institutional quality and trade: which institutions? which trade?

INSTITUTIONAL QUALITY AND TRADE: WHICH INSTITUTIONS?WHICH TRADE?

PIERRE-GUILLAUME MEON and KHALID SEKKAT*

Using a panel of countries over 1990–2000, this paper examines the extent to whichdifferent dimensions of the institutional framework affect total exports, exports ofmanufactured goods, and exports of nonmanufactured goods. It is observed thatexports of manufactured goods are positively affected by the quality ofinstitutions but neither total exports nor nonmanufactured exports. The latter mayeven correlate negatively with the quality of institutions. The results are robust toestimation methods. (JEL F14, F15, O17)

I. INTRODUCTION

The contention that ‘‘institutions rule,’’ asRodrick, Subramanian, and Trebbi (2004) putit, has become a core belief among both schol-ars and practitioners of economic develop-ment. This consensus results from a widebody of evidence suggesting that a country’soverall economic performance is affected byits institutional framework.1 It has beenobserved that ailing institutions are associatedwith slower growth, for instance by Mauro(1995) or Knack and Keefer (1995), lowertotal factor productivity (TFP), by Hall andJones (1999), lower TFP growth, by Olson,Sarna, and Svamy (2000), or lower per capitaincome, by Acemoglu, Johnson, and Robin-son (2001). Thanks to different instrumentalvariables, Hall and Jones (1999) and Acemoglu,Johnson, and Robinson (2001) convincingly

argued that the causality ran from institutionsto economic performance.

The debate now focuses on the channelsthrough which institutions affect overall eco-nomic performance. Capital accumulationfirst appeared as the most likely culprit, andthis is why the institutional determinants ofinvestment have been closely scrutinized.Accordingly, the quality of institutions hasbeen found to affect total investment, amongothers by Mauro (1995) or Knack and Keefer(1995), public investment, by Mauro (1998),and foreign direct investment, by Wei (2000).These results explain the impact of governanceon capital accumulation but only incidentallyaddress its impact on productivity. This iswhere integration in world trade comes tothe fore due to its observed relationship toTFP, for instance documented by Edwards(1998).

Strikingly, however, the impact of institu-tions on the trade of goods has received littleattention so far. This is puzzling in view of thekey role that integration in world trade playsin development and the fact that many devel-oping countries either remain on the peripheryof world trade or are stuck with exporting pri-mary products. This observation is allegedlyone of the main puzzles of international eco-nomics, since relative factor endowments shouldresult in substantial North-South trade. To

*We appreciate helpful comments from two anony-mous referees, Frank Bohn, Axel Dreher, Bernd Hayo,Jan-Egbert Sturm, and seminar participants at UniversityCollege Dublin, Philipps-Universitat Marburg, and ETH-KOF Zurich. We are responsible for all remaining errors.

Meon: Associate Professor, Universite Libre de Bruxelles,DULBEA, CP-140, Avenue F.D. Roosevelt, 50, 1050Bruxelles, Belgium. Phone 32-2-650-66-48, Fax 32-2-650-38-25, E-mail [email protected]

Sekkat: Professor, Universite Libre de Bruxelles,DULBEA, CP-140, Avenue F.D. Roosevelt, 50,1050 Bruxelles, Belgium. Phone 32-2-650-41-39, Fax32-2-650-38-25, E-mail [email protected]

1. In the literature, the concepts of ‘‘institutions’’ or‘‘institutional framework’’ broadly refer to the activitiesof the state. Their functioning is referred to as ‘‘gover-nance.’’ In what follows, we shall use these expressionsinterchangeably so as to remain as general as possible.However, whenever possible, we will also focus on morespecific dimensions of governance, such as corruption orthe rule of law, which will be defined below.

ABBREVIATIONS

GDP: Gross Domestic Product

2SLS: Two-Stage Least Squares

TFP: Total Factor Productivity

Economic Inquiry doi:10.1111/j.1465-7295.2007.00064.x

(ISSN 0095-2583) Online Early publication June 11, 2007

Vol. 46, No. 2, April 2008, 227–240 � 2007 Western Economic Association International

227

date, the main explanation of that puzzle hasbeen to blame developing countries’ restrictivetrade policies. Thus, Sachs and Warner(1995a) found that economies that adjustmore slowly from primary-intensive to manu-factured-intensive exports were those whosetrade was less liberalized.

However, recent research suggests that forcountries to fully benefit from openness strat-egies, institutions might be crucial. Anderson(2005) thus suggested that the risk of preda-tion and imperfect enforcement of contractsimpairs foreign trade because it increases boththe costs and the risks of trading abroad.Anderson and Marcouiller (2002) accordinglyobserved that bad opaque public policies andan ineffective legal system reduce the volumeof trade. Dollar and Kraay (2003) also re-ported a positive correlation between opennessand the rule of law, although they argued thatthe causality between the two variables may bebidirectional. In a similar vein, Giavazzi andTabellini (2005) observed that political liberal-izations were associated with trade liberaliza-tions. The former moreover tended to leadrather than follow the latter, which suggeststhat political liberalizations at least partly causetrade liberalizations.

However, trade is not homogenous, and thevolume of trade is only one dimension ofa country’s integration in the world economy.Moreover, all exports are not equivalent interms of development and growth. The devel-opment economics literature suggests thatmanufactured exports are more likely to leadto development than nonmanufactured ex-ports. The empirical support for this is basedon the observation that countries with morediversified exports seem to do better and thatgrowth tends to be positively correlated withgrowth in manufactured production andexports. To highlight the reason for sucha relationship, some authors stress the impor-tance of ‘‘forward and backward linkages’’ increating higher positive externalities comingfrom manufacturing than from natural resourcesectors (see, e.g., Hirschman, 1958; Seers, 1964).Matsuyama (1992) underlined the importanceof learning by doing in manufacturing and itsimplication for the rate of human capital accu-mulation. Other arguments hinge on the Dutchdisease. Natural resources have more volatileworld prices than manufacturing, and this indu-ces greater uncertainty for primary commodityproducers, which extends to other sectors.

Uncertainty is known to be detrimental to fac-tor accumulation and hence to growth (see, e.g.,Sachs and Warner, 2001).

There is another reason to distinguish man-ufactured and nonmanufactured exports. Theimpact of institutional quality on exports ofprimary products is likely to differ from itseffect on manufactured exports. Endowmentsof natural resources create natural rents thatare usually controlled by the administrationand generate corrupt competition over theirdistribution as Ades and Di Tella (1999) sug-gested. In such a context, exports of nonmanu-factured goods may be positively rather thannegatively associated with the lack of qualityof institutions. Distinguishing exports of man-ufactured goods from exports of nonmanufac-tured goods may therefore lead to a betterspecification of exports regressions, hencemore reliable estimates of the impact of insti-tutions on trade.

Moreover, the current debate over the rela-tionship between institutions and trade remainsfairly vague on what is meant by institutions.Governance is indeed a multifaceted concept.It ranges from the rule of law to the degreeof democracy of the country. Unsurprisingly,there exists a wide choice of indicators, eachaiming to assess one dimension of the widerphenomenon. Unfortunately, most indicatorshave been developed separately, thus pro-ducing a lacunal picture of countries’ overallinstitutional environment. As a result, if eachdimension of governance has been indepen-dently studied, attempts to compare the impactof different facets of the institutional frame-work remain scarce. The lack of comparabilityof the various dimensions of the institutionalframework was remedied by Kaufmann,Kraay, and Zoido-Lobaton (1999a) who syn-thesized existing indicators to provide a dis-tinct and consistent assessment of the maindimensions of governance. They thus con-structed six governance indexes devoted tosix dimensions of the institutional framework.A second contribution of this paper is to takeadvantage of the set of indicators of Kauf-mann, Kraay, and Zoido-Lobaton (1999a)to compare the effects of several dimensionsof institutional quality on trade flows. Theresults should allow identifying the institu-tional reforms that may be the most promisingin economic terms.

Using a panel of around 60 countries over1990–2000, this paper examines separately the

228 ECONOMIC INQUIRY

impact of each dimension of the institutionalframework on total exports of goods, manu-factured goods exports and nonmanufacturedgoods exports. In a first stage, we use a simpleleast squares approach relating a given cate-gory of exports to a given dimension of theinstitutional framework plus a set of controlvariables. In a second stage, we use a two-stageleast squares (2SLS) approach to take accountof potential endogeneity of the institutionalvariables and get a clearer idea of their causaleffect.

In the first stage, we find a positive impactof the quality of institutions on the manufac-tured exports ratio but no significant impacton the ratio of nonmanufactured exports.When using the 2SLS approach, we find a pos-itive impact of the exogenous component ofinstitutions on exports of manufactures. Inparticular, an improvement in the quality ofthe regulatory framework is significantly andpositively associated with exports of manufac-tures. In contrast, we observe a negative impactof the exogenous component of institutions onthe exports of nonmanufactured goods. In par-ticular, nonmanufactured exports appear nega-tively affected by a better accountability ofpolitical leaders and higher respect of the ruleof law. This opposite correlation of the twokinds of exports with institutions results inthe total exports ratio being not significantlyrelated to institutions.

To reach those results, the rest of the paperis organized as follows: the next section dis-cusses why different categories of exportsmay be differently affected by the domesticinstitutional framework. The following sec-tion examines the impact of six differentdimensions of governance and compares theircapacity to account for cross-country differen-ces in exports performance. Section IV usesa 2SLS approach as a robustness check andto assess the causal link from institutions totrade. Section V concludes.

II. INSTITUTIONS AND TRADE

The study of the relationship between insti-tutions and trade is still in its infancy, hencethe relative scarcity of theoretical argumentslinking trade and governance. However, thereare reasons to contend that formal as well as

informal institutions may affect trade bothdirectly and indirectly.2 Moreover, there isground to believe that aggregating manufac-tured and nonmanufactured exports may bemisleading.

The Impact of Institutions on Exports

As the impact of institutions on the econ-omy is pervasive, institutions can affect thewillingness of agents to trade abroad not onlydirectly but also by affecting variables thatmay in turn lower the propensity of agentsto trade.

The direct impact of institutions on the pro-pensity to trade runs through the reduction ofthe expected return of trading abroad. Thus,faulty institutions may act as a tax on tradeflows. Moreover, cumbersome regulations andnit-picking bureaucracies have often been usedas nontariff barriers to trade. Rodrik (2002)pointed out that the main impediment to inter-national trade may indeed be the problem ofcontract enforcement, which is of particularrelevance in international transactions sincethey confront traders in countries whose legaland political jurisdictions differ. Needless tosay, these differences may also be accompa-nied and magnified by differences in the qual-ity of institutions and in the rule of law inparticular.

A first theoretical illustration of the conse-quences of imperfect contract enforcement ontrade was provided by Anderson and Young(2006) who found that lack of enforcementof contracts may act as a tariff on risk-neutraltraders and therefore reduce trade.3 In a re-lated contribution, Anderson and Marcouiller(2002) incorporated the impact of the qualityof institutions in a gravity model by assumingthat a country with weak institutions incursa positive markup on the price of its exportsthat reduces foreign demand. They thereforefound that a deterioration of the quality of

2. Note that some authors argue that the causalitybetween institutions and trade may run in the other direc-tion (Rodrik, 2002, or Treisman, 2000). Empirical evi-dence suggests, however, that such a relationship isstatistically fragile and may in large part be due to a sampleselection bias (Knack and Azfar, 2003). We abstract fromthis issue in this section but will address it in Section IV.

3. Contract enforcement becomes crucial when trad-ers incur significant sunk costs resulting in a holdup prob-lem. Robert and Tybout (1997) documented that suchcosts may be large and have dramatic consequences ontrade.

MEON & SEKKAT: INSTITUTIONS AND TRADE 229

a country’s institutions should result ina reduction of its exports.

The impact of institutions on trade mayalso result from their effect on the risks asso-ciated with international transactions. Thispoint was made by Anderson and Marcouiller(2005) in a theoretical contribution. Theseauthors developed a model of trade betweentwo regions whose inhabitants may either spe-cialize according to their comparative advan-tage or opt for a career in predation. They thenshowed that insecurity may prevent trade eventhough it offers potential mutual gains. Intheir framework, not only does predationreduce trade because it is a direct deductionon the flow of traded goods but also becauseit diverts resources from their productive allo-cation toward the defense of property rights. Itfollows that good institutions may help barpredation and thus foster trade.

Defective institutions may also impactthe geographic structure of trade. Thus,Lambsdorff (1998) observed that some coun-tries, like Belgium, France, Italy, the Nether-lands, and South Korea, are persistentlyoverrepresented in the imports of corruptcountries. He observed on the other hand thatcountries like Sweden and Malaysia tend totrade less with corrupt importers. Lambsdorff(1998) concluded that those differences maybe due to the differences in the propensityof exporters to offer backhanders.

In addition to their direct effect, institu-tions may also indirectly affect trade throughtheir impact on other variables that determinetrade flows. There are at least two such vari-ables that come to mind: investment and pro-ductivity. Thus, the literature suggestsa relationship between the investment ratioand the quality of institutions. In a comprehen-sive study, Brunetti and Weder (1998) showedthat nearly all facets of governance, rangingfrom political stability to the control of graft,tend to be positively associated with invest-ment. Other studies, like Mauro (1995) orKnack and Keefer (1995), obtain similarresults. At the same time, investment has beenfound to affect trade, for instance by Rodrik(1995). One can therefore expect a deteriora-tion of the quality of institutions to result inlower trade through a lower investment ratio.

Bad institutions have also been found toimpact productivity. Hall and Jones (1999)thus observed that bad institutions reduceaggregate productivity, while Olson, Sarna,

and Svamy (2000) found that they are alsoassociated with slower productivity growth.As a greater productivity is necessary to coverthe cost of trading on foreign markets, asBernard et al. (2003) emphasized, one mayreasonably expect that countries whose insti-tutions result in low productivity will likelyhave difficulties in exporting and tradingabroad.

However, it must be stressed that the abovearguments may not be equally relevant to allkinds of exports. They may in particular bemore directly relevant to exports of manufac-tured goods than to exports of nonmanufac-tured goods and raw materials in particular.The next subsection explains why.

Nonmanufactured Exports as an Exception

The relationship between institutions andthe volume of nonmanufactured goods maydiffer from the relationship expected for otherexports. For instance, Rauch and Trindade(2002) have found that an informal institutionlike ethnic Chinese networks affects trade indifferentiated goods more than trade in homo-geneous goods. As manufactured goods areusually more differentiated than nonmanufac-tured goods, this finding points to a distinctdirect effect of institutions on the two typesof goods. The difference may hinge on boththe direct and the indirect channels that leadfrom institutions to trade.

The direct impact of institutions on nonman-ufactured exports may even be opposite to theone on manufactures. This would in particularbe the case in sectors where firms are moreprone to make corrupt deals. For instance,the oil and gas sector ranks third in Transpar-ency International’s 2002 bribe payer survey.4

A country specialized in such sectors mayexport more if its administration is corrupt.Greater corruption of the administration ofthat exporting country would ease rather thanhamper exports.

The indirect effect of institutions may alsodiffer across sectors. Thus, in a sector whereendowments determine comparative advan-tages, the impact of governance on productiv-ity and infrastructure may be of secondaryimportance. In a nutshell, if there is a resource

4. The oil and gas sector is only preceded by the publicworks/construction sector and the arms and defense sectorin that survey.


to be exploited, it will be even though othersectors suffer from a lack of infrastructure.

A comparable argument deals with thedeterminants of a country’s comparative ad-vantage in the production and exports of man-ufactured goods versus the production andexports of nonmanufactured goods. If ailinginstitutions are associated with lower invest-ment in education (Mauro, 1998), hence withlower literacy (Kaufmann, Kraay, and Zoido-Lobaton, 1999b), then bad governance willdistort production away from manufacturedgoods toward nonmanufactured goods. Thisargument is due to the contention that the pro-duction of manufactured goods is relativelymore skill intensive than the production ofnonmanufactured goods. It therefore impliesboth a positive relationship between institu-tional quality and exports of manufacturedgoods and a negative relationship betweeninstitutional quality and exports of nonmanu-factured goods.

Overall, one may conclude that, althoughthe relationship between the quality of institu-tions and the volume of manufactured exportsshould be positive, this result may not extend toexports of nonmanufactured goods. Their rela-tionship with institutional quality is moreambiguous and may well be negative.5 The nextsection empirically tests those presumptions.

III. A COMPARISON OF DIFFERENT DIMENSIONSOF THE INSTITUTIONAL FRAMEWORK

Before providing the results of our estima-tions, this section first presents the econometricstrategy that is used to study the relationshipbetween governance and exports of variouskinds and describes the data employed in ourregressions.

Econometric Specification

To study the relationship between traderatios, which vary over time, and institutionalindexes, for which we only have one observa-

tion, we separate explanatory variables intotwo subsets: those that vary over time (firstsubset) and those that do not (or almost not).As the indexes of Kaufmann, Kraay, andZoido-Lobaton (1999a) are still only availableon a time span that is too limited to featuremeaningful variations, we only use their firstvintage and include it in the second subsetof variables. We then apply a two-step proce-dure. The first step consists in estimatinga model where the explanatory variables arethose included in the first subset and countryfixed effects. In the second step, the estimatedfixed-effects coefficients are used as dependentvariables to be explained by governance indi-cators and the other time-invariant variables.

To apply that two-step procedure, we startfrom a specification that was used by Sekkatand Varoudakis (2000). Assuming that theexporter is small with respect to the marketfor manufactures, profit maximization leadsto the following specification of exports ofmanufactures:

log ðXitÞ 5 a0i þ a1 log ðEitÞþ a2RYPit þ lit

ð1Þ

where

Xit is relevant ratio of exports to grossdomestic product (GDP) for year t (totalexports, manufactured exports and nonmanu-factured exports);

a0i is country i’s fixed effect;Eit is country i’s real effective exchange rate

for year t, where an increase inEit stands for an appreciation of the export-

er’s currency;RYPit is the GDP growth rates of country

i’s partners; andlit is the error term.

Total exports refer to good exports (exclud-ing services, see Footnote 5), and it is splitbetween manufactures and nonmanufactures.We scaled down exports by GDP to correctfor the differences in countries’ sizes. The con-trol variables are standard in the literature, andall have a well-defined expected impact on man-ufactured exports. The coefficient of the realexchange rate should be negative because anincrease in Eit means an appreciation of theexporter’s currency. We expect a positive coef-ficient for the growth rates of a country’s part-ners. If a country’s partners grow faster, they

5. As a referee rightly pointed out, the relationship ofinstitutions with exports of services may also differ fromtheir relationship with other exports. We do not addressthis issue here, because data on services have only recentlybecome available. Namely, the Organization for Eco-nomic Cooperation and Development only started pub-lishing data on exports of services in 2006. However,studying the impact of institutions on exports of serviceswould be highly relevant.


will increase their demands for goods producedin that country, thereby raising its exports.6

Once Equation (1) is estimated, countries’fixed effects are regressed on the set of time-invariant variables. The exact specification ofthat second estimation is

a0i 5 g0 þ g1 log ðPotiÞþ g2 log ðInstiÞ þ ei

ð2Þ

where

a0i is country i’s fixed effect as estimated inEquation (1);

Poti measures country i’s market potential;Insti is an index of the quality of country i’s

institutions; andei is the error term.

We used countries’ market potential asa control variable in the exports’ regressions.That variable is defined as the inverse–distanceweighted average of a country’s partners’GDP’s. It therefore measures how closea country is to other markets. This is a struc-tural variable reflecting a country’s structuralproximity to potential trade partners. Our pre-sumption is that the closer a country is to richeconomies, the more it may export. We there-fore expect the market potential variable to bepositively correlated with a country’s exportsof manufactures ratio.7 Note that this variablecomplements the year-to-year variations inpartners’ GDP, incorporated in Equation(1), because it also takes account of the prox-imity to such partners. It was computed onlyfor 1 yr by Head and Mayer (2004).

Data Sources

All noninstitutional variables are drawnfrom the World Development Indicators data-base. The only exception is market potential.This variable was downloaded from the Cen-tre d’Etudes Prospectives et d’InformationsInternationales Web site.

Of course, the explanatory variables ofinterest are the institutional variables. We con-sider all six governance indexes developed byKaufmann, Kraay, and Zoido-Lobaton

(1999a, 1999b), who classified available in-dicators of governance into six independentclusters and aggregated them into as manycomposite indexes. Each composite indicatorrefers to a different dimension of governance.It ranges from �2.5 to +2.5, higher values sig-naling better governance. To allow for the esti-mation of elasticities in Equation (2), we added3.5 to those indexes, so as to be able to computelogarithms. Since the composition of the sixindicators is reported in Kaufmann, Kraay,and Zoido-Lobaton (1999b), we simply recalltheir definitions here. They all measure a differ-ent dimension of the institutional frameworkbut can be presented as three pairs of indexes.

The first pair of indicators provided byKaufmann, Kraay, and Zoido-Lobaton (1999a,1999b) assesses the soundness of a country’spolicies and the efficiency of the administra-tion that implements them. The indicatornamed ‘‘government effectiveness’’ (Goveff)is defined as an assessment of the ‘‘perceptionsof the quality of public service provision, thequality of the bureaucracy, the competence ofthe civil servants, the independence of the civilservice from political pressures, and the cred-ibility of the government’s commitment topolicies.’’ The indicator labeled ‘‘regulatoryburden’’ (Reg) was constructed to gauge‘‘the incidence of market unfriendly policiessuch as price controls or inadequate banksupervision, as well as perceptions of the bur-den imposed by excessive regulation.’’ Thisindicator measures dimensions of governancerelated to what Easton and Walker (1997)refer to as economic freedom.

The second pair of indicators was built toassess the degree to which a country’s citizensfeel bound by the legal framework embodied intheir country’s institutions. Thus, the ‘‘rule oflaw’’ index gauges ‘‘the extent to which agentshave confidence in and abide by the rules ofsociety’’ (Rulelaw). This cluster is the focusof Dollar and Kraay (2003). The other indexis labeled ‘‘(control of) graft’’ or ‘‘probity.’’Graft, or corruption, is commonly defined inthe literature as the misuse of public powerfor private benefits. Since Mauro’s (1995) sem-inal paper, it has been the focus of a bloomingempirical literature, and its impact on the struc-ture of trade was studied by Lambsdorff (1998).

The last pair of indicators refers to the pro-cess of selection of the authority. It thereforemeasures aspects of governance that havebeen the focus of the literature devoted to

6. We also included previous year’s investment in theset of explanatory variables, but that variable turned outinsignificant.

7. We also used other control variables in that step,such as country size and human capital, but the resultswere unaffected.


the impact of democracy and political stabil-ity. More precisely, the indicator called ‘‘voiceand accountability’’ (Voice) measures ‘‘theextent to which citizens of a country are ableto participate in the selection of govern-ments.’’ It is therefore a measure of the open-ness of the political system, that is its degree ofdemocracy, whose relationship with economicperformance was, for instance, studied byBarro (1996). The ‘‘lack of political violence’’(Lackviol) indicator ‘‘measures perceptions ofthe likelihood that the government in powerwill be destabilized or overthrown by possiblyunconstitutional and/or violent means.’’ Thisindicator therefore provides an assessmentof the political risk associated with a country.

One must bear in mind that those indicatorswere built to describe different dimensions ofthe quality of the institutional framework, asopposed to being different proxies for thesame phenomenon. Using them in turn asexplanatory variables of the same dependentvariable should not, therefore, be chiefly seenas a robustness check. On the contrary, it isa way to determine which aspect of the insti-tutional framework really matters for a coun-try’s openness to trade.

Overall, we assembled a sample that includesannual data over the period 1990–2000 andcovers between 59 and 57 countries. The listof countries included in the estimation isreported in the appendix Table A1 as well asthe descriptive statistics of the variables inthe appendix Tables A2–A4.

Empirical Results

Tables 1A–1C report the result of the sec-ond stage of the analysis, namely the result ofthe estimation of Equation (2), for variousdimensions of governance. The results of thefirst stage are reported in Table A5 in theAppendix. They conform to standard intui-tion. Namely, an appreciation of the exchangerate significantly reduces all kinds of exports,which are also positively and significantlyassociated with growth in partner countries.

The regressions of interest are,however, thoseof the second stage, which estimate Equation (2).The results of the estimation of that expressionshow marked differences between the variouscomponents of total exports. The first such dif-ference can be found in the overallquality of fit ofthe estimated relationships. Namely, with anadjusted R2 ranging from 48% to 52%, the qual-

ity of fit for manufactured exports can be consid-ered satisfactory, given that the sample is onlya cross-section in the second step of the regres-sion.Thesame conclusion does notapply to non-manufactured exports, whose adjusted R2 neverexceeds 19%. Unsurprisingly, the quality of fit ofthe relationship whose dependent variable is thesum of the two previous variables (i.e., totalexports) is also disappointing.

The second difference between various esti-mations lies in the significance of the indepen-dent variables. It appears that the proximity oflarge markets has a significantly positive im-pact on exports of manufactured goods sincemarket potential exhibits a positive and signif-icant coefficient in all regressions. This result,however, does not hold for nonmanufacturedexports, which are negatively and significantlyassociated with that variable. As a consequence,the relationship between a country’s marketpotential and its total exports ratio, thoughintuitive, appears fairly weak. However, it ispositive and significantly so in three regres-sions out of seven.

The main difference between the variouskinds of exports has to be found in the key var-iables of interest, namely governance variables.First, we observe that governance indexes ingeneral exhibit positive and significant coeffi-cients in estimations involving exports of man-ufactures, the only exception being the qualityof the regulatory framework and voice andaccountability of political leaders, which failto appear significantly in any regression.Accordingly, better institutional quality shouldbe associated with larger exports of manufac-tured goods. By contrast, we observe thatexports of nonmanufactured goods are neversignificantly associated with governance.

Here again, the discrepancies in the reac-tion of the various types of exports to institu-tional quality blur its impact on total exports.Indeed, whereas the coefficient of institutionalquality is in general intuitive in the relation-ships involving the total exports ratio, italmost always fails to be significant at usuallevels of confidence.8 The only exception is

8. One may notice that, as we scale down all exportsby GDP, for reasons that have been underlined above, wemay well underestimate the impact of institutions ontrade. Namely, institutions also have a direct effect onGDP. A variation of institutional quality therefore affectsboth the numerator and the denominator of all exportsratios in the same direction, which minimizes its absoluteimpact on the volume of exports.


TABLE 1A

Results of the Least Square Regression of Equation (2): ‘‘Respect for

the Institutional Framework’’

Dependent

Probity Rule of Law

Xtot Xman Xnm Xtot Xman Xnm

Constant �1.30 (1.25) �10.89 (7.41)*** 6.76 (4.11)*** �1.44 (1.39) �11.00 (7.21)*** 6.63 (4.20)***

Market potential 0.17 (1.27) 1.04 (5.55)*** �0.63 (3.11)*** 0.21 (1.65)* 1.05 (5.17)*** �0.57 (3.16)***

Institutional quality 0.40 (1.34) 1.06 (2.18)** �0.10 (0.22) 0.22 (0.68) 1.10 (1.95)* �0.41 (0.89)

Adjusted R2 0.06 0.51 0.18 0.05 0.51 0.19

Number ofobservations

59 57 57 59 57 57

Notes: Absolute t statistics are displayed in parentheses under the coefficient estimates. The estimates are heteroske-dastic consistent.

*Test statistic is significant at the 10% level; **significant at the 5% level; ***significant at the 1% level.

TABLE 1B

Results of the Least Square Regression of Equation (2): ‘‘Government Action’’

Dependent

Government Effectiveness Regulatory Framework


Constant �1.42 (1.38) �11.01 (7.37)*** 6.71 (4.16)*** �2.08 (1.74)* �12.33 (7.02)*** 6.85 (3.64)***

Market potential 0.20 (1.59) 1.05 (5.34)*** �0.61 (3.16)*** 0.21 (1.88)* 1.22 (7.05)*** �0.65 (3.54)***

Institutional quality 0.27 (0.81) 1.10 (2.02)** �0.23 (0.49) 0.65 (1.18) 0.94 (1.11) �0.03 (0.05)

Adjusted R2 0.05 0.51 0.18 0.07 0.48 0.18


59 57 57 59 57 57



TABLE 1C

Results of the Least Square Regression of Equation (2): ‘‘Selection of the Authority’’

Dependent

Voice and Accountability Lack of Political Violence


Constant �1.55 (1.50) �11.44 (7.56)*** 6.77 (4.17)*** �1.30 (1.29) �11.10 (7.71)*** 6.84 (4.23)***

Market potential 0.25 (2.11)** 1.17 (6.37)*** �0.60 (3.21)*** 0.12 (0.93) 1.02 (5.47)*** �0.66 (3.58)***

Institutional quality 0.00 (0.01) 0.58 (0.88) �0.33 (0.61) 0.73 (1.91)* 1.36 (2.07)** 0.06 (0.12)

Adjusted R2 0.04 0.48 0.18 0.10 0.52 0.18


59 57 57 59 57 57




the lack of political violence, which is posi-tively related to total exports at the 10% levelof confidence.

These results should, however, be consid-ered as tentative because they may in fact beaffected by a simultaneity bias. Namely, insti-tutions are as likely to affect trade as they areto be affected by it. The aim of the next sectionis precisely to address that bias.

IV. ROBUSTNESS CHECK

As mentioned above, the direction of cau-sality between trade and institutions is ambig-uous, which may result in a simultaneity biasin our estimations. Fortunately, solutions tothat issue have been suggested in the recent lit-erature on the empirics of institutions. Theyconsist in using instrumental variables forinstitutional quality. That solution allowsnot only to provide better quantitative esti-mates but also to tackle the issue of causality.

The subsequent question is then that of theinstrument that we use. Several instrumentalvariables have been used so far, ranging frommeasures of ethnic and linguistic fractionaliza-tion by Mauro (1995) to distance to theequator by Hall and Jones (1999). Each instru-mental variable can be thought to affect tradethrough its impact on institutions. Namely,greater ethnic fractionalization is no hin-drance to trade as such, but it results in greatersocial unrest, as Mauro (1995) argued, whichin turn affects trade. A country’s legal originindicates its colonial origin, which, as Hall andJones (1999) claimed, is a determinant of thequality of that country’s institutional infra-

structure. Finally, Hall and Jones (1999) alsocontend that distance to the equator alsodetermined former colonies’ exposure toWestern influence.

One may, however, argue that geographyalso directly determines the capacity of a coun-try to participate in world trade. This is whywe control for market potential in the secondstep of our regressions. Along similar lines,one may contend that ethnolinguistic fraction-alization may slow down the diffusion of newideas, hence cut down productivity and even-tually competitiveness. However, this effect iscontrolled for by the real exchange rate inEquation (1). Hence, we think these variablesto be good instruments for institutions in ourframework.

To maximize the predictive power of ourinstruments, we use a 2SLS approach and a com-bination of all these variables. Namely, we firstregress each governance indicator on the set ofinstruments including ethnolinguistic fraction-alization (Mauro, 1995), distance to the equa-tor, and legal origin (Hall and Jones, 1999).Having observed that the fit of the relationshipspectacularly increased when the square of theethnic fractionalization index was included, wealso incorporate it among the regressors. Foreach governance indicator, we therefore get a fit-ted counterpart, which is then included in Equa-tion (2) in place of the observed variable. Aseach fitted variable is a combination of prede-termined ones, it is a reasonable instrumentand allows causality to be determined. Theresults of this 2SLS estimation are displayedin Tables 2A–2C.

A cursory glance at Tables 2A–2C revealsthat the previous section’s main conclusions

TABLE 2A

Results of the 2SLS Regression of Equation (2): ‘‘Respect for

the Institutional Framework’’ Variables

Dependent

Probity Rule of Law


Constant �1.01 (0.90) �10.71 (7.11)*** 7.05 (3.78)*** �1.04 (0.95) �10.76 (7.18)*** 6.97 (3.90)***

Market potential 0.23 (1.40) 0.99 (4.61)*** �0.53 (1.97)* 0.26 (1.62) 0.98 (4.59)*** �0.45 (1.72)*

Institutional quality �0.22 (0.48) 1.15 (1.45) �0.94 (1.33) �0.40 (0.78) 1.29 (1.49) �1.44 (1.93)*

Adjusted R2 0.01 0.48 0.23 0.01 0.48 0.26

Number of observations 48 48 48 48 48 48




survive to the instrumentation of institutionalquality. The observed differences between thethree exports ratios remain. More precisely,the quality of fit remains quite high for man-ufactured exports, satisfactory for nonmanu-factured exports, but very disappointing fortotal exports.

As regards the association of the threekinds of exports with their explanatory varia-bles, manufactured exports are still positivelyrelated to the quality of institutions when it ismeasured by the regulatory framework index.All other institutional indexes exhibit positivecoefficients, but they are not significant. Some,like probity or the rule of law, however, comerather close to being significant.

Concerning nonmanufactured exports, therecourse to 2SLS regressions noticeably modi-fies the results of our estimations. Thoseexports now appear negatively affected bythe quality of institutions. This is true wheninstitutional quality is measured by the rule

of law, voice and accountability, and the lackof political violence. This finding suggests thatreverse causality was probably underminingour previous results. By addressing this issue,2SLS regressions show that nonmanufacturedexports are greater in countries with faultyinstitutions. This also provides an additionalargument for discriminating exports of manu-factured and nonmanufactured goods.

When it comes to analyzing separately theimpact of the different dimensions of gover-nance, the picture provided by instrumentalvariable regressions differs somewhat fromthe previous section’s. Indeed, the quality ofthe regulatory framework is the only institu-tional variable whose exogenous componentis significantly associated with exports of man-ufactured goods at conventional levels of con-fidence. However, the probity and the rule oflaw indexes are only marginally rejected at the10% level of confidence. This is encouragingsince some observations were lost due to the

TABLE 2B

Results of the 2SLS Regression of Equation (2): ‘‘Government Action’’ Variables

Dependent

Government Effectiveness Regulatory Framework


Constant �1.02 (0.92) �10.85 (7.28)*** 7.12 (3.86)*** �0.21 (0.12) �14.89 (5.41)*** 9.76 (4.57)***

Market potential 0.27 (1.52) 0.97 (4.11)*** �0.48 (1.67)* 0.24 (1.53) 0.95 (5.44)*** �0.55 (1.95)*

Institutional quality �0.47 (0.73) 1.43 (1.33) �1.35 (1.57) �0.84 (0.56) 4.41 (2.01)** �2.78 (1.34)

Adjusted R2 0.01 0.48 0.25 0.01 0.50 0.24


48 48 48 48 48 48



TABLE 2C

Results of the 2SLS Regression of Equation (2): ‘‘Selection of the Authority’’ Variables

Dependent

Voice and Accountability Lack of Political Violence


Constant �1.02 (0.92) �10.97 (7.23)*** 7.18 (3.98)*** �1.02 (0.93) �10.95 (7.20)*** 7.14 (4.04)***

Market potential 0.31 (1.63) 0.99 (3.67)*** �0.43 (1.50) 0.29(1.67)* 1.00 (4.08)*** �0.41 (1.52)

Institutional quality �0.74 (0.94) 1.37 (1.02) �1.69 (1.75)* �0.65 (0.92) 1.34 (1.10) �1.82 (1.92)**

Adjusted R2 0.03 0.47 0.26 0.02 0.47 0.26

Number of observations 48 48 48 48 48 48




unavailability of some instruments, and thesize of the sample is therefore limited.

Among the institutional indexes that aresignificantly associated with the exports ofnonmanufactured goods ratio, the lack ofpolitical violence is the most significant andthe one with the largest coefficient. Voiceand accountability and the rule of law exhibitthe second and third largest absolute coeffi-cients. Finally, like in the previous section,total exports do not seem correlated to thequality of institutions. However, we cannow suggest an explanation to this result. Itstems from the fact that the two componentsof total exports correlate in opposite direc-tions with institutions.

Overall, these results suggest a positive andcausal relationship between institutions andexports of manufactured goods. They alsounderline a causal relationship between insti-tutions and exports of nonmanufacturedgoods. However, this relationship is negative.As a result, no relationship between totalexports and institutions is observable.

These findings are consistent with those ofAnderson and Marcouiller (2002), whoreported a positive relationship between insti-tutional quality and total exports. We, how-ever, probe deeper in that relationship byshowing that it is mainly driven by the impactof governance on exports of manufacturedgoods. This result is important since manufac-tured exports are admittedly the component ofexports that is the most likely to drive growth.Therefore, bad institutions are likely to distortthe composition of a country’s trade in a waythat is inimical to growth and development.

To get a clearer picture of the meaning ofour results, however, it is useful to comple-ment the insights of Tables 2A–2C with aquantitative assessment of the impact of theregulatory framework on a country’s exportsof manufactured items ratio. Let us, forinstance, assume that Romania, whoserescaled regulatory framework score amountsto 1.31, could raise it by 1 standard deviation,which would take it to the level of Belgium.This would amount to 11.31% improvementin Romania’s index. According to our pointestimate of the elasticity of the exports of man-ufactured goods ratio, that improvement inthe regulatory framework would result ina 4.41 � 11.31 � 49.86% increase of Roma-nia’s exports of manufactured goods ratio,which would then exceed 23%. That increase

would bring Romania’s exports ratio closeto Finland’s.

V. CONCLUSION

The impact of institutions on the economyis pervasive. The present paper emphasizesthat they can affect a country’s integrationin international trade. To do so, it distin-guishes manufactured and nonmanufacturedexports and six dimensions of the institutionalframework. The results suggest that defectiveinstitutions chiefly hurt a country’s capacity toexport manufactured goods. The use of in-strumental variables techniques moreover sug-gests that the causality runs from institutionsto exports. Accordingly, an improvement ininstitutional quality would result in an in-crease of manufactured exports.

Exports of nonmanufactured goods seemrelated to institutional quality in the oppositeway. This differentiated relationship of insti-tutions with the two kinds of exports resultsin an insignificant relationship between insti-tutional quality and the total exports ratio.

A by-product of the present analysis is thatthe various facets of governance may not playthe same role in affecting exports of manufac-tured goods. On the whole, our estimationssuggest that the quality of the regulatory frame-work may be the facet of governance that is themost robustly associated with manufacturedexports. Other dimensions of the institutionalframework, like the rule of law or governmenteffectiveness, may also play a role, but theirrelationship with manufactured exports is lessrobust. At the same time, nonmanufacturedexports seem to respond chiefly to the lack ofpolitical violence, the rule of law, and theaccountability of political leaders.

Taken at face value, these findings havestraightforward policy implications. They sug-gest that improving a country’s institutionalframework may be instrumental in improvingthat country’s integration in internationaltrade. By allowing it to reorientate its tradetoward exports that are more favorable togrowth, it may also improve its developmentprospects. This paper’s findings also suggestthat all dimensions of the institutional frame-work are not equal in affecting trade. It thusappears that the quality of the regulatoryframework should receive high priority.Determining how and how fast this may bedone paves the way for further research.


APPENDIX

TABLE A1

Countries in the Regressions

Least Squares 2SLS

Armenia Australia

Australia Austria

Austria Belgium

Belgium Bolivia

Bolivia Cameroon

Cameroon Canada

Canada Chile

Chile Colombia

China Costa Rica

Colombia Cote d’Ivoire

Costa Rica Denmark

Cote d’Ivoire Ecuador

Croatia Egypt, Arab Republic

Czech Republic Finland

Denmark France

Ecuador Germany

Egypt, Arab Republic Ghana

Finland Greece

France Iceland

Georgiaa Ireland

Germany Israel

Ghana Italy

Greece Japan

Hungary Jordan

Iceland Malawi

Ireland Malaysia

Israel Morocco

Italy Netherlands

Japan New Zealand

Jordan Nicaragua

Macedonia, FYR Nigeria

Malawi Norway

Malaysia Pakistan

Moldova Paraguay

Morocco Philippines

Netherlands Portugal

New Zealand Singapore

Nicaragua South Africa

Nigeria Spain

Norway Sweden

Pakistan Switzerland

Paraguay Tunisia

Philippines Uganda

Portugal United Kingdom

Romania United States

Singapore Uruguay

Slovak Republic Venezuela, RB

South Africa Zambia

Spain

Sweden

Switzerland

Tunisia

Uganda

Ukrainea

United Kingdom

United States

Uruguay

Venezuela, RB

Zambia

aOnly present in the total exports sample.

TABLEA2

Su

mm

ary

Sta

tist

ics

of

the

Go

ver

nan

ceV

ari

ab

les

RespectfortheInstitutionalFramew

ork

GovernmentAction

SelectionoftheAuthority

Probity

Rule

ofLaw

GovernmentEfficiency

Regulatory

Framew

ork

VoiceandAccountability

Lack

ofPoliticalViolence

Mea

n1

.34

1.3

51

.34

1.3

61

.38

1.3

3

Med

ian

1.3

51

.40

1.4

01

.39

1.4

11

.36

Sta

nd

ard

dev

iati

on

0.2

70

.25

0.2

50

.16

0.2

30

.23

Min

imu

m0

.88

0.8

70

.78

0.8

10

.79

0.7

9

Ma

xim

um

1.7

31

.70

1.7

21

.56

1.6

51

.65


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institutional quality and trade: which institutions? which trade?

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