Regional Integration and Economic Growth...THE WORLD BANK ECONOMIC REVIEW, VOL. 12, NO. 2: 251-70...

THE WORLD BANK ECONOMIC REVIEW, VOL. 12, NO. 2: 251-70

Regional Integration and Economic Growth

Athanasios Vamvakidis

The rapid economic growth of developing countries that opened their markets to freeinternational trade during the past two decades has stimulated a large empirical andtheoretical literature on the impact of trade on growth. This literature concludes thatfree trade and growth were positively correlated during the 1970s and 1980s. How-ever, most studies focus on nondiscriminatory openness. Does regional integrationmatter for economic growth? Do regional trade agreements have any impact on growth?

This article presents empirical evidence that countries with open, large, and more de-veloped neighboring economies grow faster than those with closed, smaller, and less de-veloped neighboring economies. The results are robust to different specifications of theempirical model and different definitions of openness, suggesting that small economiesshould grow faster when they form regional trade agreements with large and more devel-oped economies. However, testing for the impact of five regional trade agreements duringthe 1970s and 1980s finds that none led to faster growth. The main reason seems to bethat most of these agreements were among small, closed, and developing economies.

The rapid economic growth of developing countries that opened their marketsto free international trade during the past two decades has stimulated a largeempirical and theoretical literature on the impact of trade on growth. This lit-erature concludes that free trade and growth were positively correlated duringthe 1970s and 1980s (Dollar 1992, Edwards 1992, Levine and Renelt 1992,Ben-David 1993, Barro and Sala-I-Martin 1995, Sachs and Warner 1995, andVamvakidis 1996, 1997). This result is robust to different proxies for opennessand the specification of the empirical model. However, most studies focus onnondiscriminatory openness. Does regional integration matter for economicgrowth? Do regional trade agreements (RTAs) have any impact on growth? Thesequestions remain unanswered. Their importance has become apparent recently,as many developing countries try to determine an appropriate liberalization strat-egy. Should they open their markets to countries from the same region beforethey open to the rest of the world? Or should they move directly toward nondis-criminatory liberalization?

Athanasios Vamvakidis is with the Research Department at the International Monetary Fund. Theauthor is grateful to Donald Davis, Ashish Garg, Robert E. Lucas, Maurice Schiff, David Weinstein,Jeffrey Williamson, and Alan Winters for their helpful comments. He would also like to thank theparticipants in the seminar series of the International Trade Division at the World Bank and threeanonymous referees. This article was produced as part of the World Bank Development EconomicsResearch Group's research program on regionalism and development. It is based on the author's researchon regional integration for the World Bank and on his doctoral thesis at Harvard University.

© 1998 The International Bank for Reconstruction and Development/THE WORLD BANX

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252 THE WORLD BANK ECONOMIC REVIEW, VOL. 12, NO. 2

The literature approximates openness by using trade figures or indexes ofdomestic trade policy. This methodology considers domestic trade policies butignores trade policies in the rest of the world. However, openness depends onboth domestic and foreign trade policies. As shown by Vamvakidis (1996,1997),the benefits from domestic openness are a positive function of openness in therest of the world. This result has important implications for regional integrationand RTAs.

This article considers three questions. First, how do the trade policies of coun-tries from the same region affect economic growth in the home country? Second,does a country benefit from positive spillover effects if it is in the same region aslarge, open, and developed economies? Third, have member countries of RTAsbenefited from such spillovers, growing faster? I investigate the first and secondquestions without considering RTAs. If a country does benefit from being nearopen economies and if the size and development of these economies matter forgrowth, I examine whether RTAs, by increasing the openness of countries fromthe same region, increase these benefits. Even economies that are characterizedas open have trade barriers; therefore, an RTA increases their openness towardmember countries.

All data in this article are from the Summers-Heston (1991) and Barro-Lee(1994) data sets. I include all countries with available data in each regression. Asa result, the number of countries changes depending on the independent vari-ables included in each regression. However, the results remain the same if theregressions include only countries with data for all independent variables.

Section I reviews the literature on international trade and growth. Section IIdiscusses data and methodology issues. Section ELI estimates the growth benefitsfor a country whose neighbors have large and open economies. Section IV esti-mates spillover effects from the level of development and the growth of neigh-boring economies. Section V tests the impact of five RTAs on growth. Section VIconcludes with some policy implications for developing countries.

I. PREVIOUS LITERATURE ON TRADE AND GROWTH

This section provides a brief review of the theoretical and empirical literatureon trade and growth.

Theoretical Studies

The recent literature on trade and growth tries to explain why free trade fos-ters growth. This contrasts with earlier literature that used infant industry argu-ments to support protection. An important part of the recent theoretical litera-ture started with Lucas (1988), who considers a world in which human capital isthe engine of growth and analyzes the effects of learning by doing. According tohis analysis, the initial conditions determine the comparative advantage of eachcountry and, thus, which products each country will produce under free trade.The model predicts that each country's comparative advantage increases through

Vamuakidts 253

learning by doing. This implies that some countries are locked in sectors withrelatively little learning by doing and diverge from the rest of the world. Thismodel provides a plausible explanation for the absence of convergence in cross-country data. However, it predicts that only countries with initial comparativeadvantage in sectors with significant learning by doing will benefit from freetrade.

More recent theoretical literature focuses on the channels through which freetrade leads to faster growth (Grossman and Helpman 1989,1990,1991; Rivera-Batiz and Romer 1991a, 1991b; Romer 1990; and Krugman 1990, ch. 11). Ac-cording to the new literature, trade increases innovation through economies ofscale, technological spillovers, and elimination of the replication of research anddevelopment (R&D) in different countries. In the Grossman and Helpman stud-ies, innovation of new products is a positive function of past innovations, whichrepresent the stock of knowledge. International trade provides access to a largeinternational market, to advanced technology, and, therefore, to a larger stockof knowledge, leading to more innovations and faster growth. This implies thata country benefits from free trade with large economies and an advanced stockof knowledge, assuming that technological spillovers are absorbed to the samedegree across countries. Indeed, Coe and Helpman (1997) provide empiricalevidence for these arguments, showing that a country's total factor productivitydepends not only on its own R&D capital stock but also on the R&D capitalstocks of its trade partners. Also, Coe, Helpman, and Hoffmaister (1997) findthat developing countries with limited R&D stock can boost productivity bytrading with a more developed country that has a large stock of knowledge fromits cumulative R&D activities. Finally, Vamvakidis (1996) presents evidence thatthe size of the domestic market is important for growth only for closed econo-mies, whereas a large international market fosters economic growth for openeconomies, as predicted by the theoretical models just mentioned.

The new literature suggests that a country that is more open to free trade willhave greater technological spillovers and, therefore, faster growth than a coun-try that is less open. However, the literature does not address the issue of re-gional integration. Should a country form or join an RTA or reduce trade barriersfor all countries? Free trade is beneficial for growth, but what kind of free trade—regional or nondiscriminatory? Given that theory has not answered these im-portant questions, empirical evidence on the impact of regional integration ongrowth may provide stylized facts and show the direction that future theoreticalwork should follow.

Empirical Studies

The empirical literature has established that free trade fostered economicgrowth in the 1970s and 1980s. However, this was not true in earlier decades.Vamvakidis (1997) estimates the impact of international trade on growth from1870 to 1990 and finds that free trade and growth are positively correlated onlyin the 1970s and 1980s. There is no correlation in any of the earlier decades in


the sample, except for a negative correlation in the 1930s. Because the data usedhere are from the 1970s and 1980s, the other studies discussed focus on thisperiod.

Dollar (1992) estimates a cross-country index of distortion in the real ex-change rate. He uses the index to determine if a country is outward or inwardoriented. Based on estimations for 95 developing countries, he concludes thatmore outward-oriented countries grow faster. The rigorous measure of exchangerate distortion and the focus on developing countries distinguish this study.

Edwards (1992) estimates the impact of international trade on growth usingnine indexes of openness proposed in the literature. All these openness measuresshow a positive correlation between openness and growth.

Levine and Renelt (1992) test the robustness of the determinants of growthsuggested by previous literature that performs sensitivity analysis. They find thatfree international trade indirectly affects growth through investment. Countriesthat have low trade barriers invest more and therefore grow faster. This result isrobust to different specifications and to different indexes of openness.

Ben-David (1993) shows that open economies converge and that the tradeagreements of the European Union have resulted in the convergence of its mem-bers. It is a known puzzle in the empirical literature on growth that economiesdo not experience the convergence that the neoclassical growth model predicts.In general, growth of the world economy agrees more with divergence than withconvergence. Ben-David's work shows that the only economies that convergeare those that are integrated in the world economy through trade.

Baldwin and Seghezza (1996) document the positive growth effects of theEuropean Union for the medium term. Henrekson, Torstensson, and Torstensson(1997) show that a dummy for participation in the European Union has a posi-tive coefficient in cross-country growth regressions, but its significance is notalways robust and depends on the specification of the empirical model. Theresults in this article confirm these findings.

Sachs and Warner (1995) also confirm these results. They construct a dummyvariable of openness based on five protection dimensions, including tariff andnontariff barriers, black market premia, and the role of the state in the economy.Using this index, they find that open economies grow on average 1.5 percentfaster than closed economies and that unconditional convergence is true only foropen economies. They also present evidence that economies liberalize only aftera serious economic crisis. Bruno and Easterly (1996) present similar evidence.Alesina and Drazen (1991) provide the theoretical foundation of this stylizedfact. Their model shows that an economic crisis can stop the war of attritionamong economic groups that delay liberalization in an effort to avoid its costs.

Barro and Sala-I-Martin (1995) find that protection has a negative impact ongrowth. Using tariffs on capital goods and intermediate inputs as a measure ofprotection, their results indicate that countries with high tariffs grow slowerthan those with low tariffs. Protection has no significant impact, however, whenthey use an index of nontariff barriers on capital goods and intermediate inputs.

Vamvakidis 255

Most of the literature on trade and growth does not examine the impact ofregional integration on growth. Ben-David (1993) is an exception, showing thattrade agreements in Europe have caused convergence. Vamvakidis (1996) showsthat the trade policies of countries in the same region matter for growth, a resultconfirmed here, and compares the importance of a large international marketfor the growth of open economies with the importance of a large domestic mar-ket for the growth of closed economies. The present article focuses on whetherthe openness, size, and level of gross domestic product (GDP) per capita affectgrowth for countries in the same region. It also analyzes whether RTAs reinforcethis impact.

II. DATA AND METHODOLOGY

Most RTAs in the 1970s and 1980s were among small developing economiesand do not provide enough variation to test the theoretical predictions in sectionI. In this and the following section, I address this issue by looking at the impactof trade policy, market size, and level of development of countries in the sameregion on the growth of the home country, regardless of any existing RTA. Doesit matter if a country is in the same region as open economies? Do the marketsize and the income level of neighboring economies foster economic growth inthe home country? Most of the theoretical models reviewed in section I suggestthat such spillovers should exist. For example, Grossman and Helpman (1991)suggest that a country with more advanced and bigger trading partners has greaterspillover effects from them. The trading partners of a country are not alwayswithin the same region, but often countries in the same region trade a lot withone another if their economies are open.

The model estimated here is similar to the models in Barro and Sala-I-Martin(1995), Sachs and Warner (1995), and Levine and Renelt (1992). The depen-dent variable is growth in average annual GDP per capita for 1970-90. The stan-dard independent variables are the log of GDP per capita in 1970, the averageshare of investment in physical capital over GDP in 1970-90, the secondary schoolenrollment in 1970, the average population growth in 1970-90, the averagegrowth rate of the terms of trade in 1970-90, and the infant mortality rate in1970. In this section, an economy is characterized as open if it has low tradebarriers toward all countries. Section IV considers the case of RTAs in which amember country may not be open to nonmember countries.

The analysis uses an openness dummy constructed by Sachs and Warner (1995),who define an economy as open if all of the following conditions are true: theaverage tariff rate is less than 40 percent, average nontariff barriers cover lessthan 40 percent of total trade, the black market premium is less than 20 percentof the official exchange rate, there is no communism, and there is no state mo-nopoly on major exports. I define a country as open based on the value of thisdummy in 1970, the first year of the period considered, to avoid potential prob-lems of reversed causality. The results do not change when the dummy takes the

Table 1. The Impact of the Size of Open Neighboring Economies on Growth, 1970-90

Variable

Constant

Log of GDP per capita, 1970

Open neighbors' market, 1970*

Closed neighbors' market, 1970*

Average annual share of investment inphysical capital over GDP, 1970-90

Secondary school enrollment, 1970

Average annual growth in the termsof trade, 1970-90

Infant mortality rate, 1970

Average annual population growth, 1970-90

Openness dummy, 1970

Share of years open, 1970-90

Average annual trade share, 1970-90b

Africa dummy

East Asia dummy

Number of observationsAdjusted R2

1

0.030(1.551)-0.002(-1.023)

0.155(3.508)

1200.10

2

0.155(5.809)-0.019

(-6.028)0.106

(2.238)

0.113(3.659)

0.007(0.528)0.164

(3.051)

-0.167(-3.440)-0.226

(-0.998)

900.50

3

0.149(5.706)-0.019

(-6.033)0.070

(1.802)

0.102(3.025)

0.004(0.259)0.161

(2.962)

-0.172(-3.350)-0.078

(-0.308)0.011

(1.842)

900.52

Regression

4

0.033(1.664)-0.003

(-1.061)0.132

(2.287)-0.025(-0.670)

1200.095

5

0.153(5.802)-0.019

(-6.063)0.130

(3.065)0.025

(1.067)0.113

(3.677)

0.006(0.426)0.165

(3.084)

-0.172(-3.625)-0.266

(-1.092)

900.50

6

0.146(5.670)-0.019

(-6.128)0.102

(2.537)0.036

(1.509)0.099

(3.019)

0.0013(0.087)0.162

(3.017)

-0.180(-3.664)-0.120(-0.456)

0.012(2.190)

900.52

7

0.153(5.324)-0.019

(-5.535)0.07

(2.650)0.034

(1.437)0.080

(2.287)

-0.004(-0.272)

0.179(3.249)

-0.154(-2.742)-0.020

(-0.076)

0.020(3.407)

-0.008(-1.872)-0.001

(-0.180)90

0.56

8

0.164(6.320)-0.020

(-5.317)0.07

(2.574)0.0002

(0.005)0.118

(3.358)

0.004(0.232)0.184

(2.799)

-0.164(-3.024)-0.222

(-0.762)

-0.021(-0.791)-0.005(-1.024)-0.0004(-0.049)

890.51

Note: The dependent variable is average annual growth in GDP per capita for 1970-90. Neighboring economies are listed in table A-1. Openness is based onSachs and Warner's (1995) openness dummy, (-statistics based on heteroscedastic-consistent standard errors are in parentheses.

a. The log of the sum of the GDP of all open or closed neighboring economies.b. (Exports + imports)/GDP.Source: Author's calculations.

Vamvakidis 257

value of 1 if a country is open for most years in the period 1970-90. In someregressions I use the share of the years a country has been open during 1970-90,and the results are also robust.

The proxy for the openness of countries from the same region is the opennessof neighboring countries. If the openness of neighboring countries matters forgrowth, then regional integration also matters if it leads to freer trade policies.For every country in the analysis, I consider the openness of countries with com-mon borders. The log of the sum of the GDP of all open neighboring economiesin 1970 measures the size of the open neighbors' market. I construct a similarvariable for neighboring economies with high protection, the closed neighbors'market. The estimates do not change if the GDP of the home country is alsoadded to the open neighbors' market, as I do in some regressions, or if popula-tion is used as the definition of country size. Actually, GDP and population varymore within regions than the openness dummy.

To test the robustness of the results, I use a continuous measure of opennessinstead of an openness dummy and estimate for each country the GDP-weightedaverage trade share [(exports + imports)/GDP] of the neighboring countries for1970-90. This variable measures how much the neighbors of each country trade;therefore it shows whether proximity to countries that trade a lot has an impacton growth. The advantage of this variable is that it varies much more withinregions than the openness dummy.

For reasons of simplicity and comparison, I use the list of neighboring econo-mies that Chua (1993) and Barro and Sala-I-Martin (1995) use in their estimatesof the effects of neighboring economies. Table A-l provides the list of neighbor-ing economies for each country in their sample.

III. THE IMPACT OF THE SIZE OF OPEN NEIGHBORING ECONOMIES ON GROWTH

Table 1 shows that the openness of neighboring economies has a positive andstatistically significant coefficient. Having neighbors with large open economiesfosters growth. The coefficient in regressions 7 and 8 means that an increase inthe log of GDP of open neighboring economies by one standard deviation (5.63)results in 0.39 percent faster annual growth.1 Adding the GDP of all open coun-tries in the same continent to obtain the open market size for each country yieldssimilar results. The estimated coefficient of the closed neighbors' market in table1 is by far smaller than the coefficient for open neighboring economies and notstatistically significant. This means that a country experiences significant posi-tive spillovers mainly from open neighboring economies. The results confirmthose of Sachs and Warner (1995): the openness dummy remains significant inall regressions. Keeping everything else constant, open economies grew on aver-age 1.5 percent faster annually than closed economies during the 1970s and1980s.

1. One standard deviation of the log of the market of open neighboring economies (5.63) times theestimated coefficient of this variable in regressions 7 and 8 (0.07).


Table 2. The Impact of Regional Market Size on Growth, 1970-90

Regression

Variable

Constant


Open neighbors' market plus GDP,

1970'Closed neighbors' market, 1970*





Average annual population growth,1970-90

Share of years open, 1970

Average annual trade share, 1970-90b

Average annual trade share ofneighbors, 1970-90b


Note: The dependent variable is average annual growth in GDP per capita for 1970-90. Regionalmarket size is measured by open neighbors' market plus GDP. Neighboring economies are listed in tableA-l. Openness is based on Sachs and Warner's (1995) openness dummy, f-statistics based onheteroscedastic-consistent standard errors are in parentheses.

a. The log of the sum of the GDP of all open neighboring economies plus the home country or of allclosed neighboring economies.

b. (Exports + imports)/GDP. For neighbors, the average is weighted by GDP.Source: Author's calculations.

The results show that countries can benefit from being near large, open econo-

mies. In contrast, the market size of closed neighboring economies matters much

less for growth. This implies that keeping everything else constant, most coun-

tries in Europe, North and Central America, and East Asia grew faster than

those in Sub-Saharan Africa, which consists mainly of small and highly pro-

tected economies. Sachs and Warner (1996) make a similar point about the coun-

tries in Sub-Saharan Africa.

Regression 6 in table 1 shows that, controlling for home-country openness,

the coefficient of the open neighbors' market drops but is still significant. This

indicates that the coefficient of open neighbors' market partly captures the effect

1

0.133(4.564)-0.020(-6.801)

0.26(2.307)

0.086(2.472)0.006

(0.437)0.171

(2.907)-0.166(-2.868)

0.087(0.305)0.018

(2.744)

900.58

2

0.139(4.732)-0.020(-5.333)

0.25(2.407)

0.123(3.819)0.014

(1.060)0.169

(2.441)-0.161(-2.960)-0.160(-0.600)

-0.013(-0.581)

890.52

3

0.131(4.486)-0.020(-6.686)

0.267(2.356)0.015(0.776)0.086

(2.467)0.005

(0.399)0.171

(2.902)-0.168(-2.902)

0.064(0.214)0.019

(3.097)

900.57

4

0.144(5.040)-0.022(-5.386)

0.234(2.267)-0.023(-0.720)

0.122(3.667)0.014

(1.008)0.172

(2.478)-0.162(-2.955)-0.103(-0.333)

-0.015(-0.633)

890.52

5

0.176(5.451)-0.019(-4.628)

0.151(4.036)-0.011

(-0.635)0.197

(2.872)-0.291(-4.291)-0.290(-0.993)

-0.043(-1.584)

0.032(1.646)660.55

Vamvakidis 259

of home-country openness. In other words, most open economies have openneighboring economies.

Regression 7 tests the robustness of the results obtained by adding two dummyvariables for Africa and East Asia and using the share of years a country wasopen during 1970-90 instead of the openness dummy. Regression 8 uses thetrade share as the definition of openness instead. The results remain robust tothese changes. The dummy variables for Africa and East Asia are not significant,which suggests that the other independent variables in the regression alreadyexplain the differences in these countries' growth compared with other areas ofthe world economy. Also, the trade share is not statistically significant, a resultconsistent with Levine and Renelt (1992).

Table 2 presents some tests of robustness, including a variable that adds thehome country's GDP to the open neighbors' market. This variable measures theavailable market for a country in its region, which is its own market plus themarket of its open neighbors. If regional market size matters, domestic marketsize should also matter and should be considered. This variable has the advan-

Table 3. The Impact of All Neighboring Economies on Growth, 1970-90

Variable

Constant


Neighbors' GDP, 1970

Neighbors' population, 1970

Open neighbors' population,1970

Average annual share ofinvestment in physicalcapital over GDP, 1970-90

Secondary school enrollment,1970

Average annual growth in theterms of trade, 1970-90


Average annual populationgrowth, 1970-90



1

-0.054(-2.811)

0.0006(0.316)0.350

(2.777)

1180.06

2

0.113(3.425)-0.018(-5.271)

0.157(1.696)

0.102(2.854)

0.007(0.492)0.161

(2.701)-0.153(-2.645)-0.051

(-0.191)0.015

(2.067)90

0.52

Regression

3

-0.026(-1.741)

0.003(2.039)

0.145(1.776)

1200.02

4

0.136(4.172)-0.017(-5.061)

0.0004(0.417)

0.107(2.894)

0.006(0.374)0.158

(2.622)-0.163(-2.761)-0.105

(-0.379)0.015

(2.116)90

0.51

5

0.035(1.924)-0.004(-1.487)

0.218(3.985)

1200.15

6

0.148(5.333)-0.018(-5.661)

0.090(1.761)0.103

(2.911)

0.003(0.206)0.154

(2.724)-0.168

(-3.070)-0.098

(-0.369)0.010

(1.556)90

0.52

Note: The dependent variable is average annual growth in GDP per capita for 1970-90. Neighboringeconomies are listed in table A-l. Openness is based on Sachs and Warner's (1995) openness dummy,t-statistics based on heteroscedasric-consistent standard errors are in parentheses.

Source: Author's calculations.

Table 4. Spillover Effects from the Economic Development of Neighboring Economies, 1970-90

o

Variable

Constant


Neighbors' GDP per capita, 1970"

Neighbors' average annual growth inGDP per capita, 1970-90*





Average annual population growth,1970-90



1

-0.030(-2.507)-0.002

(-0.696)0.787

(2.746)

1170.08

2

0.113(3.957)-0.022(-5.841)

0.757(3.730)

0.111(4.090)0.026

(1.877)0.153

(3.055)-0.143(-2.984)-0.037(-0.178)

900.52

3

0.113(4.217)-0.022

(-6.129)0.683

(3.582)

0.092(2.954)0.018

(1.180)0.153

(3.012)-0.156

(-3.090)0.164

(0.692)0.012

(1.963)900.55

Regression4

-0.012(-0.903)

0.003(2.113)

-0.027(-0.672)

1150.008

5

0.142(4.762)-0.018(-5.045)

0.051(1.777)0.140

(4.207)0.014

(1.020)0.135

(2.484)-0.161(-3.048)-0.330(-1.547)

870.49

6

0.137(4.954)-0.017(-5.470)

0.026(1.007)0.115

(3.150)0.006

(0.382)0.129

(2.361)-0.169(-3.014)-0.032(-0.117)

0.016(2.172)

870.52

7

0.110(4.047)-0.021(-6.054)

0.643(3.453)0.018

(0.625)0.099

(3.008)0.017

(1.069)0.127

(2.555)-0.159(-3.055)

0.218(0.857)0.015

(1.964)870.56

Note: The dependent variable is average annual growth in GDP per capita for 1970-90. Neighboring economies are listed in table A-l. Openness is based onSachs and Warner's (1995) openness dummy, r-statistics based on heteroscedastic-consistent standard errors are in parentheses,

a. The sum of the GDP for all neighboring economies divided by the sum of their population.Source: Author's calculations.

Vamvakidis 261

tage of capturing more variation within regions than the open neighbors' mar-ket variable. As regressions 1-4 show, the coefficient of the regional marketmeasure is positive, statistically significant, and robust to different specifica-tions of the empirical model. These regressions do not include the Africa andEast Asia dummies because they are not statistically significant and do not changethe results. The regressions include the share of years a country was open during1970-90; an openness dummy gives similar results.

Regression 5 in table 2 uses a different definition for the openness of theneighboring countries—their GDP-weighted average trade share. The advantageof this variable is that it is continuous and varies a lot within and across regions.The estimated coefficient is positive and statistically significant at the 10 percentlevel. The estimate means that an increase in the average trade share of the neigh-boring countries by one standard deviation (9.6 percent) will result in 3.2 per-cent faster growth. Therefore, other things being equal, countries with neigh-bors that trade a lot grew faster during the period considered.

Table 3 presents regressions that do not separate open from closed economiesand that, for the most part, use population as the measure of the neighbors'market size. Neighbors' GDP and population vary more within and across re-gions than the open neighbors' market variable. The first two regressions showthat countries with neighbors that have high GDP grow faster. However, whenpopulation is used as the measure of neighboring countries' size, without sepa-rating open from closed neighboring economies, the impact is not always signifi-cant. In contrast, when the regression includes only the population of open neigh-boring economies, the coefficient is positive and statistically significant. The resultsdo not change in regressions using other definitions of openness from the previ-ous tables or dummies for Africa and East Asia. Based on regression 6, an in-crease in the log of the open neighbors' population by one standard deviation(4.9) will result in 0.41 percent faster growth.

To summarize, countries with large and open neighbors grow faster, a resultthat is robust to different model specifications and measures of openness and issignificant in both the statistical and economic meaning of the word.

IV. SPILLOVER EFFECTS FROM THE ECONOMIC DEVELOPMENT

OF NEIGHBORING ECONOMIES

Section III focused on the market size of neighboring economies. This sectionestimates the impact that the stage of development and the growth of the neigh-boring economies have on domestic growth. It looks at the impact of all neigh-boring economies and also distinguishes between open and closed ones.

Table 4 presents estimates of the impact of the level and growth of the popu-lation-weighted average per capita GDP in neighboring economies on growth ofper capita GDP in the home country. (The results do not change if the estimationuses GDP-weighted averages instead.) The results show that countries benefitfrom having neighbors with more developed economies. The average per capita

2 6 2 THE WORLD BANK ECONOMIC REVIEW, VOL. 12, NO 2

GDP of neighboring economies has a positive and statistically significant coeffi-cient. By contrast, the estimated coefficient of the growth rate of neighboringeconomies is not statistically significant. Therefore, being near developed coun-tries results in positive spillovers, but being near fast-growing countries doesnot. Barro and Sala-I-Martin (1995) also find positive spillovers from high GDPper capita in neighboring economies. The present article shows that these spillovereffects essentially come from open neighboring economies.

Table 5 presents estimates of the impact of the average GDP per capita of openand closed neighboring economies. The results show that the population-weightedGDP per capita of open neighboring economies has a positive and statisticallysignificant impact on domestic growth. The effect of closed neighboring econo-mies is not significant except at the 10 percent level in regression 2. Regressions3-6 include Africa and East Asia dummies, which do not have a robust impact.Regression 4 uses the share of trade as openness, and regression 5 uses the shareof years a country was open during 1970-90. The results are robust for thesealternative specifications. Based on regression 3, an increase in the log of aver-age GDP per capita in open neighboring economies by one standard deviation(3.86) results in 0.66 percent faster growth in the home country. Therefore, thespillover effects from the level of development of neighboring economies areimportant mainly if these economies are open.

Regression 6 in table 5 includes the variable of open neighbors' market plus thehome country's GDP. This coefficient is positive and significant as in specificationsin table 2, but in this case the average GDP per capita of open neighboring econo-mies becomes insignificant. This result may imply that the market size of the neigh-boring economies is more important than their level of GDP per capita for home-country growth. However, given that the two variables are correlated, thisinterpretation should be approached with caution. If the regression includes theopen neighbors' market variable without adding the home country's GDP, the twovariables—open neighbors' market and average GDP per capita of neighboringeconomies—become insignificant, simply because they are highly correlated.

V. REGIONAL TRADE AGREEMENTS AND GROWTH

Most RTAs created during the 1960s and 1970s were South-South agreementsand were part of the import substitution policies that member countries werefollowing. As a result, they diverted trade from more efficient external sourcesof production. The member countries were typically small, highly protected,and similar in their economic endowments.

To test the impact of RTAs on economic growth, I consider agreements thatstarted during the 1970s or earlier and continued for most of the following twodecades and for which data are available for most member countries (for moreinformation, see United Nations Conference on Trade and Development 1994).Table A-2 defines these RTAs: Association of South East Asian Nations (ASEAN),Andean Common Market (ANCON), Central American Common Market (CACM),

Vamvakidis 263

Table 5. Spillover Effects from the Economic Development of Openand Closed Neighboring Economies, 1970-90

RegressionVariable

Constant

Log of GDP per capita,1970

Open neighbors' GDPper capita, 1970*

Closed neighbors' GDPper capita, 1970*

Open neighbors' marketplus GDP, 1970b


Secondary schoolenrollment, 1970

Average annual growth

1

0.038(2.049)-0.004(-1.590)

0.279(4.155)

in the terms of trade, 1970-90Infant mortality rate, 1970



Share of years open, 1970-90

Average annual trade share,1970-90*

Africa dummy

East Asia dummy


1180.14

2

0.145(5.357)-0.019(-5.912)

0.18(2.411)0.12

(1.666)

0.103(3.051)

0.004(0.253)0.147

(2.630)-0.178(-3.434)-0.062(-0.229)

0.011(1.893)

900.53

3

0.151(5.033)-0.020(-5.260)

0.17(2.491)0.09

(1.343)

0.100(2.770)

0.003(0.174)0.151

(2.610)-0.153(-2.735)

0.015(0.054)0.013

(2.188)

-0.007(-1.533)-0.00 1(0.177)

900.53

4

0.163(6.341)-0.020(-5.773)

0.21(3.054)0.069

(0.894)

0.125(3.776)

0.007(0.441)0.173

(2.667)-0.175(-3.160)-0.135(-0.537)

-0.025(-1.087)-0.004(-0.826)-0.002(-0.287)

890.52

5

0.150(5.085)-0.020(-5.412)

0.15(2.118)0.091

(1.387)

0.087(2.508)

0.001(0.086)0.165

(2.867)-0.152(-2.703)

0.059(0.235)

0.019(3.055)

-0.008(-1.723)-0.001(-0.159)

900.55

6

0.146(5.001)-O.023

(-6.899)0.090

(1.073)0.099

(1.297)0.25

(1.940)0.087

(2.585)

0.005(0.331)0.173

(2.902)-0.165

(-2.887)0.147

(0.527)

0.020(3.064)

-0.006(-1.267)-0.006

(-1.022)900.58

Note: The dependent variable is average annual growth in GDP per capita for 1970-90. Neighboringeconomies are listed in table A-l. Openness is based on Sachs and Warner's (1995) openness dummy,(-statistics based on heteroscedastic-consistent standard errors are in parentheses.

a. The sum of the GDP for all neighboring economies divided by the sum of their population.b. The log of the sum of the GDP of all open neighboring economies plus the home country.c. (Exports + imports)/GDP.Source: Author's calculations.

European Union, and Union Douaniere et Economique de PAfrique Centrale(UDEAC). On the right side of the growth regression, dummy variables are in-cluded for countries that were members of any of the five RTAs.

Table 6 presents the results. In the first regression, only the estimated coeffi-cient for the European Union is positive and statistically significant at the 10percent level, while all other RTAs have no impact on growth. However, control-


Table 6. The Impact of Regional Trade Agreements on Growth, 1970-90

Variable

Constant



Dummy for membership in RTA'ASEAN

ANCON

CACM

European Union

UDEAC


Secondary schoolenrollment, 1970

Average annual growth inthe terms of trade, 1970-90


Open neighbors' market,1970b

Open neighbors' GDP percapita, 1970*



1

0.089(4.758)-0.015(-5.199)

1

0.754E-2(0.614)-0.264E-2(-0.455)-0.114E-2(-0.190)

0.598E-2(1.70)0.057E-2

(0.081)0.155(5.394)

0.034(2.605)

-0.134(-0.553)

990.43

2

0.092(5.459)-0.015(-5.929)

0.018(3.039)

0.203E-2(0.351)0.044E-2

(0.075)-0.27E-4(-O.004)-0.048E-2(-0.144)-0.90E-4

(-0.012)0.143

(5.293)

0.024(1.930)

-0.013(-0.051)

990.48

Regression

3

0.143(4.99)-0.017(-5.111)

0.016(2.261)

-O.261E-2(-0.684)-0.278E-2

(-0.520)-0.141E-2(-0.262)-0.183(-0.673)-0.861E-2

(-1.104)0.100

(2.840)

0.320(0.219)0.184

(2.860)-0.177(-3.036)

-0.089(-0.335)

900.49

4

0.154(5.761)-0.019(-5.789)

0.013(2.031)

-0.442E-2(-0.673)-0.087E-2(-0.162)-0.031E-2(-0.058)-0.387E-2(-1.259)-0.864E-2(-1.099)

0.092(2.674)

-0.55E-3(-0.037)

0.192(3.078)-0.186(-3.429)

0.078E-2(1.949)

-0.082(-0.314)

900.50

5

0.157(6.024)-0.019(-5.970)

0.013(2.143)

-O.598E-2(-0.838)

0.023E-2(0.044)0.345E-3

(0.064)-0.382E-2(-1.306)-0.835E-2

(-1.042)0.091

(2.660)

-0.004(-0.255)

0.191(3.099)-0.185(-3.485)

0.115E-2(2.485)-0.156(-0.617)

900.51

Note: The dependent variable is average annual growth in GDP per capita for 1970-90. Neighboringeconomies are listed in table A-l. Openness is based on Sachs and Warner's (1995) openness dummy,f-statistics based on heteroscedastic-consistent standard errors are in parentheses.

a. Table A-2 provides the full name, country members, and date of formation for each of the fiveregional trade agreements (RTAS).

b. The log of the sum of the GDP of all open neighboring economies.c. The sum of the GDP for all neighboring economies divided by the sum of their population.Source: Author's calculations.

ling for openness and other independent variables, even the European Uniondummy becomes insignificant. Although the estimated coefficients of all regionalagreements' dummies are negative in most specifications, none is significant.These results indicate that these RTAs did not affect growth significantly.

Although past RTAs did not result in faster growth, this does not necessarilyimply that the RTAs formed during the 1990s will have no impact on growth.

Vamvakidis 265

Some of the recent trade agreements are considered as part of a broader liberal-ization—especially in the case of North-South RTAS—and include open, large,and more developed economies. The results of section IV show that a countrywith such neighboring economies will experience positive spillovers. Thus, eventhough RTAS did not help member countries experience these benefits in previ-ous decades, some of the recent RTAS may have an important impact on growth.

VI. CONCLUDING REMARKS AND POLICY IMPLICATIONS

This article has examined whether the openness, market size, and level ofdevelopment of countries in the same region foster growth in the home country.The results show that the economies of countries near large and open economiesgrow faster. Also, the level of development of neighboring economies, especiallywhen they are open, has significant positive spillover effects. By contrast, thesize and level of development of closed neighboring economies have little or noimpact on domestic growth. These results suggest that trade agreements betweendeveloping countries and large and more developed countries may lead to fastergrowth. Given that no country has zero trade barriers, if an RTA increases theopenness of the large and more developed economies toward less developedmember countries, it will promote their growth.

This article has found that RTAs had no impact on growth in the past. Themost appealing theoretical reason is that these agreements were among small,developing, and very similar economies. Most of the time, the countries designedRTAs to divert trade, as a part of import substitution trade policies. However,this interpretation does not explain the empirical results for the European Union.

It is possible that countries have designed recent RTAS as part of a broaderliberalization and that these agreements, especially North-South RTAS, will af-fect growth. This article has shown that countries with open, large, and moredeveloped neighboring economies do experience positive spillovers.

(Table A-l begins on the following page.)

2 6 6 THE WORLD BANK ECONOMIC REVIEW, VOL. 12, NO. 2

Table A-l. Neighboring EconomiesCountry code and country

1 Algeria2 Angola3 Benin4 Botswana5 Burkino Faso

6 Burundi7 Cameroon8 Cape Verde9 Central African Republic

10 Chad

11 Comoros12 Congo13 Egypt14 Ethiopia15 Gabon

16 The Gambia17 Ghana18 Guinea19 Guinea Bissau20 Cote d'lvoire

21 Kenya22 Lesotho23 Liberia24 Madagascar25 Malawi

26 Mali27 Mauritania28 Mauritius29 Morocco30 Mozambique

31 Niger32 Nigeria33 Rwanda34 Senegal35 Seychelles

36 Sierra Leone37 Somalia38 South Africa39 Sudan40 Swaziland

41 Tanzania42 Togo43 Tunisia44 Uganda45 Zaire

46 Zambia47 Zimbabwe

2945323826

4132344539

45393912

3442261823

4438182830

272624

125

3276

2721

18144

1438

2117

121

2

4530

2646424731

33102710

9

158937

7

20363417

14

363046

134

47

1031451637

2321221030

303

4512

24

Codes

43125

20

459

163931

7

21

520

18

41

20

41

51

41

13

412641

3013

255

3946

2546

of neighboring economies

31

31

17

1219

77

9

23

5

37

18

38

26104418

409

6

419

4738

27

3

15

1232

2

34

26

39

31

46

5

19

4745

44

3344

30

42

19

20

40

3

21

46

39

41

34

44

33

6 33

Vamvakidis 267

Table A-l. (continued)Country code and country Codes of neighboring economies

48 Bahamas49 Barbados50 Canada

51 Costa Rica52 Dominica53 Dominican Republic54 El Salvador55 Grenada

56 Guatemala57 Haiti58 Honduras59 Jamaica60 Mexico

61 Nicaragua62 Panama63 St. Lucia64 St. Vincent65 Trinidad and Tobago

66 United States67 Argentina68 Bolivia69 Brazil70 Chile

71 Colombia72 Ecuador73 Guyana74 Paraguay75 Peru

76 Suriname77 Uruguay78 Venezuela79 Afghanistan80 Bahrain

81 Bangladesh •82 Myanmar83 China84 Hong Kong85 India

86 Indonesia87 Iran88 Iraq89 Israel90 Japan

91 Jordan92 Korea, Rep. of93 Kuwait

666566

6278575678

6053615766

5851787849

5070696867

7575696771

7369699799

82104

858381

9488879192

999088

58

58

54

56

5171

78

6074757868

7871786969

69677187

0

858584

10383

13497

102102

83

102

99

54

56

69707175

69

766872

73

8182

97

1289913

89

686775

72

68

83

95

79128

88

777474

62

70

82

93

67 77 76

91

(Table continues on the following page.)


Table A-l. (continued)Country code and country

94 Malaysia95 Nepal

96 Oman97 Pakistan98 Philippines99 Saudi Arabia100 Singapore

101 Sri Lanka102 Syria103 Taiwan104 Thailand105 United Arab Emirates

106 Yemen, Arab Republic107 Austria108 Belgium109 Cyprus110 Denmark

111 Finland112 France113 Germany114 Greece115 Hungary

116 Iceland117 Ireland118 Italy119 Luxembourg120 Malta

121 Netherlands122 Norway123 Poland124 Portugal125 Spain

126 Sweden127 Switzerland128 Turkey129 United Kingdom130 Yugoslavia

131 Australia132 Fiji133 New Zealand134 Papua New Guinea135 Solomon Islands

136 Tonga137 Vanuatu138 Western Samoa

8685

998586

10694

85128

849499

99113112128113

122125107128130

122129127108118

113126

125124

122118102117114

133134131

86134

131131131

10483

10587

91

88838296

96118121102

126108121130107

129

112113114

108111

112

11111287

118

86131132

133

133

Codes

100

10683

96

91

127113

127112

107112

11388

134133

of neighboring economies

79

105

89

115119

118127

130

107114

88

113108

93

119119 110

Vamvakidis 269

Table A-2. Regional Trade AgreementsAgreement Year created Member countries

Andean Common Market, ANCOM 1 1969 Bolivia, Colombia, Ecuador, Peru, VenezuelaAssociation of South East Asian 1967 Indonesia, Malaysia, Philippines, Singapore,

Nations, ASEAN ThailandCentral American Common Market 1960 Costa Rica, El Salvador, Guatemala, Honduras,

CACMb NicaraguaEuropean Union c 1958 Belgium, Denmark, France, Germany, Greece,

Ireland, Italy, Luxembourg, Netherlands,Portugal, Spain, United Kingdom

Union Douaniere et Economique 1966 Cameroon, Central African Republic, Chad,de l'Afrique Centrale, UDEAC Congo, Gabon

a. Venezuela joined ANCOM in 1973.b. Costa Rica joined CACM in 1962.c. Denmark, Ireland, and United Kingdom joined the European Union in 1973.Source: UNCTAD (1994).

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