepublicKazakhstan 1995 YesKyrgyz RepublicMoldova 1996 YesKyrgyz RepublicRussia 1993 YesKyrgyz RepublicUkraine 1998 Yes

Kyrgyz RepublicUzbekistan 1998 YesLAIA 1981 YesLaosThailand 1991 YesLatviaTurkey 2000 YesLebanonKuwait 1996 NoLebanonSyria 1998 NoLebanonUAE 2001 NoLithuaniaTurkey 1998 YesMacedoniaYugoslavia 1996 NoMRU 1973 NoMERCOSUR 1991 YesMERCOSURBolivia 1997 NoMexicoBrazil 2002 NoMexicoCosta Rica 1995 NoMexicoCuba 1985 No

12 WORLD DEVELOPMENT



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Table 7 continued


MexicoIsrael 2000 YesMexicoNicaragua 1998 NoMexicoNTR 2001 NoMexicoUruguay 2001 NoMoldovaArmenia 1995 NoMoldovaAzerbaijan 1996 NoMoldovaBelarus 1994 NoMoldovaKazakhstan 1996 NoMoldovaRussian Federation 1993 NoMoldovaTurkmenistan 1996 NoMoldovaUkraine 1996 NoMoldovaUzbekistan 1995 NoMoroccoTunisia 1999 NoMSG 1993 YesNAFTA 1994 YesNamibiaZimbabwe 1993 NoNew ZealandSingapore 2001 YesNicaraguaColombia 1985 NoPalestinian AuthorityUnited States 1996 NoPalestinian AuthorityEgypt 1998 NoPalestinian AuthorityJordan 1995 NoPanamaCosta Rica 1973 NoPanamaDominican Republic 1987 NoPanamaEl Salvador 1974 NoPanamaGuatemala 1975 NoPanamaHonduras 1974 NoPanamaMexico 1986 NoPanamaNicaragua 1974 NoPATCRA 1977 YesPeruCuba 1994 NoPolandFaroe Islands 1999 YesPolandIsrael 1998 YesPolandLatvia 1999 Yes

PolandLithuania 1997 YesPolandTurkey 2000 YesPTAES 1981 NoPTN 1973 YesRomaniaMoldova 1995 YesRomaniaTurkey 1998 YesRussiaTajikistan 1992 No

Table 7 continued


RussiaUkraine 1994 NoRussian FederationAzerbaijan 1992 NoRussian FederationBelarus 1995 NoRussian FederationTurkmenistan 1992 NoRussian FederationUzbekistan 1992 NoSAPTA 1995 YesSaudi ArabiaSyria 2003 NoSingaporeAustralia 2003 YesSlovak RepublicEstonia 1998 YesSlovak RepublicIsrael 1997 YesSlovak RepublicLatvia 1997 YesSlovak RepublicLithuania 1997 YesSlovak RepublicTurkey 1998 YesSloveniaBosnia and Herzegovina 2002 YesSloveniaCroatia 1998 YesSloveniaEstonia 1997 YesSloveniaIsrael 1998 YesSloveniaLatvia 1996 YesSloveniaLithuania 1997 YesSloveniaMacedonia 1996 YesSouth AfricaMalawi 1990 NoSouth AfricaZimbabwe 1964 NoSACU 1969 NoSADC 2000 NoSPARTECA 1981 YesTaiwanPanama 2004 NoTRIPARTITE 1968 YesTunisiaEgypt 1998 NoTurkeySlovenia 2000 YesTurkeyBosnia and Herzegovina 2003 YesTurkeyCroatia 2003 YesTurkeyMacedonia 2000 YesUkraineAzerbaijan 1996 No

UkraineTurkmenistan 1996 NoUnited StatesJordan 2001 YesUnited StatesIsrael 1985 YesUnited StatesChile 2004 NoUnited StatesSingapore 2004 NoVenezuelaCuba 1989 NoVenezuelaTrinidad and Tobago 1989 NoWAEMU/UEMOA 2000 Yes


impact of preferential trade agreements on fdi

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