Integration and Growth in the EU: The Role of Trade by María Luz García de la Vega* José A. Herce**

DOCUMENTO DE TRABAJO 2000-20

December, 2000

* Dpt. of Economics, Universidad Complutense de Madrid (Spain). Visiting graduate student at the University of California - Santa Cruz. ** FEDEA and Universidad Complutense de Madrid

Los Documentos de trabajo se distribuyen gratuitamente a las Universidades e Instituciones de Investigación que lo solicitan. No obstante están disponibles en texto completo a través de Internet: http://www.fedea.es/hojas/publicaciones.html#Documentos de Trabajo

These Working Documents are distributed free of charge to University Department and other Research Centres. They are also available through Internet: http://www.fedea.es/hojas/publicaciones.html#Documentos de Trabajo

Abstract

Using spatial econometrics techniques this paper investigates the relationship between trade and growth in the European Union (EU). We find that the EU integration process has promoted trade, especially between close neighbours, and that trade has been the channel of diffusion of interdependent growth, being this fact more important at the beginning of the integrating process than in the latter years. This result illustrates the idea that by enhancing trade, economic integration induces externalities between countries.

(JEL F15, F43, O47, R11)

1. Introduction

It is generally believed that trade can promote growth in industrial countries. With this idea in mind and a mixture of economic and political considerations, the EU countries have followed a deep regional integration. It started with the elimination of trade barriers among countries, allowing latter for the free intra-EU movements of labour, services and capital and the pursuit of economic policies in order to launch a common currency, already under way.

Some of the empirical studies that estimate the long run effects of the EU integration process are based in endogenous growth models that take into account the dynamic gains of trade; for instance, the incentives for the accumulation of production factors and the spillovers due to a deeper economic relationship between countries. The contribution of this paper is the measurement of interdependent growth among the EU countries, considering trade as the main factor of diffusion of growth externalities. Trade in this study is seen as the channel through which the interrelation of countries takes place and the source of spillovers that enhance mutual growth.

Recent analyses of growth and trade due to Coe and Helpman (1993) and Branstetter (1996) explore whether there have been international spillovers among trading economies. Following this line, on the one hand, this paper shows how general trade externalities are related to interdependent growth between countries. There is an extensive theoretical literature that postulates the positive growth effects associated with free trade. For instance, Grossman and Helpman (1991) develop models to determine how trade can shift resources to different activities (production or R&D), Aghion and Howitt (1998) write growth models in which different economic policies and openness affect the endogenous accumulation of resources. On the other hand, trade is an indicator of the degree of integration among countries, for instance, those belonging to the EU.

Other possible way to analyse the effects of trade would be to explore how trade equalises goods or factors prices across countries, as it was developed by Samuelson (1948) and Helpman and Krugman (1985). Nevertheless our focus is on measuring how the EU process, though trade among them, has made the growth rates of its member countries more interdependent. This set-up is explored in Miller and Spencer (1977) and Grinols (1984). They, using a general equilibrium approach, reflect the interdependence between different sectors of the economy due to the increase of trade. Prewo (1974) measures integration effects of the EEC using a model that links inter-industry structures via gravitational trade flows. More recently Frankel and Romer (1996) examine different determinants of trade and growth and illustrate the influence of distance and other geographical and cultural relationships among countries on trade.

As an empirical tool, spatial econometrics (Anselin, 1988) based on the multidirectional dependence present among observations in cross-sectional data sets, links very naturally with both ideas. First, the idea that EU integration generates more economic relationships and therefore more trade, and second, how growth in a particular EU country affects growth in other country depending on the economic connections between them. This kind of empirical analysis of interdependent growth has been used by Goicolea, Herce and de Lucio (1998) to show that flows of goods among Spanish regions enhance their mutual growth.

We thus examine how trade dependence between countries incite their mutual growth, to find that there is evidence of this. We also show that this externality has decreased with time. Our conclusion is that the EU process has overcome some geographical “anomalies” concerning flows of trade among neighbors and that there is evidence that trade has been an important element to encompass the integration of the EU economies. In the latter years, other factors, a deeper financial integration for instance, may have partly substituted the role of trade to create an interdependent growth pattern among EU countries.

The rest of this paper is organized as follows. Section 2 describes briefly the EU integration process and shows that it has been a case of integration between neighbors, in which distance has played a role. Section 3 describes the EU trade flows. A very simple model of interdependent growth is explained in section 4. The measurement of interdependent growth using spatial econometrics is studied in Section 5. This section contains the paper’s central result concerning trade, growth and economic integration. Finally, Section 6 summarises the results obtained.

2. The EU integration process

A short history

The origins of the European economic co-operation lie with the U.S. aid to rebuild Europe after the Second World War. As soon as 1948 the Organisation for European Economic Co-operation (OEEC) was created with the additional idea to promote trade liberalisation. Indeed, it was supported by ideological movements in favour of the European unification. In 1951, the core of the European Union was founded: France, West Germany, Italy, Belgium, Luxembourg and the Netherlands created the European Coal and Steel Community (ECSC), a common market in coal, iron and steel. It was the beginning of the Franco-German economic alliance that six years later went even further. With the Treaty of Rome (1957), the ECSC countries established the European Economic Community (EEC). The Treaty had as main objectives the establishment of a common market (achieved in 1992 through the so-called Single Market) and the approximation of the members’ economic policies. By 1961, the EEC internal tariff barriers had been reduced and quota restrictions largely eliminated. Few years later, in July 1968 the Custom Union was complete. Internal community custom duties were removed and the Common External Tariff established.

At in about the same time, a free trade association was created in Europe (EFTA, 1961) among the United Kingdom, Denmark, Sweden, Norway, Portugal, Switzerland, Austria and Liechtenstein (EFTA7+Liechtenstein). This association was enlarged with Finland and Iceland years later (1961, 1970 respectively). The United Kingdom however applied for membership to the EEC in 1961, 1967 and 1970 and joined the EEC in 1973 when it was also enlarged to Ireland and Denmark.

Coinciding with the end of the Basle Agreement or “snake” scheme for currency flotation, discussion of a European Monetary Union (EMU) was started. The effects of the U.S. dollar instability on intra-European exchange rates led EEC leaders to focus on achieving a deeper monetary integration. In 1978-79 proposals were put forward for a European Monetary System (EMS). The EMS was then created. It started the co-ordination of the exchange rate policies among the countries of the Community and helped considerably to limit short-term nominal exchange rate fluctuations afterwards. Years after the creation of the EMS, the Community was again enlarged with the accessions of Greece (1981), Spain and Portugal (1986) and, lately, Austria, Finland and Sweden (1995). Meanwhile, a common currency was adopted as of January 1999 by eleven of the EU members and will be physically introduced in January 2002.

In this way the Community membership has grown to fifteen, with the promise of further enlargement, up to a 24 member EU, towards Central and Eastern Europe in the coming years. Figure 1 shows the genesis of the European Union: the different countries that compose the EU and the moment of their entry.

Figure 1 Genesis of the European Union

Integration among neighbours

Letting apart concerns about monetary policy or others, this economic integration based on free movements of capital (achieved in 1994 when Greece removed its restrictions), labour, goods and services, was a relationship between neighbours. In fact the average distance between the six founder countries capitals was slightly over 500 miles, something like between New York and Detroit. Therefore, distance must have been a factor in the choreography of the integration and to take into account this fact helps to understand the unfolding of the enlargement process of the EU. Table 1 shows the distance between European capitals in the different stages of the integration process. It can be seen that the average distance between Community capitals has constantly increased with time, more than doubling since 1958.

Closeness has been a clear characteristic of this process at its beginning and, together with economic policies, based on massive liberalisation, has promoted trade among members of the Community. Consequently, exporters of the successive member countries found themselves with, among others, a new opportunity: higher accessibility to close and larger markets. To examine how distance has played a role in the integration process we have calculated the probability to belong to the EU depending of distance for the periods in which there has been accession of new countries in the Community. We have regressed an artificial variable that takes the value 1 if any two countries of the present EU belonged to the EU at that time and 0 otherwise against the logarithm of the distance between these two countries’ capitals, for all possible country couples of the present EU at different years. The results are reported in table 2.

Distance is statistically significant and the results show that, for a given year, the higher the distance with respect the Community countries, the lower the probability for a given country to belong to the EU. It is no wonder then that close neighbours founded the EEC. The results in Table 2 also show that the coefficient of the distance variable decreases in absolute value and significativeness with time. Obviously, with time, farther countries access to the Community and, above all, less and less countries remain out of the club. That is so in general except for the equation for 1973, in which the absolute value of the distance variable coefficient is higher. We take this as an illustration of the fact that that the “British anomaly” was at last corrected. Indeed, the UK, due to its proximity to the core of the EEC was a natural candidate to be part of the founding countries.

3. Trade flows in the EU

Whether EU promotes interdependent growth and, if so, what have been the mechanisms for it, depends on a combination of political and economic variables. The EU in its origins was a free trade area. In fact, trade has been one of the oldest and deepest linkages among EU countries in the sense that it was a main economic objective and many economic policies promoted it. Therefore, there can be a relation between flows of trade and integration. As it was pointed out in the previous section, trade liberalisation in the EU countries, based on the removal of physical, fiscal and technical barriers to trade, creates profit opportunities for exporting firms within the EU. There are more incentives to trade between Community countries due to the lifting of quotas and the reduction in costs due both to the elimination of tariffs and the harmonisation and simplification of different technical standards, industrial regulations, administrative formalities, etc. Consequently, integration affects relative competitiveness and the profitability of the EU firms.

Changes in the incentives to trade can be documented through data on bilateral trade from IMF’s Directions of trade. Table 3 shows data on trade openness of the EU countries through time. It is reported the differential between the openness ratio that each of the EU countries has with the other thirteen EU countries (Belgium and Luxembourg have been added all through this paper) minus its openness ratio with the rest of the world. The openness ratio is computed as imports plus exports over a country’s GDP. Export and import data come form the OECD. The bigger this differential, the more oriented the country towards the EU rather than towards the rest of the world. What we see is a growing trend, despite cyclical influences, towards more trade within the present EU group of countries than with the rest of the world, since the early seventies. Certain country cases deserve explanations.

As said, a positive differential indicates the relative importance for any country of trade with the EU, with respect to trade with the rest of the world. For most of the countries this differential is positive and especially large for Belgium+Luxembourg and the Netherlands -the founding Benelux countries. This shows the well known fact that EU countries trade more among themselves than with the rest of the world. The differential is increasing for most of the period for Spain, France, Greece and Portugal, while, in the UK, the accession to the EU soon diminished the gap in favour of the rest of the world.

In fact as it is shown in figures 2 to 5, the openness rate of the Iberian countries and Greece have switched dramatically with their entry in the EU while the UK has closed the gap previously existing. This is an indication that for these countries the EU has created an incentive to change their trade patterns increasing their trade with countries belonging to the Community.

Countries such as Austria, Germany, Ireland, Denmark and Sweden also maintain higher openness rates with the EU than with the rest of the world. Finland and Italy share the same feature except for periods between 82-84 and 82-86 respectively, when the openness rate with the rest of the world is higher than the EU openness rate. The United Kingdom, although having the lowest differentials, has approximated its openness rates since the beginning of the eighties.

Figure 2 Trade openness in Spain

Figure 3 Trade openness in Portugal

Nevertheless, there is a problem with distinguishing between the present EU and the rest of the world. One is not taking into account that most of the EU countries had different trade agreements between them prior to their accession to the EU (that is the case of the EFTA countries or the above mentioned case of Spain). To get a clearer view about how the EU has promoted trade flows between its members we need a more detailed analysis. In order to do that we compute trade flow intensities between the EU countries as the flows between any two countries i and j, relative to total flows of these countries with the EU. Defining as exports of i to j (or imports of j from i), a trade flow intensity measure currently used is just:

\[\text {Trade flows intensity} = \frac {1}{4} \frac {\ddot {x} _ {i , j}}{\ddot {x} _ {i , E U}} + \frac {\ddot {x} _ {j , i}}{\ddot {x} _ {j , E U}} + \frac {\ddot {x} _ {j , i}}{\ddot {x} _ {E U , i}} + \frac {\ddot {x} _ {i , j}}{\ddot {x} _ {E U , j}}\]

Table 4 below and Tables A1, A2 and A3 of the appendix show trade flow intensities for different periods for EU countries.

After these data we can see who are the main EU trade partners of each of the present EU countries on average between 1970-1997 as shown in Table 5. This table reflects the huge weight of Germany in the EU economy for it figures regularly among the three main trade partners with the rest of the EU countries. The other main partners, as we will see latter, are highly dependent on distance between them and any other country. As one can expect distance, among other factors, plays a role in trade relationships and there is no wonder that, for instance, the couples Austria-Germany, Ireland-United Kingdom, show strong trade interdependece. Table 6 shows the main changes in trade flow intensities in the last thirty years. Looking at the pattern in Table 6 some features can be pointed out.

For founder countries (EUR-6), in general, trade flows intensities between them decrease or remain stable; that is the case of Germany and Belgium-Luxembourg (from 22% to 20%), Germany and France (from 30% to 23%), Germany and the Netherlands (from 30% to 24%), Belgium-Luxembourg and France (from 22% to 18%), Belgium-Luxembourg and the Netherlands (from 22% to 19%). As for non EU-6 countries, flow intensities increase: Germany and Austria (from 28% to 33%), Germany and Denmark (from 13% to 18%), Germany and Ireland (from 3% to 7%), Germany and the United Kingdom (from 11.4% to 19%), Belgium-Luxembourg and the United Kingdom (from 7% to 11%), France and the United Kingdom (from 9.5% to 15%), France and Spain (from 12% to 19%), Italy and Greece (from 9% to 14%), Italy and Spain (from 6.5% to 11%). These data indicate two features: a proportional increase of trade with the United Kingdom since the entry of this country in the Community and a more than proportional trade increase between countries that being close were not in EU-6 (Germany and Austria, France and Spain, Italy and Greece).

As for the United Kingdom, Denmark and Ireland, all joiners in 1973, the first two countries belonged to EFTA7. Therefore they had a particular trade agreement before their entry in the Community. With their accession to the EU their trade flows intensities have decreased (from 16.5% to 7%), increasing mainly those with Germany and France. Ireland has increased its trade flows intensities about one point with almost each country of the Community except with the United Kingdom with which it has considerably decreased its relative flows (from 44% to 27%). All these countries have clearly diversified their trade patterns since their entry in the EU.

The two Iberian countries trade considerably more between themselves since their accession to the EU in 1986 (from 4.5% to 15%). Their case clearly shows that distance cannot be the only determinant of trade. At the same time, Portugal and the United Kingdom reduce their trade intensities (from 16% to 6%), a clear EFTA issue. This case is illustrative in the sense that there is a switch in the trade partners. There are also important increases in trade flow intensities between Spain and France (from 12% to 19%) and Spain and Italy (from 6% to 11%) for almost each period since the seventies and between Greece and Italy (from 9% to 14%) since the Greece entry in the Community. Again, the same characteristic appears: there is more trade between countries that are close, provided genuine integration occurs. Figure 6 shows the evolution of trade intensities for Southern European countries.

Figure 6 Trade flows intensity among some Southern EU countries

In what refers to Austria, Finland and Sweden, these three countries have decreased their trade flow intensities with the United Kingdom (Austria from 7% to 3%, Finland from 14.5% to 9% and Sweden from 16% to 9%) and have increased them with the rest of the EU countries, in particular with those of the founding core of the EU.

From those data it can be confirmed that the EU has promoted trade between its members, changing the incentives to trade. This is specially reflected in the case of close countries that, with the exceptions of Ireland and the United Kingdom, have increased their trade flows intensities considerably as in the cases of neighbouring Austria-Germany, France-Spain, Spain-Portugal, etc.

The relationship between trade and closeness is illustrated in Figures 7 and 8, where it is clear that the relationship between intensities of flows and distance among EU countries is negative and non-linear as a standard gravity equation estimated below also confirms.

Figure 7 Intensity of trade and distance in 1970

Figure 8 Intensity of trade and distance in 1997

Estimating a standard gravity equation for the present EU countries (1970 to 1997), one obtains that, as expected, the flows of trade depend positively on country size (GDP) and negatively on distance, what is shown in Table 7. Moreover, the distance coefficient diminishes with time, that is reported in Table A4 in the appendix, indicating that technological and logistic innovations are actually reducing relative transport costs.

In general thus, EU countries have increased their trade and have rearranged their patterns of trade in the sense that they have relatively increased trade flows with their new EU partners and in particular with nearer ones. Additional reduction in transportation costs may have reinforced trade links even more, despite distances, but the above arguments suggest that distance seems easier to overcome via integration arrangements than through technological or organisational advances. From this perspective it is understandable that the economic relationships between the EU countries have become more interrelated due among other factors to the increase in trade among them. Has this had any influence on growth patterns in the EU?

4. Interdependence in a standard growth equation.

A convenient, if somewhat oversimplified, vehicle to illustrate the phenomenon of interdependent growth is the standard growth model. This model states that output in country i, , obeys the following law:

\[Y _ {i} = A _ {i} K _ {i} ^ {\alpha} L _ {i} ^ {\beta}\tag{1}\]

where and are capital and labour in country i. Interdependence can be modelled as:

\[A _ {i} = \eta_ {i} \prod_ {j = 1} ^ {J} Y _ {j} ^ {\omega_ {j}}; \text { with } i \neq j\tag{2}\]

where , besides technology for country i, represented by , captures a “thick markets” externality, , that emerges as markets expand, that is an externality due to the fact that markets are larger and more densely populated by firms and consumers and display a larger variety of goods and services. This is also related to how markets increase and thicken as countries get more interrelated.

The externality set-up assumed in (2) has been proposed by Bertola (1992) where interdependence is established through private capital. It is also retaken in Goicolea et al. (1998) where output in other countries replaces capital as the channel through which externalities flow. There are basically two reasons for considering such specification. First, it makes explicit how relationships among countries generate a pattern of interdependent growth. Second, it permits the application of spatial econometric techniques to a specification based on a theoretical model.

Spatial econometric techniques (Anselin, 1988), permit to study crosssection data with multidependent relations in the space. This spatial dependence can be caused by measurement problems or because there exits complex dependence and interrelations in the studied phenomena based on “physical transfer of commodities, people or information”, “background geography” or “relates to more volatile levels of spatial regularity”, as stated in Haining (1986).

From (1), taking log derivatives, the following equation can be obtained:

\[g _ {t} = a _ {t} + \alpha k _ {t} + \beta l _ {t} + \varepsilon_ {t}\tag{3}\]

where represents the random term.

To focus the analyses in the interdependent growth relationship it is considered the simplest case in which capital, labour and the technology are disregarded and treated as a constant term, and is replaced according to expression (2) yielding:

\[g _ {i t} = c + \rho \sum_ {j = 1} ^ {J} \omega_ {i j t} g _ {j t} + \varepsilon_ {i t}\tag{4}\]

where is the coefficient of the “spatially lagged” dependent variable that measures the degree of interrelation between rates of growth of any one country with its partners: growth in one country affects growth in any other country to an extent given by existing relationships between both, (trade, distance, etc). For all EU countries and years, equation (4) takes the following general specification:

\[g = c + \rho W g + \varepsilon\tag{5}\]

where is a 392 elements column vector of GDP growth rates for the EU member states from years 1970 through 1997 organised as follows:

\[g = \left[ \begin{array}{c} g _ {7 0} \\ \vdots \\ g _ {9 7} \end{array} \right] \quad \text {with} g _ {t} = \left[ \begin{array}{c} g _ {1 t} \\ \vdots \\ g _ {1 4 t} \end{array} \right]\]

is a constant term and is a weights matrix organised as follows:

\[W = \left[ \begin{array}{c c c c} W _ {7 0} & 0 & \vdots & 0 \\ 0 & W _ {7 1} & \vdots & 0 \\ \vdots & \vdots & \ddots & \vdots \\ 0 & 0 & \vdots & W _ {9 7} \end{array} \right]\]

where each is a 14x14 matrix of bilateral trade flows for that particular year whose elements are defined as follows:

\[\omega_ {i j t} = \left\{ \begin{array}{l l} \frac {x _ {i j t}}{\sum_ {j = 1} ^ {1 4} x _ {i j t}} & \text { if } i \neq j \\ 0 & \text { if } i = j \end{array} \right.\]

where are exports from country i to country j. Note that the weights have been normalised in order to avoid biases due to the absolute size of trade flows or variation of their measurement units across time.

The arrangement of the W matrix implies that only contemporary spatial dependence is assumed or, in words, only trade relationships in a given year carry the influence of growth in a given country that year to any other country but the dependence among different years (elements out of the main diagonal) is null.

5. Estimation of interdependent growth among EU countries.

A first step is to test whether there is spatial dependence for the data of trade and growth. This can be tested using the Moran scatterplot (Vayá et al, 2000) (figure 10). In this graph the dependent variable, is plotted in the axis whereas the explanatory variable, , is plotted in the y’s axis. One can determine whether there is spatial dependence in the data and what its structure is as follows. If the observations are dispersed in the four quadrants, there is not spatial dependence. On the contrary, if the set of points lies mainly in upperright and lower-left regions this indicates that there is a positive spatial correlation.

From Figure 10 one can observe that there is indeed positive spatial correlation. Consequently the next step is the estimation of the interdependent growth equation (5). This is done using maximum likelihood because the errors in (5) are not independent and therefore estimation by ordinary least squares would be inconsistent. The results of the estimation are reported in Table 7 for the whole period and for different subperiods.

Here, it is assumed that contemporary trade flows are the channel through which growth patterns are connected among countries. The results in Table 7 show that there are positive externalities transmitted through trade because the parameter is significant. Indeed, these results provide a measurement of a trade externality that implies interdependent growth. That is, for instance, if every trade partner of a given country experiences an extra growth of 1 percentage point, this country’s economy will grow an extra 0.75 point as implied by the value of in the first column of Table 7. The same applies for recessions unless countries defend themselves against that.

Figure 11 graphs the evolution of the trade spillover through time. The size of the externality seems to fall with time what indicates that there are less mutual growth influences due to trade relationships. Even if this trade externality remains high and significant, since the eighties, other channels may be growing in importance as for the relationship between integration and interdependent growth.

Consider now the same model to which the income level of the country has been added in order to control for convergence issues. Let be the logarithm of per capita GDP lagged one year. Equation (5) can then be rewritten as:

\[g = c + \rho W g + \beta y _ {- 1} + \varepsilon\tag{6}\]

Equation (6) is also a convergence equation. One would expect that the parameter has a negative sign indicating that, other things being equal, richer countries grow less than poorer ones.

The results of the estimation are reported in Table 8. The sign of the convergence parameter indicates that countries with a lower initial per capita GDP are growing faster than richer countries. Note that the values of the trade spillover are only slightly smaller than those of Table 7 and significative. The growth spillover thus remains substantial in this estimation again indicating that trade enhances interdependent growth although in a decreasing fashion across time.

6. Conclusion

This paper has shown that an integration process like the one followed by the EU can promote interdependent growth for the countries participating in it through its effect on trade. Although we have not shown that integration (through trade) has increased growth in the EU, our results indicate that deeper integration between countries leads to larger trade exchanges and to more interdependent growth patterns among them. As long as trade promotes growth, integration also promotes mutual growth.

The simple growth model presented in the paper captures the idea that integration and trade benefit the participating economies because the market at the reach of their firms increases. However, it has not been explained why trade causes growth. The impact of trade on technical progress and accumulation of factors and, by extension, how the EU process has affected these factors should be in the root of the explanation.

Furthermore, whereas this paper has focused only on trade as the element that makes economies interdependent, the analysis of other aspects that are becoming increasingly important in the EU such as financial integration, the Euro or EU-wide policies can provide a deeper understanding about the linkages between integration and growth. However, even if these other factors can promote interdependent growth among EU countries, trade seems to remain a primary factor for this.

Appendix

References

1. Aghion, P. and P. Howitt (1998), Endogenous growth theory M.I.T. Press.
2. Anselin, Luc (1988), Spatial Econometrics: Methods and Models. Kluwer Academic Publishers.
3. Baldwin, R. (1993), “On the measurement of dynamic effects of integration,” Empirica 20.
4. Bertola, G. (1992), “Models of economic integration and localized growth,” Discussion Paper 651 CEPR.
5. Branstetter, L. (1996), “Are knowledge spillovers national or international in scope?. Microeconomic evidence from the U.S. and Japan,” NBER Working Paper 5800.
6. Coe, D. and Helpman, E. (1993), “International R&D spillovers,” NBER Working paper 4444.
7. Frankel, J.A. and D. Romer (1996), “Trade and growth: An empirical investigation,” NBER Working Paper 5476.
8. Goicolea, A., J. A. Herce and J. J. de Lucio (1998), “Regional integration and growth: The Spanish case,” FEDEA D. T. 98-14.
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11. Haining, R. (1986), “Income diffusion and regional economics,” in Transformations through space and time edited by Griffith and Haining Dordrecht: Martinus Nijhoff.
12. Helpman, E. and P. Krugman (1985), Market structure and foreign trade. Cambridge. M.I.T. Press.
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