Trade integration and the EU economic membership criteria

European Journal of Political EconomyŽ .Vol. 16 2000 807–827

Trade integration and the EU economicmembership criteriaq

Lars Nilsson)

Ministry for Foreign Affairs, Department for European Union Affairs, Stockholm SE-103 39, Sweden

Received 1 February 1998; received in revised form 1 August 1999; accepted 1 September 1999

Abstract

Ž .The purpose of this paper is to consider whether the European Union EU ’s economicŽ .membership criteria for the Central and Eastern European countries CEECs and Cyprus

Ž .the Candidate Countries are fulfilled. To this end, I examine the actual and potential levelsof trade between the Candidate Countries and the EU countries using the gravity model.The results show a high degree of trade integration between all Candidate Countries and theEU, indicating that the Candidate Countries would not face any serious difficulties incoping with the competitive pressure and market forces within the Union in the mediumterm. The European Commission, however, suggested the contrary for some of theCandidate Countries in its opinions of 1997. q 2000 Elsevier Science B.V. All rightsreserved.

JEL classification: F13; F14; F15Keywords: Candidate Countries; Eastern Europe; European Union; Gravity model; Trade integration

1. Introduction

Ž . 1This paper examines if the European Union EU ’s economic criteria forŽ .membership for the Central and Eastern European countries CEECs and Cyprus

q The opinions expressed in this article are entirely the author’s and do not necessarily reflect theviews of the Swedish Government.

) Tel.: q46-8-405-56-79; fax: q46-8-723-11-76.Ž .E-mail address: [email protected] L. Nilsson .

1 Ž .The EU denotes the EU 15 , unless otherwise stated.

0176-2680r00r$ - see front matter q2000 Elsevier Science B.V. All rights reserved.Ž .PII: S0176-2680 99 00060-9

( )L. NilssonrEuropean Journal of Political Economy 16 2000 807–827808

Ž .the Candidate Countries are satisfied. According to the economic criteria, theCandidate Countries must have the capacity to cope with the competitive pressureand market forces within the Union in the medium term. The European Commis-sion, in its opinions of 1997 on the Candidate Countries’ applications formembership, considered that some applicants would have serious problems tofulfill this condition.2 At the Luxembourg summit in December 1997, the Com-mission’s evaluations formed the basis for the European Council’s decisionregarding Candidate Countries for whom membership negotiations should begin.

The level of trade integration between the EU and the Candidate Countries is anindicator of the extent to which the EU and the Candidate Countries have managedto penetrate each other’s markets. Low ratios of potential to actual CandidateCountry exports to the EU, indicating a high level of trade integration, thus implythat these countries have capacity to successfully compete on the EU market.3

Before 1989, the governments of the CEECs were part of the Council forŽ .Mutual Economic Assistance CMEA and restricted trade with the west by

explicit interventions.4 In the early 1990s, a number of studies sought to predictthe future long-run pattern and potential volume of trade between the CEECs and

ŽWestern market economies see, e.g., Wang and Winters, 1991; Hamilton and.Winters, 1992; Baldwin, 1994 . These studies concluded that the volume of trade

between the CEECs and Western Europe would increase to a multiple of the levelŽ .prevailing in the mid- and late 1980s. More recently, Gros and Gonciarz 1996

proposed that, with considerable expansion of trade with the EU countries, tradebetween Eastern and Western Europe had reached its potential level.

Against this background, in this paper, I update previous projections on thepotential volume of trade between the EU and the Candidate Countries. BaldwinŽ . Ž .1994 and Gros and Gonciarz 1996 are the main points of reference. The formerstudy is widely cited and contains policy proposals that are based on a predictionof large potential East–West trade flows. The latter is among the most recentstudies assessing the trade potential between the EU and the CEECs. I willexamine differences between the estimates of potential and actual trade betweenall CEEC–EU and Cyprus–EU country-pairs, in order to shed new light on thenotion that some Candidate Countries would have problems in coping withcompetitive pressure and market forces within the Union in the medium term. Iwill also reconsider the extent to which trade among the CEECs has reached itspotential level.

2 Ž . Ž Ž . .Commission of the European Communities 1997 COM 97 2001–2010, final .3 w xThe Commission, e.g., notes in one of its opinions that AThe high degree of trade integration with

w x Žthe Union . . . suggests that competitiveness remains quite highB Commission of the European. Ž Ž . .Communities, 1997 COM 97 , 2010, final, p. 32 .

4 Ž .See, e.g., Schrenk 1992 for a description of the CMEA system and the importance and pattern ofCMEA trade.

( )L. NilssonrEuropean Journal of Political Economy 16 2000 807–827 809

Data on the CEECs’ gross national product are notoriously unreliable before thechange in regime in 1989.5 The use of more recent data of better quality providesa more accurate picture of potential and actual trade, and thus of the level of tradeintegration between the Candidate Countries and the EU as well as among theCEECs. The paper is organized as follows. Section 2 presents the overall setting,including a brief background to the enlargement process and a short description ofthe Candidate Countries’ recent trade with the EU, and of intra-CEEC trade.Section 3 reviews the methodology and presents the estimated results. Section 4updates the projections of potential and actual trade between the EU and theCandidate Countries, and makes the comparison with the projections of BaldwinŽ . Ž .1994 and Gros and Gonciarz 1996 . This section also examines the CandidateCountries’ level of trade integration with the EU, and their capacity to compete onthe EU market. The findings are further discussed in Section 5. Section 6summarizes.

2. The setting

A foreign policy objective for the countries of Central- and Eastern Europeafter the end of socialism has been membership of the European Union. At the EUsummit in Copenhagen in 1993, the European Council concluded that EU mem-bership requires that a set of criteria be fulfilled. These so-called CopenhagenCriteria consist of political and economic criteria, and the ability to take on theobligations of membership.6

Based on the Commission’s opinions on the Candidate Countries’ applicationsfor membership in 1997, the Luxembourg European Council decided to launch theenlargement process with all Candidate Countries. The Czech Republic, Estonia,

Ž Ž ..Hungary, Poland, Slovenia and Cyprus the 5q1 were considered to be able tomeet the Copenhagen Criteria in the medium term, and were given the status offrontrunners for membership. The Luxembourg European Council decided that

Ž . Ž .intergovernmental conferences IGCs be opened with the 5q1 , thereby provid-ing the platform for the start of negotiations for membership.7 The remainingCandidate Countries, Bulgaria, Latvia, Lithuania, Romania, and the Slovak Repub-

5 Ž .See, e.g., Gros and Gonciarz 1996 , pp. 715–716.6 The political criteria require that a Candidate Country has achieved stability of institutions

guaranteeing democracy, the rule of law, human rights, and respect for and protection of minorities.The economic criteria require that a Candidate Country has a functioning market economy as well asthe capacity to cope with the competitive pressure and market forces within the Union.

7 Ž .Negotiations with the 5q1 began on seven chapters of the acquis in late 1998, and continued onanother eight chapters under the German Presidency during the first half of 1999. Under the FinnishPresidency during the second half of 1999, an additional seven chapters were opened for negotiations.


Ž Ž ..lic the 5 were considered to need to make additional efforts in order to fulfillthe Copenhagen Criteria in the medium term and be invited to start negotiations.

An important component in the Council’s decision not to open up IGCs withŽ .the 5 , and thus to facilitate the start of the negotiation process, was the presumed

Ž .incapacity of the 5 to cope with the competitive pressure and market forceswithin the Union in accordance with the economic criteria. Section 2.1 examines ifthe development of trade between the EU and the Candidate Countries supportssuch a suggestion.

2.1. EU trade with the Candidate Countries

ŽThe EU is, by far, the Candidate Countries’ most important trading partner see.Table 1 . Estonia, Latvia and the Slovak Republic experienced the greatest

increases in trade with the EU between 1993 and 1995, and one may observe thatŽ .several Candidate Countries among the 5 display greater increases in trade with

Ž .the EU compared to the Candidate Countries among the 5q1 . Breaking downthe increase in trade into increases in exports and imports reveals that several of

Ž .the countries among the 5 show greater increases in exports to, than in importsfrom the EU, indicating ability to cope with the competitive pressure on the EU’sinternal market.

2.2. Trade among the CEECs

In March 1993, ex-Czechoslovakia, Hungary and Poland founded the CentralŽ .European Free Trade Agreement CEFTA , with the intention of eventually

Table 1Ž .Change in, and share of, the Candidate Countries’ trade with the EU percent

Candidate Countries Share of Change in Change in Change intotal trade total trade exports importsŽ . Ž . Ž . Ž .1995 1993–1995 1993–1995 1993–1995

Ž .The 5q1 Cyprus 47.49 30.69 21.59 32.92Czech Republic 50.44 84.90 59.96 108.88

aEstonia 56.51 238.49 201.54 265.06Hungary 63.71 49.77 62.12 40.67Poland 67.04 58.29 63.76 53.90Slovenia 68.11 48.92 44.46 52.96

Ž .The 5 Bulgaria 52.07 71.07 93.85 58.12Latvia 48.69 137.96 70.06 217.54Lithuania 45.22 74.75 53.46 98.57Romania 50.75 74.94 97.34 58.04

aSlovak Republic 59.92 126.66 141.06 116.18

Ž .Source: Own calculations based on figures from IMF 1997a .a The figures are for 1994.


Table 2Ž .Change in intra-CEFTA trade percent

CEFTA country Change in Change in Change inexports imports total tradeŽ . Ž . Ž .1993–1995 1993–1995 1993–1995

Czech Republic 18.90 32.78 24.97Hungary 237.48 49.44 105.04Poland 84.19 125.81 106.01Slovak Republic 40.71 11.78 26.91Slovenia 54.29 91.24 74.95

Ž .Source: Own calculations based on figures in OECD 1997a , Tables 1a–4.

establishing free trade.8 Following the dissolution of Czechoslovakia, Sloveniabecame the fifth member of the CEFTA in 1996, and Romania became the sixthmember in 1997. Table 2 presents changes in trade between the countries of theCEFTA, including Slovenia, but excluding Romania. As can be seen, the increasein trade between the CEFTA members was most substantial for Hungary, Polandand Slovenia.9 Since trade among the CEFTA countries is subject to furtherliberalization via amendments made to the agreement,10 trade between the CEFTAcountries can be expected to increase in the period beyond the table.

Section 3 estimates how far trade integration between the EU and the CandidateCountries has reached, thereby indicating any potential differences between theapplicant countries as far as the capacity to cope with the competitive pressure onthe EU market is concerned.

3. Methodology and estimation

Several authors have contributed to improvements of the theoretical foundationsof the gravity model over the last decades,11 and the use of the model hasexperienced a revival through the studies, by, among others, Wang and WintersŽ . Ž . Ž . 121991 , Hamilton and Winters 1992 and Baldwin 1994 . The basic idea of the

Ž .gravity model is that bilateral trade flows X are determined by three sets ofi j

8 A free trade agreement in industrial products also between the Baltic States came into force onApril 1, 1994. The agreement was supplemented in 1997 by a free trade agreement in agriculturalproducts.

9 Despite the increase in intra-CEFTA trade, this is still a small proportion of the countries’ totalŽ .trade, some 5–10% see OECD, 1997a, p. 4 .

10 In late 1995, it was agreed that concessions on agricultural products were to be increased to 80%of products traded from 50% earlier. With respect to trade in industrial products, the last tariffs will be

Ž .eliminated over the period 1999–2002 see OECD, 1997a, p. 10 .11 Ž . Ž . Ž .See, e.g., Bergstrand 1985, 1989 , Helpman and Krugman 1985 , and Deardorff 1995 .12 Ž .See Oguledo and MacPhee 1994 for a survey on the empirical use of the model.


Ž .variables: i variables indicating total potential demand of the importing countryŽ . Ž .i; ii variables indicating total potential supply of the exporting country j; and iii

variables aiding or hindering trade between importing and exporting countries. Themodel may formally be represented as follows:13

GDP GDPi jX saqb GDP qb qb GDP qbi j 1 i 2 3 j 4ž / ž /POP POPi j

qb DIST qÝg D qe . 1Ž .5 i j k k i j i j

Ž .In Eq. 1 , all variables are in logs, GDP denotes gross domestic product, POPdenotes population, DIST stands for distance and ÝD is a set of dummy variables.The model may be interpreted as providing a long-run equilibrium view of tradepatterns. Prices are excluded from the model due to its long-run nature, since in ageneral equilibrium, setting prices are endogenous and simply balance to equatesupply and demand. The exclusion of price variables does not imply that prices arenot effective in allocating resources. Prices are assumed to adjust quickly, andsupply and demand are assumed to be sufficiently responsive to price changes togenerate an equilibrium quickly.14

The variables, GDP and GDPrPOP , capture the import demand of thei i i

importing country. GDP reflects economic size and is expected to be positive. Ai

higher per capita income indicates a higher import demand. The populationcomponent of per capita income may, however, affect trade in two ways. A largepopulation indicates a large domestic market, a higher degree of self-sufficiencyand less need to trade. A large population also promotes division of labor andimplies the presence of economies of scale in production and therefore also ofopportunities and desire to trade with a greater variety of goods. Thus, the effectsof per capita income on imports are undetermined. The variables, GDP andj

GDP rPOP , capture potential export supply of the developing countries in thej j

sample, using the same arguments applied to import demand. The variable forgeographic distance, DIST , is a measure of transport and transaction costs.i j

Transport costs are related to distance, while transaction costs reflect betterinformation and smaller cultural differences when countries are adjacent. Thevariable, DIST , is expected to influence trade flows negatively. The dummyi j

variables in the gravity model often denote factors that increase trade such aslinguistic and historical ties, tariff preferences, etc.

The gravity model gives the relationship between GDP, per capita GDP,distance and bilateral trade flows for what could be considered as AnormalB tradebetween countries integrated into the world trade system, as the average of the

13 Ž .See, e.g., Baldwin 1994 . The model may be equivalently specified with GDP and POP, or GDPand GDPrPOP, separately.

14 Ž .See Leamer and Stern 1970 , pp. 146–147.


sample considered. In this study, AnormalB trade is defined as the average of thetrade between the OECD countries.15 In order to analyze whether EU trade withthe CEECs and Cyprus as well as among the CEECs is above this AnormalB level,the EU countries’ trade with the non-OECD countries of Central and EasternEurope and Cyprus, and trade among the CEECs are added to the sample.

Ž . Ž .This paper employs a version of Eq. 1 in which the trade data X arei jŽ .obtained from the UN 1997 ’s Comtrade database and equal the dollar value

Ž .US$1000 of the imports into country i from country j. Data on the incomeŽ .variables, in dollars in purchasing parities , are obtained from the World Bank’s

Ž . 16 Ž .1997 World DeÕelopment Indicators, and distances in kilometers have beenŽ .computed as straight lines between capitals. The binary variables ÝD accountk i j

Ž .for major trade arrangements, or other more far-reaching trade agreements,between the countries in the sample. They refer to trade between the EU and the

Ž .EFTA countries in the European Economic Area EEA , trade between countriesŽ .of the North American Free Trade Agreement NAFTA , i.e., Canada, Mexico and

Ž .USA, trade between Australia and New Zealand AUNZ under the agreement ofCloser Economic Relations, and to the EU countries’ customs union with TurkeyŽ . 17EU–TURKEY .

Binary variables for the EU countries’ trade with the Candidate CountriesŽ . Ž .EUCC and for trade among the CEECs intra-CEEC are included in order toexamine whether the EU’s trade with the Candidate Countries and intra-CEECtrade significantly differ from the average, or normal, OECD level. Binary

Ž .variables accounting for countries in the sample with a common border BORDERŽ .and for countries with a common or similar language LANGUAGE are also

included in the regressions.18 Finally, e is a log normally distributed error termi j

and a , b and g are parameters to be estimated.i k

3.1. Results

In order to avoid cyclical effects and to reduce the effects of temporary shocks,Ž . 19Eq. 1 is estimated on data averaged for 1995 and 1996. Export data for all

Ž .trading countries are used and the data denoted in nominal US dollars wereconverted to constant US dollars.20 The observations in the sample include trade

15 The OECD as of 1997.16 Data on GNP are used.17 The EU’s customs union with Turkey came into force on December 31, 1995.18 Ž .Wang and Winters 1991 also use a land border binary variable and a binary variable for France’s

and the UK’s trade with their ex-colonies. Thus, the latter covers trade between countries with a similarlanguage.

19 Ž .Bayoumi and Eichengreen 1995 use the same procedure.20 The data are converted to constant 1990 prices by using the overall US GDP deflator obtained

Ž .from OECD 1998 .


Table 3Gravity model regression results of OECD trade, EU trade with the Candidate Countries, andintra-CEEC trade, average 1995–1996

Variables Coefficient t-statistics Coefficient t-statistics

Ž . Ž . Ž .GNP exporting countries 0.82 34.11 0.82 34.17iŽ . Ž . Ž .GNP rPOP exporting countries 1.21 15.33 1.23 15.14i i

Ž . Ž . Ž .GNP importing countries 0.84 36.67 0.84 36.63jŽ . Ž . Ž .GNP rPOP importing countries 0.67 8.72 0.69 8.48j j

Ž . Ž .DIST y0.89 20.43 y0.89 20.35i jŽ . Ž .Dummies EEA 0.27 2.91 0.27 2.88Ž . Ž .BORDER 0.58 4.58 0.58 4.62Ž . Ž .LANGUAGE 0.56 4.94 0.56 4.87Ž . Ž .NAFTA 0.28 0.70 0.28 0.70Ž . Ž .AUNZ 1.95 15.20 1.95 14.90Ž . Ž .EU–TURKEY 0.25 1.71 0.27 1.82

Ž . Ž .EUCC 10q1 0.14 1.08 – –Ž . Ž .EUCC 5q1 – – 0.10 0.82Ž . Ž .EUCC 5 – – 0.23 1.48

Ž . Ž .INTRA-CEEC 1.02 4.69 1.07 4.80Ž . Ž .Constant y41.40 25.99 y41.78 25.19

2Adjusted R 0.86 0.86Number of observations 1038 1038

All variables are in logs. The log value of the binary variables takes on the values 1 and 0, respectively.The t-statistics in parentheses are estimated with heteroscedasticity-consistent standard errors.

between the OECD countries, the EU countries’ trade with the CEECs andCyprus, and trade among the CEECs.21 The ordinary least squares regressionresults are presented in Table 3.

The results are by and large as expected. The explanatory power of the model isgood, with the included variables explaining some 85% of the variation of tradebetween the countries. The coefficients of the exporting and importing countries’GNPs, GNP and GNP , have expected signs and are significant at the 1% level.i j

The coefficients are similar in size compared to those obtained from otherstudies.22 The parameter estimates of per capita income of the exporting andimporting countries are significant at the 1% level. The magnitude of the parame-ter of per capita income is, however, greater for the exporting countries. If themodel is re-parameterized using population and per capita income in order tofacilitate a comparison, both parameter estimates are greater in magnitude than

21 Data for Luxembourg are included in the data for Belgium; data for Bulgaria as an exportingcountry are missing; Cyprus does not report any export to Portugal, and trade between Iceland andMexico is zero.

22 Ž .See, e.g., Wang and Winters 1991 .


Ž .those obtained by Baldwin 1994 . Distance appears as a strong impediment totrade. The coefficient of DIST is negatively significant at the 1% level.i j

The coefficients of the variables denoting trade agreements indicate that tradeŽ .between the countries in the EEA zone is significantly greater at the 1% level

than average OECD trade. The same holds for trade between Australia and NewZealand. The NAFTA agreement does, however, indicate that trade betweenCanada, Mexico and the USA is not significantly greater than average OECDtrade. Finally, the EU countries’ custom union with Turkey seems to have had apositive influence on trade.

The binary variable for the EU countries’ trade with the Candidate CountriesŽ .EUCC is insignificant, indicating that average EU trade with the CEECs andCyprus does not differ significantly from the average level of trade among the

Ž .OECD countries. Splitting the Candidate Countries into two groups, 5q1 andŽ . Ž . Ž .5 , does not affect the result. The parameters of EUCC 5q1 and EUCC 5 areinsignificant. In addition, there is no statistically significant difference between thetwo groups of Candidate Countries as far as trade with the EU is concerned.23 Thevariable for intra-CEEC trade is, however, significant, indicating that trade be-tween the CEECs is greater than the average level of trade between the OECDcountries.

4. Potential trade between the Candidate Countries and the EU and amongthe Candidate Countries

The binary variable for trade between the EU countries and the CandidateCountries is insignificant. Hence, as far as trade is concerned, the CandidateCountries appear to be as integrated with the EU as the OECD countries are onaverage. Some individual Candidate Countries may, however, display greatervolumes of trade with the EU than the model predicts, and others less, thusrevealing varying degrees of trade integration and competitiveness among theCandidate Countries.

The potential volume of trade between the Candidate Countries and the EUcountries, defined as the volume of trade that would prevail if trade wereexplained by the same factors determining trade between the OECD countries inthe model, is obtained by taking the coefficients of the variables in the model and

24 Ž .plugging in the trading countries’ actual values of the variables. Baldwin 1994

23 The test statistics may be obtained from the author.24 Should trade between the EU and the CEECs after enlargement resemble the trade among the EEA

countries, the potential volume of trade would be greater as indicated by the positive and significantcoefficient of the EEA variable.


Table 4Ratio of the EU’s potential to actual exports to the Candidate Countries

Baldwin Gros and Gonciarz This study

Austria 2.8 – 1.4BelgiumrLuxembourg 2.3 – 0.9Denmark 3.7 – 1.2Finland 6.5 – 0.5France 3.1 – 1.5Germany 1.1 – 1.1Greece 2.3 – 0.7Ireland 2.0 – 0.7Italy 2.5 – 0.9Netherlands 2.1 – 0.9Portugal 11.2 – 2.6Spain 2.3 – 1.2Sweden 2.0 – 0.6UK 4.3 – 1.3

aŽ .EU 15 2.1 0.4 1.1

Ž .Source: Own calculations, and calculations based on figures adapted from Baldwin 1994 , p. 90 andŽ .Gros and Gonciarz 1996 , p. 717.

Ž .The figures of Baldwin 1994 are estimated for 1989 and do not include the Baltic States and Cyprus.Note also that Austria, Finland and Sweden were not EU members in the estimation year of BaldwinŽ .1994 .

a Ž . Ž . Ž .The figure is for the CEEC 3 . The ratio of actual to potential EU 15 exports to the CEEC 3 is2.3. The inverse of 2.3 rounded off equals 0.4, which is the ratio of potential to actual EU exports tothe CEECs presented. The authors do not present ratios obtained at individual EU country level.

applies the same procedure, using, by and large, the same reference group as inthis study.25

4.1. Potential and actual EU exports to the Candidate Countries

Ž .In the medium-run scenario, Baldwin 1994 estimates that the EU’s exports toŽ .the CEECs excluding the Baltic States should have been approximately twice as

Ž .large as they actually were in 1989 see the last row of Table 4 . There are,however, great differences between the EU countries. The results of BaldwinŽ .1994 indicate that the exports of the UK, Finland, and Portugal to the CEECsshould have been between 4 and 11 times higher than actual exports in 1989,while German exports to the CEECs, more or less, already had reached theirpotential level in 1989.

25 Ž .The comparison group of countries in Baldwin 1994 is made up of the EU and EFTA countries,Canada, Japan, Turkey and the United States, and he estimates trade potentials for Albania, Belarus,Bulgaria, Croatia, Czech Republic, Estonia, Hungary Latvia, Lithuania, Moldova, Poland, Romania, theSlovak Republic, Slovenia and Ukraine.


Ž . Ž .Gros and Gonciarz 1996 find that the GDP of the CEECs in Baldwin 1994is overvalued. They adjust the CEECs’ GDP figures and update the estimated trade

Ž .potentials of Baldwin 1994 for 1989 with actual data for 1992. Gros andŽ .Gonciarz 1996 conclude that the trade of the CEECs has responded very quickly

to the change in regime and that the projections based on data from 1992 do notindicate any unused export potential of the EU countries.

Ž .Compared to the trade projections of Baldwin 1994 for 1989, I find that thegap between potential and actual trade between the EU and the CEECs and Cyprushas been greatly reduced. The ratio of the EU’s potential to actual exports to theCandidate Countries is 1.1, indicating that the EU’s actual exports are slightly

Ž .lower than estimated potential exports. Compared to estimates of Baldwin 1994 ,it can be seen that the difference between potential and actual EU exports to theCEECs has been substantially reduced for each EU country, except for Germanywhose ratio of potential to actual trade remains at 1.1. In addition, several EUcountries export more to the Candidate Countries than the gravity model predicts.

Ž .The individual country-pair estimates see Table 9 reveal that the highest ratiosof potential to actual EU exports are found for Portugal’s exports to the twofrontrunners, Slovenia and the Czech Republic. The lowest ratios of potential toactual EU exports are found for EU exports to the Baltic countries and Cyprus. Ifwe instead consider the EU’s exports to the CEECs and Cyprus from theimporting countries’ view, we see that, except for the Czech Republic and theSlovak Republic, all Candidate Countries have reached or exceeded their estimated

Ž .import potential from the EU countries see the last row of Table 9 .

4.2. Potential and actual Candidate Country exports to the EU

There also remains some potential for Candidate Country exports to the EUŽ . Ž .see Table 5 . Baldwin 1994 predicts that the ratio of potential to actual CEEC

Ž . Ž . Ž .exports to the EU 12 varies between 1.2 Romania and 5.2 Bulgaria . Gros andŽ .Gonciarz 1996 estimate that the CEECs already have reached and exceeded their

estimated export potential.Ž .I find the ratio of potential to actual CEEC 10 and Cypriot exports to the EU

to be 0.9, indicating that the Candidate Countries have slightly exceeded theirestimated export potential to the EU. Compared to the medium-run estimates of

Ž .Baldwin 1994 , the ratios are lower for each CEEC, implying that the gapbetween potential and actual CEEC exports to the EU has been reduced over time.Only Cyprus and the Czech Republic show ratios above 1, indicating a remainingexport potential to the EU countries.

ŽFrom the individual Candidate Country–EU country-pair estimates see Table.9 , we see that the Baltic States are frequently present among those Candidate

Countries showing the lowest ratios of potential to actual exports to the EU. Whenwe consider the Candidate Countries’ exports to the EU from the importing

Ž .countries’ view see the column to the far right of Table 9 , we see that six EU


Table 5Ratio of the CEECs potential to actual exports to the EU

Baldwin Gros and Gonciarz This study

Bulgaria 5.2 – –Cyprus – – 1.7Czech Republic – – 1.6Estonia – – 0.4Hungary 1.7 0.4 0.5Latvia – – 0.4Lithuania – – 0.5Poland 2.1 0.4 0.7Romania 1.2 – 0.5Slovak Republic – – 0.8Slovenia – – 0.9Czech and Slovak Republics 4.8 0.8 1.4

Ž .CEEC 3 – 0.5 1.0Ž .CEEC 10 – – 0.9

Ž .Source: Baldwin 1994 , own calculations, and own calculations based on figures adapted from GrosŽ .and Gonciarz 1996 , p. 717.

Ž . Ž .The figures of Baldwin 1994 are estimated for the EU 12 in 1989 and do not include the BalticŽ .States. The figure of Baldwin 1994 for the Czech and Slovak Republics is the author’s own

Ž .calculation based on the figures of Baldwin 1994 .

countries show ratios of potential to actual EU imports from the CandidateŽ .Countries greater than 1 Austria, France, Ireland, Portugal, Spain and the UK .

Over time, these EU countries may thus be expected to increase their imports fromthe Candidate Countries to a relatively greater extent compared to the other EUcountries.

According to the European Commission’s opinions on the CEECs in its AgendaŽ .2000, several of the countries among the 5 lack the ability to cope with the

competitive pressure and market forces within the Union in the medium term.Ž .However, as Tables 5 and 9 display, the trade of the 5 does not seem to have

Ž .become less integrated with the EU countries than the trade of the 5q1 . InŽ .many cases, the ratios of potential to actual trade of the 5 are lower than

Ž .corresponding ratios of the frontrunners. Thus, as far as trade is concerned, the 5Ž . Ž .have managed to become at least as integrated in the EU market as the 5q1 .

Hence, based on the ability to cope with the competitive pressure and marketŽ .forces within the Union, the 5 may very well be considered to fulfill this part of

the economic criteria to the same extent as several of the frontrunners.

4.3. Potential trade among the CEECs

The binary variable for trade among CEECs is significant. Hence, accountingfor the gravity variables, trade among the CEECs is greater than the average level

Ž .of trade between the OECD countries. Gros and Gonciarz 1996 also foundintra-CEEC trade to be statistically significant. In order to shed further light on the


Table 6Ratio of potential to actual intra-CEEC exports and imports

Group Country Ratio exports Ratio imports

CEEC Czech Republic 0.54 0.48Frontrunners Estonia 0.16 0.27

Hungary 0.77 0.86Poland 1.00 0.99Slovenia 1.65 0.87

Ž .The 5 Bulgaria – 1.32Latvia 0.34 0.15Lithuania 0.39 0.39Romania 1.69 1.21Slovak Republic 0.27 0.33

Ž .Source: Own calculations. – Indicates that data are missing.

countries that are contributing to the relatively high level of trade among theCEECs, the ratios of potential to actual levels of intra-CEEC trade are presented inTable 6.26

The Baltic States and the Czech and Slovak Republics display quite low ratiosof potential to actual trade, indicating much greater trade than the gravity modelpredicts. A closer examination of Table 7 reveals that the low ratios of potential toactual trade of the Baltic States are mainly due to their trade with each other. Still,one should remember that the Baltic States are transit countries for trade withRussia, which influences the figures. Likewise, the low ratios of potential to actualtrade of the Czech and Slovak Republics can, to a large extent, be explained byhigh levels of trade between the two republics.27

The binary variable for trade among CEECs is significantly greater than thedummy for trade between the EU and the CEECs.28 The various trade arrange-ments between the CEECs thus appear to be more effective than the Europeagreements in the mid-1990s. This seems to apply in particular to the free tradearrangement between the Baltic States and the customs union between the Czechand Slovak Republics, as indicated by these countries’ low ratios of potential toactual trade with each other.

In the Europe agreements, the elimination of trade barriers is scheduled to takeŽ .place asymmetrically in favor of the CEECs , while the CEFTA agreement calls

for a symmetric and more rapid reduction of trade barriers than what is stipulatedin the Europe agreement. This may contribute to explain the relatively high level

26 The ratios of potential to actual trade between the individual CEECs can be found in Table 7.27 The ratio of actual to potential trade of the Czech Republic increases to 1.05 when the Slovak

Republic is excluded from the sample. Corresponding ratio of the Slovak Republic increases to 0.56when the Czech Republic is excluded.

28 The test statistics may be obtained from the author.


Tab

le7

Ž.

Pro

ject

edtr

ade

mat

rix

for

intr

a-C

EE

Cex

port

s19

95–

1996

,m

illi

ondo

llar

s,ex

cept

rati

os

Tra

deB

ulga

ria

Cze

chE

ston

iaH

unga

ryL

atvi

aL

ithu

ania

Pol

and

Rom

ania

Slo

vak

Slo

veni

aS

umR

epub

lic

Rep

ubli

c

Cze

chP

oten

tial

57,9

92–

12,3

7027

6,17

716

,296

33,1

471,

066,

780

135,

646

560,

555

172,

937

2,33

1,90

1R

epub

lic

Act

ual

61,4

71–

15,1

6233

1,14

518

,992

62,5

8193

4,61

855

,806

2,63

9,91

120

3,45

54,

323,

142

Rat

io0.

94–

0.82

0.83

0.86

0.53

1.14

2.43

0.21

0.85

0.54

Est

onia

Pot

enti

al12

9380

47–

3671

3243

1935

14,2

5933

8616

7819

6339

,476

Act

ual

1433

2212

–17

2513

2,87

488

,159

19,5

0266

785

815

524

7,58

5R

atio

0.90

3.64

–2.

130.

020.

020.

735.

081.

9612

.65

0.16

Hun

gary

Pot

enti

al36

,812

218,

923

4400

–58

4412

,914

225,

102

152,

409

219,

507

134,

307

1,01

0,22

0A

ctua

l30

,535

213,

762

12,4

58–

16,3

9343

,151

312,

012

273,

826

199,

770

204,

812

1,30

6,71

8R

atio

1.21

1.02

0.35

–0.

360.

300.

720.

561.

100.

660.

77L

atvi

aP

oten

tial

1426

9296

2843

4273

–61

9019

,463

3788

1948

2180

51,4

07A

ctua

l12

7759

0340

,187

2360

–77

,242

22,6

5715

824

8361

815

2,88

6R

atio

1.12

1.57

0.07

1.81

–0.

080.

8623

.91

0.78

3.53

0.34

Lit

huan

iaP

oten

tial

3381

20,8

0218

6510

,359

6817

–96

,268

9275

4600

4928

158,

295

Act

ual

8109

10,4

1262

,148

12,1

3221

4,97

7–

91,0

8724

0715

5854

640

3,37

7R

atio

0.42

2.00

0.03

0.85

0.03

–1.

063.

852.

959.

020.

39P

olan

dP

oten

tial

51,2

3575

8,36

215

,512

204,

249

24,1

5910

8,98

3–

136,

070

167,

264

86,6

691,

552,

503

Act

ual

40,4

8766

5,00

631

,434

248,

584

61,1

0818

0,59

4–

56,5

2224

0,94

232

,522

1,55

7,19

9R

atio

1.27

1.14

0.49

0.82

0.40

0.60

–2.

410.

692.

661.

00R

oman

iaP

oten

tial

112,

741

87,2

2932

5712

3,63

341

5892

5312

1,25

3–

25,6

1830

,891

518,

034

Act

ual

60,9

6816

,613

9814

8,88

840

414

1339

,561

–19

,801

18,7

7830

6,52

2R

atio

1.85

5.25

33.3

00.

8310

.31

6.55

3.06

–1.

291.

651.

69S

lova

kP

oten

tial

12,6

5340

8,52

418

5920

1,88

524

6353

0417

0,38

651

,663

–37

,878

892,

613

Rep

ubli

cA

ctua

l16

,268

2,48

2,81

940

6334

2,03

054

2220

,622

346,

468

42,9

19–

78,5

273,

339,

137

Rat

io0.

780.

160.

460.

590.

450.

260.

491.

20–

0.48

0.27

Slo

veni

aP

oten

tial

25,9

8219

2,17

233

4219

0,01

842

3487

1913

5,53

153

,790

58,1

33–

671,

920

Act

ual

9444

119,

927

815

94,8

0130

5386

6010

5,95

818

,629

46,8

88–

408,

176

Rat

io2.

751.

604.

102.

001.

391.

011.

282.

891.

24–

1.65

Sum

Pot

enti

al30

3,51

51,

703,

355

45,4

481,

014,

265

67,2

1618

6,44

61,

849,

041

546,

026

1,03

9,30

347

1,75

47,

226,

368

Act

ual

229,

993

3,51

6,65

416

6,36

61,

181,

665

453,

221

482,

423

1,87

1,86

445

0,93

43,

152,

210

539,

413

12,0

44,7

41R

atio

1.32

0.48

0.27

0.86

0.15

0.39

0.99

1.21

0.33

0.87

0.60

Sour

ce:

Ow

nca

lcul

atio

ns.


Table 8Ž .The Candidate Countries’ exchange rates 1993–1995 as denominated, and in percent

Group Candidate Denomination 1993 1994 1995 Change AppreciationrCountry 1993–1995, depreciation

in percent

Ž .5q1 Cyprus US$rPound 2.01 2.03 2.21 9.91 AppreciationCzech KorunyrUS$ 29.15 28.79 26.54 y8.96 AppreciationRepublicEstonia KroonirUS$ 13.22 12.99 11.47 y13.30 AppreciationHungary ForintrUS$ 91.93 105.16 125.68 36.71 DepreciationPoland ZlotyrUS$ 1.81 2.27 2.43 33.87 DepreciationSlovenia TolarsrUS$ 113.24 128.81 118.52 4.66 Depreciation

Ž .5 Bulgaria LevrUS$ – – – – –Latvia LatsrUS$ 0.68 0.56 0.53 y21.78 AppreciationLithuania LitairUS$ 4.34 3.98 4.00 y7.92 AppreciationRomania LeirUS$ 760.05 1655.09 2033.28 167.52 DepreciationSlovak KorunyrUS$ 30.77 32.05 29.71 y3.44 AppreciationRepublic

Ž .Source: Own calculations based on figures from IMF 1997b .The exchange rate is the official rate in all cases except for Poland and Romania where the exchange

Ž .rate is the market rate. – Denotes that figures are not available.

of trade between the CEECs. In addition, while both the CEFTA as well as theEurope agreements contain provisions for anti-dumping measures, no anti-dump-ing procedures have been initiated in trade between the CEFTA countries as of1997. The EU, on the other hand, has applied several anti-dumping measures intrade with CEFTA countries.29

5. Discussion of the results

The study’s projections of potential trade indicate that the differences betweenpotential and actual trade between the CEECs and the EU have been reduced

Ž .compared to the study of Baldwin 1994 on data for 1989. The results suggestthat there is still some unused trade potential between the Candidate Countries and

Ž .the EU countries. This contrasts with the results of Gros and Gonciarz 1996 .Ž .Gros and Gonciarz 1996 conclude that the pre-1989 data on the GDP of the

CEECs were greatly overstated and adjust their own projections for the overvalua-tion of the GDP figures. They also show that Austria’s and Spain’s GDP were

Ž .underestimated in the study of Baldwin 1994 . The adjustment of Gros and

29 In the 1992–1996 period, two to three anti-dumping measures were in force annually in the case ofHungary, five to six measures annually in the case of Poland, and in the Czech and Slovak Republicscombined, four measures were in force in 1993–1994, one in 1995 and one in 1996. See OECDŽ .1997a, b , p. 14.


Table 9Ž . Ž . Ž .Projected trade matrix for the EU’s exports imports to from the Candidate Countries 1995–1996 ,

million dollars, except ratios

Trade Bulgarial Czech Republic Estonia

Ž . Ž . Ž .Austrial Potential 110 – 2436 1646 17 7Ž . Ž . Ž .Actual 120 – 1383 1222 11 4Ž . Ž . Ž .Ratio 0.9 – 1.8 1.3 1.5 1.7Ž . Ž . Ž .Belgiumr Potential 72 – 681 458 19 8Ž . Ž . Ž .Luxembourg Actual 70 – 514 310 37 18Ž . Ž . Ž .Ratio 1.0 – 1.3 1.5 0.5 0.4Ž . Ž . Ž .Denmark Potential 42 – 427 286 19 8Ž . Ž . Ž .Actual 29 – 152 115 65 58Ž . Ž . Ž .Ratio 1.4 – 2.8 2.5 0.3 0.1Ž . Ž . Ž .Finland Potential 25 – 151 113 294 143Ž . Ž . Ž .Actual 36 – 182 81 877 334Ž . Ž . Ž .Ratio 0.7 – 0.8 1.4 0.3 0.4Ž . Ž . Ž .France Potential 275 – 2229 1557 64 29Ž . Ž . Ž .Actual 149 – 957 516 32 16Ž . Ž . Ž .Ratio 1.8 – 2.3 3.0 2.0 1.8Ž . Ž . Ž .Germany Potential 443 – 13,738 9866 133 62Ž . Ž . Ž .Actual 699 – 7518 6908 240 120Ž . Ž . Ž .Ratio 0.6 – 1.8 1.4 0.6 0.5Ž . Ž . Ž .Greece Potential 116 – 108 98 4 2Ž . Ž . Ž .Actual 327 – 43 79 1 1Ž . Ž . Ž .Ratio 0.4 – 2.5 1.2 3.1 3.8Ž . Ž . Ž .Ireland Potential 12 – 82 64 3 2Ž . Ž . Ž .Actual 9 – 103 38 9 4Ž . Ž . Ž .Ratio 1.2 – 0.8 1.7 0.4 0.4Ž . Ž . Ž .Italy Potential 440 – 1841 1337 48 23Ž . Ž . Ž .Actual 346 – 1320 660 57 15Ž . Ž . Ž .Ratio 1.3 – 1.4 2.0 0.8 1.5Ž . Ž . Ž .Netherlands Potential 86 – 834 591 24 11Ž . Ž . Ž .Actual 85 – 513 419 61 63Ž . Ž . Ž .Ratio 1.0 – 1.6 1.4 0.4 0.2Ž . Ž . Ž .Portugal Potential 16 – 84 73 3 2Ž . Ž . Ž .Actual 8 – 13 21 2 3Ž . Ž . Ž .Ratio 2.1 – 6.5 3.4 1.6 0.7Ž . Ž . Ž .Spain Potential 78 – 420 348 15 8Ž . Ž . Ž .Actual 26 – 261 141 10 2Ž . Ž . Ž .Ratio 3.0 – 1.6 2.5 1.4 4.7Ž . Ž . Ž .Sweden Potential 42 – 309 226 42 20Ž . Ž . Ž .Actual 46 – 284 146 215 189Ž . Ž . Ž .Ratio 0.9 – 1.1 1.5 0.2 0.1Ž . Ž . Ž .UK Potential 206 – 1638 1207 56 26Ž . Ž . Ž .Actual 130 – 866 535 57 57Ž . Ž . Ž .Ratio 1.6 – 1.9 2.3 1.0 0.5Ž . Ž . Ž .Sum Potential 1962 – 24,978 17,796 742 352Ž . Ž . Ž .Actual 2081 – 14,110 11,170 1678 885Ž . Ž . Ž .Ratio 0.9 – 1.8 1.6 0.4 0.4

Ž .Source: Own calculations. – Indicates that data are missing.


Hungary Latvia Lithuania Poland Romania

Ž . Ž . Ž . Ž . Ž .1405 751 22 9 47 20 38 404 250 108Ž . Ž . Ž . Ž . Ž .1876 1162 17 4 24 14 689 419 234 140Ž . Ž . Ž . Ž . Ž .0.7 0.6 1.3 2.1 2.0 1.5 1.2 1.0 1.1 0.8Ž . Ž . Ž . Ž . Ž .227 121 22 8 40 17 550 262 164 71Ž . Ž . Ž . Ž . Ž .375 240 48 12 52 27 880 505 140 112Ž . Ž . Ž . Ž . Ž .0.6 0.5 0.5 0.7 0.8 0.6 0.6 0.5 1.2 0.6Ž . Ž . Ž . Ž . Ž .141 75 23 9 38 16 500 243 103 44Ž . Ž . Ž . Ž . Ž .86 48 62 34 121 68 616 616 42 13Ž . Ž . Ž . Ž . Ž .1.6 1.6 0.4 0.3 0.3 0.2 0.8 0.4 2.5 3.5Ž . Ž . Ž . Ž . Ž .69 40 28 12 33 16 258 137 64 30Ž . Ž . Ž . Ž . Ž .153 52 194 33 114 27 467 288 20 5Ž . Ž . Ž . Ž . Ž .0.4 0.8 0.1 0.4 0.3 0.6 0.6 0.5 3.3 5.6Ž . Ž . Ž . Ž . Ž .818 454 75 30 139 61 1869 928 616 278Ž . Ž . Ž . Ž . Ž .604 433 36 15 66 43 1489 816 445 395Ž . Ž . Ž . Ž . Ž .1.4 1.0 2.1 1.9 2.1 1.4 1.3 1.1 1.4 0.7Ž . Ž . Ž . Ž . Ž .1726 984 174 71 331 150 9835 5062 1066 493Ž . Ž . Ž . Ž . Ž .4499 3230 353 162 536 353 8494 7407 1601 1258Ž . Ž . Ž . Ž . Ž .0.4 0.3 0.5 0.4 0.6 0.4 1.2 0.7 0.7 0.4Ž . Ž . Ž . Ž . Ž .71 51 5 3 10 6 128 84 113 66Ž . Ž . Ž . Ž . Ž .44 47 3 0 4 1 69 119 153 165Ž . Ž . Ž . Ž . Ž .1.6 1.1 1.7 7.0 2.5 4.1 1.8 0.7 0.7 0.4Ž . Ž . Ž . Ž . Ž .32 20 4 2 7 3 83 46 27 14Ž . Ž . Ž . Ž . Ž .65 11 11 8 9 31 132 51 16 4Ž . Ž . Ž . Ž . Ž .0.5 1.9 0.3 0.2 0.7 0.1 0.6 0.9 1.6 3.1Ž . Ž . Ž . Ž . Ž .1043 594 59 25 120 55 1666 861 839 386Ž . Ž . Ž . Ž . Ž .1265 927 58 13 108 61 2556 1068 1271 1136Ž . Ž . Ž . Ž . Ž .0.8 0.6 1.0 1.9 1.1 0.9 0.7 0.8 0.7 0.3Ž . Ž . Ž . Ž . Ž .272 153 29 11 52 23 702 353 198 90Ž . Ž . Ž . Ž . Ž .389 313 98 23 85 104 1086 1059 165 250Ž . Ž . Ž . Ž . Ž .0.7 0.5 0.3 0.5 0.6 0.2 0.6 0.3 1.2 0.4Ž . Ž . Ž . Ž . Ž .38 26 4 2 7 4 86 53 35 20Ž . Ž . Ž . Ž . Ž .36 9 1 0 9 14 21 33 11 8

Ž . Ž . Ž . Ž . Ž .1.1 2.8 4.7 4.7 0.8 0.3 4.1 1.6 3.2 2.4Ž . Ž . Ž . Ž . Ž .191 125 17 8 33 17 413 244 169 90Ž . Ž . Ž . Ž . Ž .178 114 10 7 27 24 456 215 82 84Ž . Ž . Ž . Ž . Ž .1.1 1.1 1.8 1.1 1.2 0.7 0.9 1.1 2.1 1.1Ž . Ž . Ž . Ž . Ž .127 73 39 17 51 24 484 253 107 50Ž . Ž . Ž . Ž . Ž .262 113 168 93 114 55 859 501 61 36Ž . Ž . Ž . Ž . Ž .0.5 0.6 0.2 0.2 0.4 0.4 0.6 0.5 1.8 1.4Ž . Ž . Ž . Ž . Ž .604 353 64 27 116 53 1500 785 472 224Ž . Ž . Ž . Ž . Ž .434 334 80 120 90 77 1549 809 261 208Ž . Ž . Ž . Ž . Ž .1.4 1.1 0.8 0.2 1.3 0.7 1.0 1.0 1.8 1.1

Ž . Ž . Ž . Ž . Ž .6763 3821 566 232 1022 464 18,912 9714 4224 1964Ž . Ž . Ž . Ž . Ž .10,267 7032 1138 525 1359 898 19,364 13,906 4502 3813Ž . Ž . Ž . Ž . Ž .0.7 0.5 0.5 0.4 0.8 0.5 1.0 0.7 0.9 0.5

( )continued on next page


Ž .Table 9 continued

Slovak Republic Slovenia Cyprus Sum

Ž . Ž . Ž . Ž .1989 978 680 513 29 22 7822 4459Ž . Ž . Ž . Ž .552 413 806 467 19 8 5730 3853Ž . Ž . Ž . Ž .3.6 2.4 0.8 1.1 1.6 2.9 1.4 1.2Ž . Ž . Ž . Ž .117 57 175 132 27 20 2093 1155Ž . Ž . Ž . Ž .125 89 141 65 56 26 2440 1404Ž . Ž . Ž . Ž .0.9 0.6 1.2 2.0 0.5 0.8 0.9 0.8Ž . Ž . Ž . Ž .71 34 84 63 16 12 1462 790Ž . Ž . Ž . Ž .36 26 32 38 27 4 1269 1020Ž . Ž . Ž . Ž .1.9 1.3 2.6 1.6 0.6 3.0 1.2 0.8Ž . Ž . Ž . Ž .31 17 37 31 10 9 1001 547Ž . Ž . Ž . Ž .50 31 29 16 15 2 2137 868Ž . Ž . Ž . Ž .0.6 0.6 1.3 1.9 0.7 5.0 0.5 0.6Ž . Ž . Ž . Ž .413 211 660 518 103 82 7260 4147Ž . Ž . Ž . Ž .260 154 700 551 133 15 4871 2954Ž . Ž . Ž . Ž .1.6 1.4 0.9 0.9 0.8 5.4 1.5 1.4Ž . Ž . Ž . Ž .943 494 1047 835 150 121 29,587 18,137Ž . Ž . Ž . Ž .1981 1499 1832 2176 251 47 28,004 23,161Ž . Ž . Ž . Ž .0.5 0.3 0.6 0.4 0.6 2.6 1.1 0.8Ž . Ž . Ž . Ž .29 19 43 43 41 42 668 414Ž . Ž . Ž . Ž .12 25 25 24 238 67 919 528Ž . Ž . Ž . Ž .2.5 0.8 1.7 1.8 0.2 0.6 0.7 0.8Ž . Ž . Ž . Ž .16 9 23 20 5 4 293 184Ž . Ž . Ž . Ž .17 6 14 9 24 5 410 167

Ž . Ž . Ž . Ž .1.0 1.6 1.6 2.2 0.2 0.9 0.7 1.1Ž . Ž . Ž . Ž .479 252 1843 1487 129 105 8507 5125Ž . Ž . Ž . Ž .521 364 1670 998 313 16 9485 5258Ž . Ž . Ž . Ž .0.9 0.7 1.1 1.5 0.4 6.4 0.9 1.0Ž . Ž . Ž . Ž .139 72 199 157 32 25 2566 1487Ž . Ž . Ž . Ž .143 137 169 104 62 15 2856 2488Ž . Ž . Ž . Ž .1.0 0.5 1.2 1.5 0.5 1.7 0.9 0.6Ž . Ž . Ž . Ž .18 11 28 27 7 73 327 218Ž . Ž . Ž . Ž .11 8 3 9 14 21 128 105

Ž . Ž . Ž . Ž .1.6 1.5 10.3 2.9 0.5 3.4 2.6 2.1Ž . Ž . Ž . Ž .90 54 147 136 33 31 1606 1060Ž . Ž . Ž . Ž .77 50 160 37 74 9 1362 683Ž . Ž . Ž . Ž .1.2 1.1 0.9 3.7 0.4 3.6 1.2 1.6Ž . Ž . Ž . Ž .60 32 71 58 17 14 1349 767Ž . Ž . Ž . Ž .53 42 77 49 52 3 2192 1227Ž . Ž . Ž . Ž .1.1 0.7 0.9 1.2 0.3 4.7 0.6 0.6Ž . Ž . Ž . Ž .301 162 448 370 142 67 5548 3274Ž . Ž . Ž . Ž .122 107 172 169 380 137 4141 2550Ž . Ž . Ž . Ž .2.5 1.5 2.6 2.2 0.4 0.5 1.3 1.3

Ž . Ž . Ž . Ž .4697 2404 5485 4390 740 628 70,091 41,764Ž . Ž . Ž . Ž .3959 2950 5830 4713 1657 374 65,943 46,267Ž . Ž . Ž . Ž .1.2 0.8 0.9 0.9 0.4 1.7 1.1 0.9


Ž .Gonciarz 1996 for the overvaluation of the CEECs’ GDPs results in a downwardrevision of the projections of CEEC–EU trade. They do not, however, adjust theEU countries’ GDP figures, which, to some extent, would counteract the down-ward projection of the estimates. The figures on the CEEC–EU trade potential in

Ž .Gros and Gonciarz 1996 are therefore likely to be too low.To support their results that CEEC–EU trade reached above AnormalB levels in

Ž . Ž .1992, Gros and Gonciarz 1996 refer to a study of Brenton and Kendall 1994 .Ž .Brenton and Kendall 1994 fit a gravity model to East–East and East–West trade

Ž .flows for 1992. They estimate a dummy variable for trade between the EU 12and the CEECs. On the basis of the positive and significant parameter of the

Ž .dummy, Gros and Gonciarz 1996 find support for their own result that tradebetween the EU and the CEECs already is above AnormalB.

Ž .The conclusion that Gros and Gonciarz 1996 draw from the study of BrentonŽ .and Kendall 1994 may be too far-reaching. The significant dummy variable

should be seen in relation to the reference group in the sample. Since the sampleconsists of East–East trade flows as well as East–West trade flows, the significant

Ž .dummy variable for trade between the EU 12 and the CEECs should beinterpreted as CEEC–EU trade being significantly greater than the average level ofEast–West and East–East trade. It is, however, doubtful whether the average levelof East–West and East–East trade in 1992 can be said to properly representAnormalB trade between industrialized western countries.

Following the start of the transition and reform process, there have beenconsiderable changes in the Candidate Countries’ GNPs and exchange rates. Notonly GNP growth in domestic currency influences a country’s potential trade, butalso GNP growth expressed in US dollars. The question is whether changes in theCandidate Countries’ exchange rates can contribute to explaining the variations inthe Candidate Countries’ levels of trade integration with the EU.

Table 8 presents the Candidate Countries’ exchange rates against the US dollarŽ .between 1993 and 1995, and indicates the extent in percent to which the national

currencies of the Candidate Countries have changed against the US dollar over theperiod. The currencies of six Candidate Countries have appreciated against the USdollar over the period, while the currencies of five Candidate Countries havedepreciated, regardless of whether the countries have traded above or below their

Ž .estimated potential level with the EU see Table 9 . The movement of theCandidate Countries’ exchange rates against the US dollar over the 1993–1995period thus fails to explain why some Candidate Countries’ trade was above theirpotential level while others’ was not.

6. Summary

This study updates the projections on the trade potential between the CEECsŽ . Ž .and the EU of Baldwin 1994 on data for 1989 and of Gros and Gonciarz 1996


on data for 1992, and analyses the differences between potential and actual tradebetween all Candidate Country–EU country-pairs. The results indicate that thedifferences between potential and actual trade have been reduced compared to the

Ž .study of Baldwin 1994 , and that EU trade with the Candidate Countries inseveral cases reached, and exceeded, its estimated potential by the mid-1990s.There is, however, still unused trade potential between some Candidate Countriesand EU countries. The results also indicate that trade among the CEECs hasincreased substantially and is significantly greater than what could be predicted bythe gravity model.

The results suggest that there is no difference between the Candidate Countriesas far as the degree of trade integration with the EU countries is concerned. Thehigh degree of trade integration with the EU indicates that all the CandidateCountries are competitive in the EU market. The European Commission’s conclu-

Ž .sion that the 5 would have difficulties to cope with the competitive pressure andmarket forces within the Union in the medium run must therefore be questioned.

Acknowledgements

Helpful comments from Yves Bourdet and three anonymous referees aregratefully acknowledged.

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Trade integration and the EU economic membership criteria