art%3a10.1007%2fs10290-005-0015-y.pdf

Growth Effects of Economic Integration:Evidence from the EU Member States

Harald Badinger

University of Economics and Business Administration, Vienna

Abstract: After compiling an index of economic integration that accounts forglobal (GATT) as well as regional (European) integration of the EU member stateswe test for permanent and temporary growth effects in a growth accounting frame-work, using a panel of fifteen EU member states over the period 19502000. Whilethe hypothesis of permanent growth effects is rejected, the resultsthough notcompletely robust to controlling for time-specific effectssuggest sizeable level ef-fects: GDP per capita of the EU would be approximately one-fifth lower today ifno integration had taken place since 1950. JEL no. C33, F15, F43, O52Keywords: Economic growth; economic integration; European Union; panel data

1 Introduction

The second half of the twentieth century was characterized by unprece-dented progress in both global and regional economic integration. Thedevelopment of the European Unions (EU) external and internal economicrelationships mirrors these two overlapping processes. Global economic in-tegration, here mainly considered as trade liberalization in the frameworkof the General Agreement on Tariffs and Trade (GATT), led to a reduction inthe EUs (formerly the European Communitys (EC)) harmonized externaltariff from some 17 per cent in 1968 down to 3.6 per cent in 2000. Withinthe same time, the EC expanded from six members originally to 15 mem-bers. These member states not only completely liberalized their intra-traderelations, but also established a Single Market, introduced a single currency,installed common institutions (European Council, European Commission,European Court of Justice) with considerable supranational competenciesand adopted common or co-ordinated policies in several important areas

Remark: I wish to thank Fritz Breuss for a number of helpful comments on an earlierdraft. This paper has also benefited much from the comments of an anonymous referee.Please address correspondence to Harald Badinger, Europainstitut, WirtschaftsuniversittWien, Althanstrae 39-45/2/3, A-1090 Wien; e-mail: [email protected]

2005 Kiel Institute for World Economics DOI: 10.1007/s10290-005-0015-y

Badinger: Growth Effects of Economic Integration 51

(such as monetary policy, external trade, agriculture, competition, energyetc.)

A question of great interest not only from an academic point of view butalso from an economic policy and public perspective relates to the conse-quences of this process for economic growth and thus human welfare. Froma theoretical point of view, both negative and positive effects of integrationare conceivable: Countries that are integrated into the world economy in-teract with one another in several dimensions. They trade goods on worldproduct markets, borrow and lend on world capital markets, and exchangeinformation through market and nonmarket channels. Many of these globalinteractions generate forces that accelerate growth in every country. But sev-eral suggest reasons why international integration might impede growth(Grossman and Helpman 1997: 336). Moreover, economic theory is stillsplit on whether the integration-induced effects on the growth rate are onlytemporary (neoclassical growth theory, endogenous growth theory withoutscale effects) or permanent (endogenous growth theory with scale effects).Thus, more empirical work on this issue seems warranted, given its obviouspolicy relevance. Being the most far-reaching integration project in history,the EU offers an example par excellence to test different hypotheses concern-ing the effects of economic integration on growth. Surprisingly, however,and in contrast to the large literature on trade, openness and growth (seeLewer and Van den Berg (2003) for a recent survey), there are only few stud-ies on this issue and with conflicting results. Landau (1995) finds no effectof EC membership on growth at all. In contrast, the results of Henreksonet al. (1997) point to a permanent effect on the growth rate, ranging from0.6 to 1.3 per cent per annum. More recently, the hypothesis of permanenteffects on the growth rate has been rejected again by Vanhoudt (1999).Obviously, a proper measurement of economic integration is a prerequisitefor the estimation of its effects; the variables used in previous studies on theeffects of European integration (such as dummies for membership in theEC and/or EFTA, length of membership, trade shares or market expansionas a result of the EC enlargements) may only be poorly correlated withthe actual liberalization process, which may in part explain the conflictingresults.

In this paper we compile a new measure of the EU-15s economic integra-tion, which captures both GATT liberalization and European integration.It considers all the relevant steps of European integration (EC, EFTA, tradeagreements between EC and EFTA in the 1970s, Single Market, EuropeanEconomic Area) and accounts for their continuous implementation. Using

52 Review of World Economics 2005, Vol. 141 (1)

this integration variable we go on to test for permanent and temporarygrowth effects of integration in a cross-country growth accounting frame-work, using a panel of the 15 EU member states over the period 19502000.While the hypothesis of permanent growth effects of economic integrationis strongly rejected, we find sizeable level effects of integration. GDP percapita of the EU-15 would be approximately one-fifth lower today if nointegration had taken place since 1950.

The remainder of the paper is organized as follows: Section 2 discussesthe theoretical background to the empirical model used in the estimations.Section 3 presents a new measure of economic integration for the EU mem-ber states. Section 4 describes the data used in the estimation of the empiricalmodels in Section 5. Section 6 summarizes the results and concludes.

2 Theoretical Background and Empirical Model

In order to provide a minimum formal framework for our discussion,we consider a simple CobbDouglas production function with constantreturns to scale Y = AKL , where Y is output, A is technology, K is capital,L is labour, and and = 1 denote the respective output elasticities.Dividing by labour and taking log differences we have

ln yt = ln At + ln kt, (1)where y = Y/L and k = K/L. From this common formulation it is easilyrecognized that integration may affect growth via one of two (supply-side)channels: technology, A, and physical capital, K. Accordingly, the literaturedistinguishes between technology-led and investment-led growth effects ofeconomic integration (Baldwin and Seghezza 1996).1

2.1 Integration-Induced Technology-Led Growth

The hypothesis that economic integration improves an economys overallefficiency is at least as old as Adam Smiths famous dictum that the divisionof labour is limited by the extent of the market (Smith 1789, Book I, Chap-ter III). More opportunities to exploit economies of scale in an increased

1 In a more general specification the production function would also include human capi-tal. Correspondingly, there is also a skills-led growth hypothesis. Since we obtained no sig-nificant results for human capital we omit this variable here from the beginning to sim-plify the exposition.


market are also stressed by Balassa (1961) as a propelling force of eco-nomic integration. Baldwin (1989, 1993) emphasizes the role of enhancedfactor mobility, lower trade costs and more competition in promoting aneconomys efficiency. A further rationale for the technology-led growth hy-pothesis is provided by Coe and Helpman (1995), who find that a countrystotal factor productivity is not only determined by its own R&D capitalstock, but also by that of its trade partners. By easing technology spill-oversfrom abroad, integration enhances a countrys opportunities to improve itsefficiency by participating in other countries technological progress.

Denoting the level of integration at time t with INTt , the technology-ledgrowth hypothesis can be written in its most simple form as

ln At = A0 + A1INTt, (1a)where A0 is an exogenous component of technological progress. Equa-tion (1a) as it stands postulates only temporary growth, i.e. level effectsof economic integration, as usually assumed in neoclassical growth theory,where the steady-state growth rate is determined only by an exogenous rateof technological progress. Alternatively, a permanent effect on the growthrate is conceivable, which can be formalized by replacing the progress inintegration INTt in (1a) with its level INTt , yielding

ln At = PA0 + PA1INTt. (1a)The hypothesis of permanent growth effects of integration emerges from en-dogenous growth theory with scale effects. Romer (1990) is a representativemodel, whichmainly as a result of assuming constant returns to the stockof knowledgeimplies that larger countries grow faster. Simply speaking,in this framework integration can be viewed as an increase in the size ofthe economy, leading to a higher steady-state growth rate.2 Endogenousgrowth models with scale effects were strongly criticized in an influentialpaper by Jones (1995); a number of endogenous growth models withoutscale effects have been developed since then (e.g. Young 1998). Predictingonly level effects of integration, their conclusions with respect to the growtheffects of integration can be reconciled with neoclassical growth theory. Inour empirical analysis, both competing hypotheses represented by (1a) and(1a) will be considered.

2 A formal treatment in a two-country version of the Romer (1990) model is given byRivera-Batiz and Romer (1991).


2.2 Integration-Induced Investment-Led Growth

In the light of the empirical evidence, some authors regard a two-chainlink between trade and growth through investment as more relevant thantrade-induced efficiency increases (Levine and Renelt 1992). Some intuitivereasoning on this investment-led growth hypothesis can already be foundin Balassa (1961), who stresses the role of integration in creating a morefavourable environment for entrepreneurial activities, reducing the riskpremium for investments (less uncertainty), and lowering the cost of capitalas a result of more efficient financial markets. Again, in the neoclassicalframework the postulated effects on the growth rate are only temporary. Inits simplest form, the investment-led growth hypothesis can be written as

ln kt = k0 + k1INTt. (1b)The corresponding hypothesis of permanent investment-led growth effectsis provided by the class of AK models, a branch of endogenous growththeory with a constant-returns-to-capital production function Y = AK.3However, AK models have been criticized for their knife-edge characterand empirically by Jones (1995: 509), who concludes that the AK modelsdo not provide a good description of the driving forces behind growthin developed countries. Once more, the existing evidence suggests that theinvestment-led growth effects of integration, if any, are only level effects, butthe hypothesis of permanent effects can again be easily tested by replacingINT with INT in (1b).

2.3 Overall Growth Effect of Economic Integration

With a view to the empirical analysis one could debate the need to dividegrowth between the accumulation of inputs and improvements in technol-ogy. For some questions of interest, this division is unnecessary, and shouldprobably be avoided. ... if the focus is a policy variable like inflation or the-budget positionor, as in our case, economic integrationit will oftenbe preferable to omit factor accumulation altogether and concentrate on theoverall growth effect of policy measures (Temple 1999: 150). This overall

3 Ignoring depreciation, an investment ratio of s implies that the capital stock and out-put grow at a rate of sA. If one is willing to assume that integration causes a permanentshift in the investment ratio s or the technology parameter A, a higher steady-state rate ofcapital accumulation and output growth would be the effect.


growth effect of integration is obtained by substituting (1a) and (1b) into(1), yielding

ln yt = 0 + 1INTt, (2)where 0 = A0 + k0, and 1 = A1 + k1. The hypothesis of permanentgrowth effects can be tested using

ln yt = P0 + P1 INTt. (3)In our empirical analysis we will depart from these models without factoraccumulation. Additionally, we will test (1a) and (1b) directly, as well asa quasi-reduced form of (1) and (1b) in order to assess the relative im-portance of the technology and the investment channel. Since we are notconcerned with the issue of convergence here, we regard this cross-countrygrowth accounting approach, which was (re-)introduced by Benhabib andSpiegel (1994) as an alternative to the convergence specification with theinitial level of income, as the more appropriate specification for our questionof interest.

3 On the Measurement of Economic Integration

Obviously, a proper measurement of economic integration is a prerequisitefor estimating its effects. Nevertheless, the choice of proper integration vari-ables has hardly attracted attention in the literature. Ben-David (2001), ina response to Slaughter (2001) who questions the convergence-stimulatingrole of trade obtained by Ben-David (1993) shows that a failure to distin-guish formal from actual periods of liberalization may lead to potentiallymisleading results. This criticism applies equally to previous studies on thegrowth effects of European integration which use crude integration variablesas zero-one dummies for membership in EC/EFTA, length of membershipsin the EC/EFTA (Landau 1995; Henrekson et al. 1997) or market expansiondue to the EC enlargements in terms of relative increases in the ECs popula-tion or GDP (Vanhoudt 1999). Obviously, such simple measures can hardlycapture the EU-15s complex process of post-war economic integration,which is summarized in Table 1. First, integration is a continuous process,not characterized by discrete jumps as reflected in zero-one dummies. Thecustoms union, for example, was implemented over a time period of 10years (19571968); similarly, DK, IE and the UK were given a transition


Table 1: Major Steps of EU Member States Post-War Economic Integration

European integration GATT liberalization

1944: Benelux Customs Union (BE, LU, NL)a) elimination of tariffs between BE, LU, NL,b) harmonization of external tariff (1950: 9%),(assumed) implementation: 19451950.

1950: Individual external tariffs (%)AT (20), BE (9), DE (16), DK (5),ESa (24), FI (13.5), FR (19), GRa (24),IEa (17), IT (24), NL (9), PTa (24),SE (6), UK (17).

1958: EC-6 (BE, DE, IT, NL, LU, FR): Customs Uniona) elimination of intra-EC-6 tariffs, b) harmoniza-tion of external tariff (1968: 16.8%), implementation:19581968.

1960: EFTA-7 (AT, CH, DK, NO, PT, SE, UK)elimination of intra-EFTA-7 tariffs, (1961: free tradeagreement FI-EFTA), implementation: 19601967.

19641967: Kennedy-Roundaverage (relative) tariff reductions: 47%,assumed implementation: 19681972.

1973: First EC enlargement (DK, IE, UK) EC-9a) elimination of tariffs between DK, IE, UK andEC-6, b) harmonization of external tariff, implemen-tation: 19731978.

1973: Free trade agreements between EFTA-6 and EC-9elimination of tariffs between EFTA-6 members (AT,CH, IS, NO, PT, SE) + FI and EC-9, implementation:19731978.

19731979: Tokyo-Roundaverage (relative) tariff reductions: 30%,assumed implementation: 19801985.

1981: Second EC enlargement (GR) EC-10a) harmonization of external tarif, b) elimination oftariffs between GR and EC-9, implementation: 19811985.

1986: Third EC enlargement (ES, PT) EC-12a) harmonization of external tarif, b) elimination oftariffs between ES and EC-10, implementation: 19861995.

19861993: Uruguay-Roundaverage (relative) tariff reductions: 40%,assumed implementation: 19941999.

1993: Single market (EU-12)4 freedoms + flanking measures (common policies),instantaneous implementation assumed.

1994: European Economic Area (EEA)partial implementation of four freedoms betweenEU-12 and EFTA-7 except CH (AT, FI, IS, LI, NO,SE), instantaneous implementation assumed.

1995: Fourth EC enlargement (AT, FI, SE) EU-15a) harmonization of external tariff, b) participationin Common Market, instantaneous implementationassumed.

Note: Country index: Austria (AT), Belgium (BE), Denmark (DK), (West)-Germany (DE), Finland(FI), France (FR), Greece (GR), Ireland (IE), Italy (IT), Netherlands (NL), Portugal (PT), Spain (ES),Sweden (SE), United Kingdom (UK), Luxembourg (LU). Monetary integration (1978: EMS, 1999:EMU) is not considered here. Data on tariff levels, size and timing of tariff reductions and tariff har-monization taken from Breuss (1983), El-Agraa (2001), and WTO (1995).a indicates missing values that were completed according to the relative position of a country ata later point of time for which data were available.


period of five years to implement the customs union after their accession tothe EC in 1973. Second, identifying the progress in the EU-15s economicintegration with EC enlargements is partly misleading, in particular for theformer EFTA countries (but also FI), which had already completely liber-alized their trade relationships with the EC in the free-trade agreements inthe 1970s, not only with their EC (EU) accession, which then only requiredthe harmonizing of the external tariff, andsince 1993the adoption ofthe Single Market Programme with its four freedoms. Finally, the EU-15seconomic post-war integration was not only driven by regional Europeanintegration, but also by global economic integration, viewed here as tradeliberalization in the framework of the General Agreement on Tariffs andTrade (GATT) (see Table 1, right column).

In this paper we propose a new measure of the EU-15s economic in-tegration, which takes both GATT liberalization and European integrationinto account. It captures all the relevant steps of European integration (EC,EFTA, trade agreements between EC and EFTA, Single Market, EuropeanEconomic Area (EEA)) and considers their continuous implementation.The integration index for country i is based on the following measure ofprotectionism

PROTi,t = Ti,t + TCi,t =J

j=1wij,t(tij,t + tcij,t), (4)

which is essentially a weighted sum of tariffs, tij, and trade costs, tcij, wherethe weights, wij, correspond to the share of country is trade with country j(imports plus exports) in the total trade of country i. If the trade regimes ofthe countries are symmetric, then Ti also measures (at least approximately)other countries protectionism against country i and TCi also measures theaverage trade costs of an enterprise of country i. At least changes in theprotectionism of each country should be highly correlated if liberalizationhas been conducted on the principle of reciprocity. In this case the index(PROT)although first a measure of country is protectionism against therest of the worldcan also be interpreted as a more general measure ofintegration of the according country with the world economy.

Let us first consider the calculation of the weighted tariff Ti in (4). Un-fortunately, there are no time series data for the tariffs of EU countries.We have, however, information on the initial tariffs in 1950 for most of thecountries and the relative size and timing of the tariff reductions followingthe according GATT rounds (see Table 1, right column). According to the


General-Most-Favoured-Nation Treatment (Article I of GATT) this gen-eral external tariff applies (should apply) to 100 per cent of trade, unlessthere are special agreements of regional integration (admissible under Art-icle XXIV of GATT). Starting from the initial level in 1950, the developmentof the EU-15s external tariffs was then shaped by the GATT tariff reductions(see Table 1, right column) and the requirement to adopt the ECs externaltariff after joining the EC. The ECs external tariff, in turn, was harmonizedby the establishment of the customs union between the original six ECmembers until 1968, and later on reduced after each of the GATT rounds.Figure 1 shows the corresponding development of the countries externaltariffs, ending up with a harmonized external tariff for all EU member statesof 3.6 per cent in 2000.

Figure 1: External Tariff af EU-15 Member States, 19502000

The process of regional European integration went beyond GATT lib-eralization, leading to a complete elimination of intra-EU and intra-EFTAtariffs, as well as of tariffs between EU and EFTA countries (see Table 1, leftcolumn). The calculation of the measure PROTi for the individual coun-tries requires a careful investigation of each countrys particular integrationhistory in order to identify when and how fast the tariffs against other EU


countries have been eliminated. The procedure cannot be outlined for eachcountry in detail here; the essential ingredients, however, are summarizedin Table 1.

In order to quantify the effect of the Single Market we use a measure ofweighted trade costs, TCi. The variable tcij is not an overall measure of tradecosts between country i and j, but is meant to represent only that extent oftrade costs between country i and j which has been eliminated by the SingleMarket. Following Smith and Venables (1988), we assume that the SingleMarket led to a reduction in trade costs, amounting to a tariff equivalentof 2.5 per cent. In the calculation of PROTi, tcij is added to the tariff tijapplicable to each trade flow, and set to zero as of 1993 for trade flowsbetween the EU-12 countries. The European Economic Area (see Table 1),which is relevant here for the relations between AT, FI, SE and the EU-12, isassumed to have halved tc in 1994. In 1995, after the EU accession of thesethree countries, the remaining half of tc is assumed to have been eliminated.Of course, the choice of a 2.5 per cent tariff equivalent of the Single Marketis somewhat arbitrary, but the same argument can be held against ignoringthe Single Market (i.e. setting the effected reduction in trade costs to zero).

In order to obtain our final index of integration INTi,t , we scale thereductions in PROTi,t with its initial value in 1950, giving the variableINTi,t the interpretation of the percentage of the total post-war integrationachieved by country i at time t:

INTi,t = PROTi,1950 PROTi,tPROTi,1950

. (5)

Beside its easier interpretation, this scaling has further advantages. First,it mitigates the uncertainty with respect to the initial tariff levels in the1950s, compared with the relatively good information on the timing andrelative size of the tariff reductions. Furthermore, the construction of INTi,tas index, which can vary between zero (initial degree of integration) and one(full integration), links the variable more closely to the theoretical modelsby Romer (1990) or Young (1998). Of course, these advantages come at thecost of ignoring differences in the absolute progress in integration: Initiallymore protectionist countries had a longer way to go and maybe also more togain. This point, however, may be addressed by testing for country-specificcoefficients of INTi in our panel estimation. Figure 2 shows the developmentof INTi,t for the aggregate EU-15 (weighted with shares of trade in total EUtrade) since 1950. The residual level of protectionism of some 13.2 (in per


Figure 2: Index of Integration for EU-15, 19502000

cent of its 1950 level) in 2000 is due to the external tariff of 3.6 per cent andthe trade costs of 2.5 per cent, both applicable to extra-EU trade (see (4)).

Of course, the variable INT is still far away from being a perfectmeasure of the EU-15s economic integration. The treatment of the SingleMarket is clearly not satisfactory yet. We also had to ignore the elimination ofnon-tariff barriers, on which no comprehensive information is available forthe time horizon of our investigation. Additionally, INT is based on averagetariffs for industrial goods and neglects industry-specific regimes such asthe Common Agricultural Policy (which is anything other than a policypromoting free trade). Finally, the variable INT also does not capture thecohesion policy of the EU, in particular the transfers to GR, PT, ES, and IE.After all, despite the remaining caveats, the variable INTi,t should mirror theactual process of the EU-15s post-war economic integration more closelythan simple dummy variables or trade shares and provide a reasonableapproximation for our purposes.

4 Data

Table 2 shows the variables and data used in the estimation of the empiricalmodels derived above. We use a panel of the 15 EU member states overthe period from 1950 to 2000. Since Luxembourg had to be excluded due


Table 2: Description of the Variables Used in the Estimation

Variable Description Units Sources

ln yi,t Average growth rate of GDP per worker(Y/L). Y = real GDP in US $ (1990prices, 1990 PPPs), L = employment innumber of persons.

% p.a. OECD: National Accounts,Economic Outlook; Maddi-son (1992).

ln ki,t Average growth rate of capital perworker (K/L). K = real capital stockin US $ (1990 prices, 1990 PPPs),calculated using a perpetual inventorymethod: Kt = Kt1(1 ) + It , withIt = gross fixed capital formation, =depreciation rate (assumption: 5%).Initial level: K1955 = IHP55/(gI,50-60),where IHP55 = HodrickPrescott fil-tered level of investment in 1955,gI,50-60 = average growth rate p.a. ofinvestment from 50 to 60 (de la Fuenteand Domnech 2000).

% p.a. OECD: National Accounts.

INTi,t (Absolute) change in level of integra-tion = (INTi,t) (INTi,t1), whereINTi,t = average level of integrationin period t.

% p.a. IMF: IFS; DoT; El-Agraa(2001); Breuss (1983); owncalculations; see Section 3.

ln hi,t Various measures of human capital(mean years of schooling, attainmentrates).

years%

Barro and Lee (2000); dela Fuente and Domenech(2000).

i,t Average growth rate of GDP deflator. % p.a. OECD: National Accounts;IMF: IFS; Maddison(1992).

OPENi,t Openness: (real) imports plus exportsin per cent of GDP.

% OECD: National Accounts.

Note: i = 1, ...,14, t = 1, ...,10 (5-year intervals, 19502000). There are some missing obser-vations for the period 19501960 which had to be approximated by inter/extrapolation.

to missing data, 14 countries remain. To smooth out cyclical fluctuationsand distortions by short-run shocks, we use overlapping, five-year averages(t = 110: 19501955, 19551960, ..., 19952000) and calculate the averageannual growth rates of our variables by running least squares of the respec-tive log levels on a time trend. This is preferable to using log differences,


since both the initial and the level at the end of the period may be consid-erably off the trend path of output (Temple 1999: 119). As output measurewe use real GDP data (in 1990 prices, 1990 PPPs) from the OECD ratherthan Penn World Tables (PWT) data; thus the calculated growth rates areequal to the real growth rates in national currencies.4

5 Estimation Results

Table 3 reports the estimation results for the empirical models outlinedabove. To control for the substantial slowdown of growth since the early1970s, which followed the golden age of high economic growth in Europefrom 1950 to 1970 (Maddison 1995), we include a level dummy (D70-00),taking a value of zero for the periods 14 (19501970) and a value of1 for the periods 510 (19702000). At the bottom of Table 3, we alsoreport F-Tests for the null of parameter homogeneity across countries.Since the hypothesis of a common parameter is rejected for the interceptand D70-00 in de facto all models, we use a fixed effects specification withvariable intercept and allow the coefficient of D70-00 to vary across countries.In Table 3, however, only averages of the country-specific intercepts andcoefficients of D70-00 are reported. The first two columns show the leastsquare dummy variable (LSDV) estimates of our empirical models (2) and(3), controlling for the slowdown of growth in the 1970s by D70-00. The levelof integration (INT), corresponding to the hypothesis of permanent growtheffects, is insignificant and also shows the wrong (negative) sign (column(a)); even if we allow for heterogeneous coefficients (as might be suggestedby the F-statistic, whose p-value is only slightly above the 10 per cent level),only 5 coefficients turn out significant, 3 of which with the wrong sign.These results can be enforced by unit root tests on yearly time series of thevariables, a testing strategy suggested by Jones (1995): While AugmentedDickeyFuller tests indicate that ln yi,t is stationary for all countries, the

4 Nuxoll (1994) shows that growth rates calculated from data measured at internationalprices (like the PWT) may be systematically distorted by the so-called Gerschenkron ef-fect. Although the PWT do not exhibit a serious bias due to the high level of aggregation,their growth rates differ from the national accounts data growth rates. Consequently, Nux-oll (1994: 1434) argues that using domestic prices to measure growth rates is more reli-able, because those price characterize the trade-offs faced by the decision-making agents,and hence have a better foundation in the theory of index numbers. Probably the idealis to use Penn World Table numbers for levels and the usual national-accounts data forgrowth rates.


Table 3: Panel Estimates for EU Member States, 19502000

Dependent variable: ln yi,t(a) (b) (c) (d) (e) (f) (g) (h)

Intercepta 4.186 3.791 4.967 4.303 4.119 2.172 2.438 2.053

D70-00 a 1.101 2.178 2.146 2.570 2.579 0.903 1.258 1.003

INTi,t 0.277 0.284 0.220 0.306 0.139 0.104 (5.84) (4.39) (3.85) (2.09) (2.58) (2.49)

INTi,t 0.059 ( 1.43)

ln ki,t 0.346 0.271 0.346 (6.88) (4.63) imposedb

ln yi,t1 0.008 ( 0.01)

OPENi,t 0.024 ( 0.54)

i,t 0.010 ( 0.19)

F-tests for parameter homogeneity

Intercept 2.07 1.98 1.18 2.95 1.34 1.38 1.66

D70-00 1.89 2.48 1.88 2.87 1.72 1.93 1.72

INTi,t 0.76 0.77 1.16 0.77 0.69

ln ki,t 1.25 1.72 INTi,t 1.56 1.25 1.72 0.79Regression statistics

SEE 1.177 1.079 1.094 0.931 0.984 1.024 1.006 1.009

R2 0.562 0.631 0.641 0.710 0.679 0.668 0.682 0.406

Adj. R2 0.451 0.538 0.522 0.593 0.549 0.584 0.599 0.256

Period 19502000 19552000 19652000 19502000T = 110 T = 210 T = 410 T = 110

, , indicate significance at the 10, 5 and 1 per cent level respectively.Note: t-values in parentheses (calculated using White heteroscedasticity-consistent standarderrors). All models except (e) estimated using the LSDV approach. Model (e): first-differences GMM estimation of (b), using lagged differences as instruments for INTit ,starting with lag two (INTi,t2). GMM estimation was carried out using DPD98 by Arel-lano and Bond (1998).a Reported numbers are averages of country-specific coefficients. b Coefficients imposedaccording to the average income shares of capital (19871989) reported by Coe and Help-man (1995) (primary source: OECD, Analytical Database), AT: 0.358, BE: 0.355, DE: 0.401,DK: 0.338, ES: 0.391, FI: 0.331, FR: 0.354, GR: 0.29, IE: 0.281, IT: 0.376, NL: 0.390,PT: 0.328, SE: 0.338, UK: 0.311, EU: 0.346.


null of a unit root cannot be rejected for any of the indices INTi. Thus, therecannot be a long-run equilibrium relationship between the two variables,at least not in the linear form as postulated by (3).

On the contrary, the change in the variable INT, corresponding to thehypothesis of levels effects of integration, enters significantly at the 1 per centlevel (column (b)).5 Interestingly, the restriction of a common coefficientfor INTi across countries cannot be rejected; given the construction ofINT as an index, whose absolute change from 1950 to 2000 varies onlyslightly across countries (see Section 3), the gains from integration (in percent of their own GDP) seem to have been shared symmetrically amongthe EU member states. The same results are obtained in tests of parameterhomogeneity between groups of large and small countries. The coefficientof INT is not only statistically but also economically significant: as willbe outlined more in detail below, the implied level effect on the EUs GDPper capita amounts to some 26 per cent. Finally, note that the numbersreported for the fixed effects and D70-00 show a plausible dimension: Onaverage, annual growth was lower by some 2 per cent in the period since1970, a value similar to that reported by Maddison (1995: 64, 79).

Of course, this result requires some sensitivity analysis. The most criticalfeature is that the inclusion of a full set of time dummies renders INTinsignificant. This is not really surprising: The synchronization of many lib-eralization steps leads to a very high partial correlation between the variableINT and the time dummies (a regression of INT on 8 time dummies(and D70-00) yields an R2 of 0.77). On the other hand, the time dummies,capturing a large part of the variation of INT, may also be interpreted toreflect integration effects; of the five time dummies that enter significantly,all but one (for the period 19551960) take a positive value and their (net)level effect is comparable to that implied by the coefficient of INT. Againstthis background and since time-specific institutional changes have also beendriven by European integration to some extent, we do not regard it as plau-sible to interpret the effect of INT as spurious; but of course, we cannot besure that the dummies do not actually capture omitted variables unrelatedto integration. Thus a skeptic might still argue that the time dummies re-flect the positive effect of institutional and structural factors that vary overtime but not across countries, and that integration had no effect. Hence thevariable INT is in some way also vulnerable to Rodriguez and Rodriks

5 Adding the level INT to the specification in column (b) does not change the results.INT is still significant with de facto the same coefficient; INT remains insignificant.


(2001) well-known critique (though their primary concern relates to thecross-country variation in institutional characteristics that may be mistak-enly captured by trade variables). Even with an improved measurement ofintegration, collinearity problems will continue, to some extent inevitably,to aggravate the firm and unambiguous empirical establishment of the linkbetween integration and growth.

We carry on with our preferred model in column (b) in order to seewhether our results are also sensitive to other robustness checks. We firstcheck the sensitivity with respect to changes in the estimation period, re-estimating the model without factor accumulation (column (b)) for allpossible sub-periods including at least 6 observations (30 years), whichyields us 13 models. The coefficient of INT varies between 0.19 and 0.32but always remains significant at the 1 per cent level (see Table A1 in theAppendix for the detailed results). We also ran the regression for the sub-periods 14 and 510 without D70-00. Again the significance level of INTis unchanged, but its coefficients for the periods 14 appear to be higherthan for the periods 510. The significance of this difference can be testedin a regression for the total period (110) by including an interaction termof INT and D70-00. Its coefficient is negative as expected and significant atthe 10 per cent level (p-value: 0.055); the implied parameters for INT50-70and INT70-00 amount to 0.43 and 0.21 respectively. In the light of the weaksignificance of the interaction term, however, we continue with one coeffi-cient for the whole time period, but add that the size of the implied growtheffects over the total period hardly differs between the two specifications.

As shown by Levine and Renelt (1992), it is also important to check therobustness of the results against the inclusion of further variables. We addthree control variables: First, one could object that INT simply measurescatching-up in the course of post-war reconstruction. Against this can beheld that by 1950 recovery from war was complete and Europes economieswere back on their pre-war growth paths (Maddison 1995: 71). Nevertheless,we check the robustness of the results against including the initial levelof output per worker (yi,t1). Second, we include the rate of inflation (proxied by the relative change in the GDP deflator), since Henrekson etal. (1997) find in their cross-section growth regression that the dummy forEC/EFTA membership becomes insignificant, when inflation is controlledfor. Third, we include the change in the share of trade in GDP (OPEN), orits level (OPEN), as general indicator for openness. Column (c) in Table 3shows the results, when all variables are jointly added to the specification incolumn (b), but the conclusions do not change, whatever combination of the


variables is used or if the variables are added separately. The control variablesare never significant and the coefficient of the variable INT is hardlyaffected. The same holds true if the level of OPEN is included instead of itschange. Repeating this robustness analysis for different estimation periods(see Table A1 in the Appendix for details) we obtained the following results:Including inflation or openness never affects the significance of INT.Including the initial level changes the significance of INT in 6 of the 15models: In 4 cases it remains significant at the 10 per cent level; only in 2cases is it rendered insignificant. This is probably due to the aforementionedfact that the coefficient of INT is smaller for the period 19702000, sinceall cases in which INT is fragile focus on this later period. Running theregression over the whole period 110 and controlling for the lower effectof INT since 1970 by an interaction term between INT and D70-00,however, INT (and the interaction term) remains significant at the 1 percent level, whatever combination of the control variables is included. Afterall, we may carefully conclude that economic integration has had a leveleffect on the EU-15s post-war growth path, which appears to be have beenmore pronounced in the period from 1950 to 1970.6

A further concern often raised in the context of growth regression isthe potential endogeneity of the right-hand side variables; also for eco-nomic policy measures such as integration one could argue that causalitymay run in the reverse direction: It may be politically easier to liberalizein periods of high growth, while in times of poor performance it may betempting to introduce protectionist measures. To check the sensitivity ofthe results, we employ a first-differences GMM estimator for the modelin column (b). As instruments for the variable INT in second differences(INTit), all available lags of its first difference dated t 2 and earlierare used (INTi,ts, s 2). Though originally introduced in the contextof dynamic panels (Arellano and Bond 1991), the extension of this GMMframework to problems like measurement error and endogeneity of theright-hand side variables is straightforward (Bond et al. 2001). Unfortu-nately, this approach implies a loss of three observations, which is particu-larly hurtful in our case, since we have to exclude the period of the customsunion. To ensure comparability, Table 3 shows the results of both the LSDV(column (d)) and GMM estimation (column (e)) for this shorter period

6 It is well known that the LSDV estimator is biased in dynamic panels (see Nickell 1981).The conclusions for our dynamic models (including yi,t1) do not change, however, whenthe first-differences GMM estimator by Arellano and Bond (1991), a consistent estimatorfor dynamic panels, is used.


from 1965 to 2000. INTi remains highly significant; its coefficient evenincreases compared with the LSDV estimate. This result, however, has tobe qualified in the light of the ambiguous results concerning the validity ofinstruments: A Sargan test of overidentifying restrictions cannot reject thenull of valid instruments (p-value: 0.58). In contrast, the null of the absenceof second-order serial correlation, a requirement for instrument validity, isrejected at the 10 per cent level (see Arellano and Bond (1991), for details onthe instruments tests). A possible interpretation of the insignificant Sargantest in the presence of second-order serial correlation is that INTi,t mightin fact be only predetermined, ruling out contemporaneous correlation be-tween INTi,t and the error term i,t (i.e. E(INTi,ti,s) = 0, all i, s < tinstead of s t as in the case of endogeneity).

Summing up, our preferred specification without factor accumulationis given by column (b) in Table 3. In a next step, we add factor accumulationin order to assess the importance of the respective channels in promotingthe EUs post-war growth. Despite using several measures of human capitalsuch as attainment rates or mean years of schooling from both the Barroand Lee (2000) as well as the de la Fuente and Domnech (2000) dataset,we could not find a significant and robust human capital variable. Thus, weonly show the results for physical capital here. Levine and Renelt (1992) findthat investment ratios are robustly correlated with openness while growth ofoutput is not, once investment is controlled for. It is thus interesting to testwhether technology-led growth effects have been significant in our sample.

Column (f) in Table 3 shows the results including only the growth ofphysical capital per worker ( ln k); its coefficient is highly significant andpoints at an elasticity of 0.35, a value which is strikingly similar to the EU-15saverage share of capital income at the end of the 1980s as reported by Coeand Helpman (1995; see note of Table 3). The results when both INT andk are included (column (g)) are of higher interest to us: The coefficient ofINT falls relative to the model without factor accumulation in column (b)as expected, but remains clearly significant, indicating that technology-ledgrowth has played a role.7 To address the endogeneity concerns with respectto ln k, one could again run a two-stage estimation, however, only at thecost of losing observations, let alone the problems in finding good instru-ments. In order to escape from this dilemma we impose the coefficients on ln k according to the country-specific income shares of capital reported by

7 As in the model without factor accumulation, tests for permanent (technology-led)growth effects yielded no significant results.


Coe and Helpman (1995). The results for these restricted estimates, whichactually correspond to a direct test of the empirical model (1a), are shownin column (h). The coefficient of INT is still highly significant, thoughsomewhat lower than the unrestricted estimate. Comparing the coefficientof INT in columns (g) and (h) with that of the model without factor accu-mulation (column (b)), we may carefully conclude that both investment-ledand technology-led growth played a significant role, with investment-ledgrowth accounting for some 5063 per cent of the total effect. Here, therelative contribution of investment-led growth was calculated as residual bydeducting the estimated technology-led growth effect from the total effectimplied by the results in column (b). Of course, this issue can also be tackledfrom the other side, i.e. by calculating the technology-led growth effect asresidual, deducting the estimated investment-led growth effects from thetotal effect. The investment-led growth effects are obtained by directly esti-mating model (1b), i.e. regressing the growth of the capital stock on INT(Table A2), and then translating this effect on the capital stock into outputeffects using either the estimated coefficients of ln k from column (g) orthe corresponding capital shares (see note of Table 3). Since none of theseapproaches can a priori be said to be superior we provide a range of estimatesof the possible distribution between technology and investment-led growtheffects in the simulation below. Before proceeding with the simulation itis worth noting that in none of the models in Table 3, the hypothesis ofa homogenous parameter for INT for all countries can be rejected; thesame holds true for the direct estimates of the investment-led growth effects(Table A2); i.e. neither technology nor investment-led growth effects havefallen disproportionately on particular member states, or on small or largecountries.

We go on to use our preferred specifications to simulate the level effectsof integration. The preferred model without factor accumulation (Table 3,column (b)) is used to simulate the overall effect. The results are given inTable 4, which shows both the actual level of GDP per capita in 2000 aswell as its hypothetical level if no integration had taken place since 1950(i.e. INTi,t = 0, all i, t). As can be seen from column (d), integrationhas induced sizeable level effects, amounting to some 26 per cent for theaggregate EU (or some 20 per cent in terms of actual values (b)); country-specific values deviate only slightly, indicating that there have been noobvious asymmetries in the gains from integration. As outlined above,different approaches to assessing the relative contributions of investmentand technology-led growth are possible. First, for a given total effect, either


technology-led or investment-led growth effects can be estimated, with thecontribution of the other channel being calculated as residuals. Second, ineach case the estimated or the calibrated parameters of ln k can be used.Column (e) shows the minimum and maximum outcome for the shareof investment-led growth effects in the total effect for each country. Theoverall results indicate that both integration-induced increases in efficiencyas well as induced investments played a significant role in promoting theEU-15s post-war growth. Accounting for one-half to three-quarters of theoverall effect, investment-led growth effects seem to have been slightly moreimportant.

Table 4: Growth Effects of Economic Integration for EU Member States, 19502000

GDP per GDP per GDP per Total level Investment-led effectworker 2000 capita 2000 capita 2000 effect as as % of total effect

actual no integration % of (c) from to

(a) (b) (c) (d) (e)

AT 40,288 20,078 15,716 27.8 53.0 72.0BE 50,815 19,715 15,806 24.7 52.7 71.9DE 47,732 20,417 16,255 25.6 52.8 80.3DK 41,857 21,403 17,482 22.4 52.5 67.6ES 40,483 14,653 11,436 28.1 53.1 79.7FI 43,013 19,363 15,517 24.8 52.7 67.5FR 49,629 19,885 15,682 26.8 52.9 71.2GR 29,484 10,958 8,570 27.9 53.0 58.7IE 50,307 22,411 17,802 25.9 52.9 57.3IT 50,969 18,460 14,537 27.0 52.9 76.8NL 45,509 19,974 16,103 24.0 52.6 78.8PT 25,137 12,184 9,456 28.9 53.1 66.9SE 41,481 19,429 15,971 21.6 52.4 67.4UK 39,849 18,707 14,907 25.5 52.8 62.8

EU 44,577 18,549 14,709 26.1 52.9 73.2

Note: (a), (b), and (c) in US$ at 1990 prices, 1990 PPP. Per capita values calculated by mul-tiplying the simulated values (per worker) with the employment/population ratio.

It is reassuring that our results are not far off those from other studieson the relationship between trade (openness) and growth. In particular,Henrekson et al. (1997), in a cross section covering the period 19751987,obtain an effect of European integration (measured with EC/EFTA mem-


bership dummies) on the growth rate in a range from 0.6 to 1.3 per cent p.a.(which the authors favour to interpret as permanent effect on the growthrate). With a level effect of some 26 per cent over 50 years, the effect onthe average growth rate implied by our results amounts to some 0.5 percent, which is in line with the Henrekson et al. study. In contrast to theirinterpretation as a permanent effect, however, our results suggest that theeffects of integration are only of temporary nature.

Our results are also compatible with the closely related literature ontrade and growth. Greenaway et al. (1998), in a panel approach with 73countries (mainly developing countries), obtain a level effect of openness(measured with the SachsWarner index) of some 46 per cent; regardedas long-run difference in GDP per capita between more open and moreclosed economies they regard this as a reasonable number. The compre-hensive survey of studies on the relationship between trade and growthby Lewer and Van den Berg (2003) finds surprisingly consistent results:a 1 percentage point increase in export growth is associated with a one-fifthpercentage point increase in economic growth. Against the background ofthe rapid growth of the EU-15s trade since 1960 (some 6 per cent p.a.)and the significant contribution of European integration to the growthof trade (Badinger and Breuss 2004), our estimates are of a comparabledimension.

Our results concerning the role of investment-led and technology-ledeffects are broadly consistent with the few previous studies that attempt todistinguish between the effects of trade on factor accumulation and technol-ogy. In Frankel and Romer (1999), two-thirds of the growth effect (of trade)materialize over technology, one-third over (physical and human) capi-tal accumulation. Wacziarg (2001), using a simultaneous equation model,finds that 63 per cent of the overall effect are investment-led, 22.5 per centtechnology-led (the rest is mainly due to stabilizing economic policy). Ourresults reinforce the view that both induced capital accumulation and in-duced technological advances are important channels via which growtheffects of economic integration materialize.

As final important point, our results have to be interpreted in a broaderinternational setting. In comparing the EUs post-war growth performancewith that of other countries, it is important to bear in mind that our integra-tion variable reflects European integration and GATT liberalization. ThusEuropean integration itself, strictly speaking, only accounts for integrationthat went beyond GATT liberalization. Other countries (such as the UnitedStates) also participated in the GATT agreement and thus also experienced


substantial economic integration. Nevertheless, progress in integration wascertainly more pronounced for the EU countries than for the United States.If integration generated level effects as suggested by the estimates, the EUshould have caught up in terms of real GDP per worker against the UnitedStates. This has indeed been the case: In 1950 the EUs GDP per worker wassome 40 per cent that of the United States; in 2000 it amounted to some80 per cent (see Maddison (1995) for a more detailed discussion of thiscatching-up process). Since the European economies were back on theirpre-war growth path by 1950 (Maddison 1995: 71) this catching-up can-not be purely attributed to reconstruction and it may be argued that theEU countries would have kept farther behind the United States withoutEuropean integration.

The question whether the post-war evolution of living standards betweenthe EU and non-EU members is significantly related to European integrationmay also be judged more rigorously by regressing the EUs GDP per workerrelative to that of some control country j (yEU,t/yj,t ; j = the United States,Australia, New Zealand, Japan, Canada, Norway, Switzerland, and Iceland)on the (lagged) level of the EU-15s integration (INTEU,t1):8

yEU,tyj,t

= + yEU,t1yj,t1

+ sEU,tsj,t

+ uEU,tuj,t

+ INTEU,t1 + t.(6)

The lagged dependent variable is included to allow for a more generaldynamic structure of the model; two further variables are included: therelative investment ratio, sEU,t/sj,t , to control for neo-classical catching-up,and the relative unemployment rate, uEU,t/uj,t (taken from the AMECOdatabase), since typical increases in EU unemployment tended to makeGDP per worker grow even without real GDP growth.

Table 5 reports the estimation results of (6) for the time period 19602000, using several control countries. Where the relative unemployment rateor the relative investment ratio turned out insignificant, they were excludedfrom the final regression (the values reported for the other variables andthe regression statistics are that of the final model). For all control countries

8 The integration measure for the EU is calculated as weighted average of the countryvalues (see Section 3) and divided by 100 (to obtain a more comfortable coefficient),where the respective countries shares in the EUs total trade (again imports and exports)are used as weights. The lagged value is chosen because it yields a (slightly) better fit. Thisis not implausible since integration effects require some time to materialize. The conclu-sions are not altered, however, when the contemporaneous value is used.


Table 5: Estimation Results for Catching-Up Specification (6), 19602000

Dependent variable: yEU,t/yj,t

US CA AU NZ JP CH NO IS

Intercept 0.001 0.078 0.144 0.201 0.118 0.031 0.196 0.564(0.04) (3.33) (1.37) (2.681) ( .94) (2.16) (2.45) (3.94)

yEU,t1/yj,t1 0.898 0.897 0.531 0.747 0.851 0.967 0.857 0.417(23.58) (22.25) (5.29) (6.99) (9.69) (43.99) (12.50) (3.23)

sEU,t/sj,t 0.044 0.009 0.177 0.034 0.308 0.092 0.050 0.094(2.63) ( .33) (2.62) (0.99) (1.74) ( 1.37) ( 2.24) (2.72)

uEU,t/uj,t 0.003 0.006 0.056 0.001 0.002 0.001 0.007 0.003( 0.44) (0.25) (3.06) (0.79) (0.32) ( 1.26) (1.48) ( 2.82)

INTEU,t1 0.047 0.033 0.159 0.158 0.098 0.019 0.016 0.090(2.54) (1.72) (4.33) (2.04) (1.75) (1.89) ( 1.60) (3.26)

Implied leveleffect (%)a 43.1 23.9 23.0 38.2 46.3 (0) 10.7

Regression statisticsLM-SCb 2.85 9.31 5.42 7.64 0.989 11.46 3.89 6.82SEE 0.008 0.010 0.018 0.028 0.022 0.012 0.017 0.028Adj. R2 0.996 0.994 0.931 0.979 0.989 0.995 0.849 0.880

, , indicate significance at the 10, 5 and 1 per cent level respectively.Note: t-values in parentheses, calculated using White heteroscedasticity-consistent standard errors. Estimation period for AU is 19642000 for reasons of data availability.a Calculated as difference between actual relative GDP per worker in 2002 and the hypothetical valuewithout integration ((yEU,2000 yno INTEU,2000)/yj,2000), divided by the actual relative GDP per worker in2000. The hypothetical scenario without integration (yno INTEU,2000/yj,2000) is obtained from a dynamicsimulation of the estimated equation (6), assuming that the level of integration remained at that ofthe first observation (residuals were included to reproduce the actual values in the baseline scenario). b LM test of Breusch (1978) and Godfrey (1978) for serial correlation, assuming a maximum orderof five; chi-square distributed with five degrees of freedom (choosing a lower order from one to fourproduces no further significant results). For CA and CH where the residuals exhibit serial correlationNeweyWest standard errors were used (explicit adjustment for autocorrelationthe more appropri-ate answer to serial correlation in the presence of a lagged dependent variabledoes not change theresults for the integration variable, suggesting that the degree of inconsistency is negligible).

except Norway the integration variable enters significantly at least at the10 per cent level.9 This suggests that the EU-15s integration has supportedthe EUs catching-up process, or to put it differently: Without integration

9 In three cases the results are sensitive to including the insignificant investment ratio andunemployment rate: For CH and NZ the coefficient of INT becomes insignificant; for NOit becomes negatively significant.


the EU would have kept (farther) behind the living standards of otherOECD countries.10 The level effects implied by the estimates are reportedin the lower part of Table 5 and range from 10.7 (0 for Norway) to 46.3per cent, compared with the level effect of 20 per cent obtained in ourpanel estimates (Table 4). Note that in the regressions with the largestlevel effects implied, the standard errors of the coefficients of INTEU arefairly large, such that the 20 per cent result is conveniently contained instandard confidence intervals. There is no convincing explanation for theinsignificant result for Norway: The fact that it underwent a very similarintegration scheme as the EU members is also true for Switzerland andIceland where a significant result is obtained; it may be due to the littlevariation in the dependent variable, since the living standards of the EUand Norway evolved very similar, implying an almost constant dependentvariable.

One could argue that it would be a better approach to replace thevariable INTEU (which measures the relative progress in the EU-15s in-tegration, see Section 3) by the ratio of the absolute level of integrationof the EU to that of the control country. This is ruled out for reasonsof data availability, however; after all, the reduction of our sample to theEU-15 is the cost of using an improved integration measure. Against thisbackground, (6) is a feasible compromise which allows us to judge the re-sults for the EU sample in a broader international setting and provides uswith an additional robustness check. The particular values of the coeffi-cients, however, should not be overstressed. Overall the significant resultsfor the integration variable buttress the conclusions obtained so far; atthe same time the suggested contribution of the EU-15s integration toits catching-up process in the post-war period adds another qualification:The results may be specifically within-EU effects and cannot easily begeneralized.

6 Conclusions

This paper provides support for the hypothesis that European integrationhas significantly contributed to the post-war growth performance of the

10 Of course, assuming that the EU-15s integration had not taken place ceteris paribus issomewhat artificial, particularly in comparison with the other European countries (CH, IS,NO) that did not join the EU but who underwent very similar integration schemes (EFTA,free trade arrangements with EC, European Economic Area (except CH)).


current EU member states. Although the results imply that growth effectshave only been of temporary nature, the suggested level effects are sizeable:GDP per capita of the EU would be approximately one-fifth lower todayif no integration had taken place since 1950. An important qualification isthat the results are not completely robust to controlling for time-specificeffects which are highly correlated with our integration variable due to thesynchronization of many integration steps. Additional research is neededto establish more firmly the link between integration and growth, despiteincreasing and surprisingly consistent evidence: Until we agree on a logicalexplanation why trade [integration] and growth go together, it is not likelythat we will agree that the statistical results have settled the matter (Lewerand Van den Berg 2003: 391).

The size of the level effects suggested by our estimates supports Templesargument that undervaluing level effects is fundamentally misguided. ... Itshould not worry us that long-run growth ... is unresponsive to policy;instead level effects ... should be central to policy analysis (Temple 2003:509). In contrast to previous studies, we find that the ties between integra-tion and growth run both over increases in efficiency as well as inducedinvestments. Accounting for one-half to three-quarters of the total effect,however, investment-led growth seems to have been slightly more import-ant. A further noteworthy result is that the hypothesis of symmetric gainsfrom integration cannot be rejected, i.e. no obvious small- or large-countrybonus appears to exist.

Our estimates also suggest that the EUs post-war catching-up processvis--vis the United States and other countries was supported significantlyby the process of European integration. Hence, the results obtained heremay be specifically within-EU effects and cannot easily be generalized,e.g. to countries that have moved very close to the technology frontier (suchas many EU member states today). Taken together with the rejection ofpermanent growth effects this has an important policy implication: Thegrowth stimulating effect of integration, achieved so far, holds no promisefor the EUs future performance. To achieve the ambitious goal set out bythe European Council in the Lisbon Strategy in 2000 (becoming the mostcompetitive and dynamic knowledge-based economy), or to keep at least upwith the United States in the twenty-first century, substantial challengessuch as making the Single Market more dynamic, boosting investmentinto knowledge and improving the macroeconomic policy framework ofEuropean Monetary Union (Sapir et al. 2003)will have to be met by theEU and its members states.


Appendix

Table A1: Robustness Analysis

Without9 Obs. 8 Obs. 7 Obs. 6 Obs. D70-00

1-9 2-10 1-8 2-9 3-10 1-7 2-8 3-9 4-10 1-6 2-7 3-8 4-9 1-4 4-1050-95 60-00 50-90 55-95 60-00 50-85 55-90 60-95 65-00 50-80 55-85 60-90 65-95 50-70 70-00

INTi,t a 0.278 0.273 0.274 0.274 0.210 0.307 0.268 0.207 0.220 0.319 0.305 0.190 0.217 0.426 0.256

Control variablesb

ln yi,t1 rob rob rob rob 10% rob rob 10% frag rob rob 10% 10% rob fragi,t rob rob rob rob rob rob rob rob rob rob rob rob rob rob robOPENi,t rob rob rob rob rob rob rob rob rob rob rob rob rob rob rob

a Coefficient of INTi,t (no control variables added); significant at the 1 per cent level in all cases. b Results forrespective period, when control variables are added: rob ... robust, i.e. remains significant at the 1 per cent levelafter including the respective variable; frag ... fragile, i.e. rendered insignificant by the inclusion of the respectivevariable.

Table A2: Estimates of Investment-Led Growth Effects for EU Member States,19502000

Dependent variable: ln ki,t(a) (b)

Intercept 5.006 23.509D70-00 3.399 1.227INTi,t 0.510 0.472

(6.90) (7.67)ln ki,t1 1.830

( 4.48)

F-tests for parameter homogeneityIntercept 2.60 1.74D70-00 1.65 1.00INTi,t 0.23 0.21

Regression statisticsSEE 1.482 1.373R2 0.673 0.722Adj. R2 0.590 0.649Period 19502000 (T = 1, ..., 10)

See note of Table 3. Column (b): check for robustness against including the initial level ofcapital per worker.


References

Arellano, M., and S. Bond (1991). Some Tests of Specification for Panel Data:Monte Carlo Evidence and an Application to Employment Equations. Reviewof Economic Studies 58 (2): 277297.

Arellano, M., and S. Bond (1998). Dynamic Panel Data Estimation Using DPD98for GAUSS: A Guide for Users. Mimeo. Institute for Fiscal Studies, London.

Badinger, H., and F. Breuss (2004). What Has Determined the Rapid Post-WarGrowth of Intra-EU Trade? Review of World Economics/WeltwirtschaftlichesArchiv 140 (1): 3151.

Balassa, B. (1961). The Theory of Economic Integration. London: Allen & Unwin.

Baldwin, R. (1989). Growth Effects of 1992. Economic Policy 9: 247282.

Baldwin, R. E. (1993). On the Measurement of Dynamic Effects of Integration.Empirica 20 (2): 129144.

Baldwin, R. E., and E. Seghezza (1996). Growth and European Integration. To-wards an Empirical Assessment. CEPR Discussion Paper 1393. Centre for Eco-nomic Policy Research, London.

Barro, R. J., and J. W. Lee (2000). International Data on Educational At-tainment: Updates and Implications. Working Paper 42. Center for In-ternational Development at Harvard University. Dataset available at:http://www2.cid.harvard.edu/ciddata/

Ben-David, D. (1993). Equalizing Exchange: Trade Liberalization and IncomeConvergence. Quarterly Journal of Economics 108 (3): 653679.

Ben-David, D. (2001). Trade Liberalization and Income Convergence: A Com-ment. Journal of International Economics 55 (1): 229234.

Benhabib, J., and M. Spiegel (1994). The Role of Human Capital in Economic De-velopment: Evidence from Aggregate Cross-Country Data. Journal of MonetaryEconomics 34 (2): 143173.

Bond, S., A. Hoeffler, and J. Temple (2001). GMM Estimation of EmpiricalGrowth Models. CEPR Discussion Paper 3048. Centre for Economic Policy Re-search, London.

Breusch, T. (1978). Testing for Autocorrelation in Dynamic Linear Models. Aus-tralian Economic Papers 17 (31): 334355.

Breuss, F. (1983). sterreichs Auenwirtschaft 19451982. Vienna: Signum.

Coe, D. T., and E. Helpman (1995). International R&D Spillovers. European Eco-nomic Review 39 (5): 859887.

De la Fuente, A., and R. Domnech (2000). Human Capital in Growth Regres-sions: How Much Difference Does Data Quality Make? CEPR Discussion Paper2466. Centre for Economic Policy Research, London. Dataset available from:http://fuster.iei.uv.es/rdomenec

El-Agraa, A. M. (2001). The European Union, Economics & Policies. London: Pren-tice Hall.


Frankel, J. A., and D. Romer (1999). Does Trade Cause Growth? American Eco-nomic Review 89 (3): 379399.

GATT (1994). The Results of the Uruguay Round of Multilateral Trade Negotiations:Market Access for Goods and Services, Overview of the Results. Geneva: GATT.

Godfrey, L. (1978). Testing Against General Autoregressive and Moving Aver-age Error Models When the Regressors Include Lagged Dependent Variables.Econometrica 46 (6): 12931302.

Greenaway, D., W. Morgan, and P. Wright (1998). Trade Reform, Adjustment andGrowth: What Does the Evidence Tell Us. Economic Journal 108: 15471561.

Grossman, G. M., and E. Helpman (1997). Innovation and Growth in the GlobalEconomy. Second edition. Cambridge, Mass.: MIT Press.

Henrekson, M., J. Torstensson, and R. Torstensson (1997). Growth Effects of Eu-ropean Integration. European Economic Review 41 (8): 15371557.

Jones, C. I. (1995). Time Series Tests of Endogenous Growth Models. QuarterlyJournal of Economics 110 (2): 495525.

Landau, D. (1995). The Contribution of the European Common Market to theGrowth of Its Member Countries: An Empirical Test. Review of World Eco-nomics/Weltwirtschaftliches Archiv 131 (4): 774782.

Lewer, J. J., and H. Van den Berg (2003). How Large Is International Trades Effecton Economic Growth. Journal of Economic Surveys 17 (3): 363396.

Levine, R., and D. Renelt (1992). A Sensitivity Analysis of Cross Country GrowthRegressions. American Economic Review 82 (4): 942961.

Maddison, A. (1995). Monitoring the World Economy 18201992. Paris: OECD.

Nickell, S. (1981). Biases in Dynamic Models with Fixed Effects. Econometrica 49:14171426.

Nuxoll, D. A. (1994). Differences in Relative Prices and International Differencesin Growth Rates. American Economic Review 84 (5): 14231436.

Rivera-Batiz, L. A., and P. M. Romer (1991). Economic Integration and Endoge-nous Growth. Quarterly Journal of Economics 106 (2): 531555.

Rodriguez, F., and D. Rodrik (2001). Trade Policy and Economic Growth: A Scep-tics Guide to the Cross-National Evidence. In G. Bernanke and K. S. Rogoff(eds.). NBER Macroeconomics Annual 2000. Cambridge, Mass.: MIT Press.

Romer, P. M. (1990). Endogenous Technological Change. Journal of Political Econ-omy 98 (5): 71102.

Sapir, A., et al. (2004). An Agenda for a Growing Europe. The Sapir Report. Oxford:Oxford University Press.

Slaughter, M. (2001). Trade Liberalization and Per Capita Income Convergence:A Difference-in-Differences Analysis. Journal of International Economics 55 (1):203228.

Smith, A. (1789). An Inquiry into the Nature and Causes of the Wealth of Na-tions. Edited by Edwin Cannan (1904). London: Methuen. Available fromhttp://www.econlib.org/library/Smith/smWN1.html


Smith, A., and A. J. Venables (1988). Completing the Internal Market in the Eu-ropean Community: Some Industry Simulations. European Economic Review32 (7): 15011525.

Temple, J. (1999). The New Growth Evidence. Journal of Economic Literature37 (1): 112156.

Temple, J. (2003). The Long-Run Implications of Growth Theories. Journal of Eco-nomic Surveys 17 (3): 497510.

Vanhoudt, P. (1999). Did the European Unification Induce Economic Growth?In Search of Scale Effects and Persistent Changes. Review of World Eco-nomics/Weltwirtschaftliches Archiv 135 (2): 193220.

Waczairg, R. (2001). Measuring the Dynamic Gains from Trade. World Bank Eco-nomic Review 15 (3): 393429.

WTO (1995). Trading into the Future. Geneva.Young, A. (1998). Growth without Scale Effects. Journal of Political Economy

106 (1): 4163.

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