Effects of European Integration on the Location of Production : A Simulation Exercise

Transcription

1 Effects of European Integration on the Location of Production : A Simulation Exercise Rikard Forslid Jan I. Haaland Karen Helene Midelfart Knarvik May VERY PRELIMINARY PLEASE DO NOT QUOTE - Abstract This paper uses a full blown CGE-model - calibrated on real 992 data - to investigate the effect of European integration on the location of industrial production. Department of Economics, Lund University, P.O. Box 782, S-22 7 Lund, Sweden. Phone: , fax: , rikard.forslid@nek.lu.se Centre for International Economics and Shipping, Norwegian School of Economics and Business Administration, Helleveien 3, 545 Bergen, Norway. Phone: ; fax: , jan.haaland@nhh.no Centre for International Economics and Shipping, Norwegian School of Economics and Business Administration, Helleveien 3, 545 Bergen, Norway. Phone: ; ; fax: ; karenhelene.knarvik@snf.no

2 . Introduction A common worry among politicians of peripheral regions in the EU is that the European economic integration will lead to loss of industry and jobs in their regions. These worries are underscored by a series of recent theoretical articles (e.g. Krugman (99) and Krugman and Venables (995)), that suggest that economic integration may indeed lead to increased concentration of industrial production and increasing international inequalities. The tendency for industrial concentration arises because of self-reinforcing backwardand forward-linkages. In Krugman and Venables (995) these stem from a combination of increasing returns to scale, trade costs, and the fact that firms are linked via their input-output matrices. Downstream firms use a CES-aggregate of upstream varieties as an intermediate input. When trade across borders incur costs - a larger number of up-stream firms in your region implies a lower price index of intermediate inputs. This mechanism constitutes the forward link. More downstream firms, however, also implies a larger home market for upstream firms, which increases their sales and profits. This is the backward link. Against these agglomeration forces, trade costs is a force that makes it less attractive to serve markets via exports. Higher trade costs, therefore, work in the direction of less concentration. It may be noted that low trade costs implies weak agglomeration forces as well as a weak dispersion force. Any dispersion force that is independent of trade costs will therefore tend to dominate for low trade costs. With such a dispersion force present agglomeration will display a U- shaped pattern with agglomeration of economic activity for intermediate trade costs and dispersion for high and low trade costs. Examples of such forces are, decreasing returns in some homogenous sector (Venables, 996), comparative advantage (Forslid and Wooton, 998, Fujita et al, 999), congestion (see e.g. Ottaviano and Puga, 998) <SJEKK DENNE!!> The theoretical studies, however, make their argument in highly stylised models normally a 2x2x2 framework - which is necessary because of the complexity of the imperfect competition framework. In this paper we simulate the effects of economic integration in Europe using a full-blown CGE-model - the EURORA model (Forslid at al, 999) which is

3 calibrated on actual 992 data. We report the effects of European economic integration on individual sectors as well as the effect on the overall level of industrial concentration in Europe. Dual to this, we look at how regional specialization is affected, and discuss the importance of increasing returns industries and pecuniary externalities for regional income. 2. Model Description and Data Sources The model has 4 sectors with various forms of competition, 4 Western European regions, and 6 regions constituting the rest of the world. Table describes the regions of interest to this paper. Table : European Regions Regions Description Europe Central Austria, Denmark, Germany, Switzerland (EuropeC) Europe North Finland, Iceland, Norway, Sweden (EuropeN) Europe South Greece, Italy, Portugal, Spain (EuropeS) Europe West BeNeLux, Ireland, France, UK (EuropeW) Sectors are linked via demand for intermediate inputs, which creates agglomeration forces a la Venables (996) and Krugman and Venables (995). In the simulation model there are both intra- and inter-industry linkages creating agglomeration forces not only within sectors but also between different kinds of economic activity. To calibrate the model we use actual inputoutput tables from Eurostat and GTAP and the NBER World Trade Flows from 992. The model we use is related to the CGE model developed by Haaland and Norman (99), but with significant modifications with respect to linkage structure, different types of trade costs and market structure. An important new feature of this paper is that the model has a complete input-output structure in the sense that all linkages across the different 4 sectors in the model are taken into account and are modelled in detail. Region specific input-output matrixes are used. The 4 sectors represent 2 perfectly competitive sectors, and 2 An exception is Puga and Venables (996), that use a framework of multiple sectors with

4 imperfectly competitive sectors, out of which two are non traded service sectors while the other are traded manufacturing sectors. Three different types of trade costs are considered: transport costs, tariffs and export tax. The basic industrial structure of the model is shown in Table 2. Table 2: Industries Industry NT: PubServ, Priv Serv. PC: Agriculture, Energy ITG: Textiles, Leather and Products, Wood Products, Metals, Minerals, Chemicals, Food Products, Transport Equipment, Machinery, Other Manufacturing Description Non-traded monopolistically competitive sector linked to the input-output structure of all other imperfectly competitive sectors Traded perfect competition sectors without trade costs. Each sector has a specific factor which creates an element of decreasing returns to scale. Traded sectors with monopolistic competition. Trade distortions of iceberg type. Linked to the input-output structure of all other imperfectly competitive sectors 2. Basic model equations Consumers have Cobb-Douglas preferences over a set of AG goods, from which follows that they will spend a fixed share of the income on each of the AG goods: C im α Y im = im AG Pim i (.) For perfectly competitive goods prices are world market prices and given by world market clearing for the respective goods. One of these goods is chosen as numeraire. As for imperfectly competitive goods, the price level for each of these is an aggregate of the price of each variety of the good i produced in region j, weighted by the number of producing firms in each region j and by a national and industry specific parameter a m, which represents a national demand bias. For non traded differentiated goods a m = for all m j, since one is only assumed to consume domestically produced varieties. P im R = N j= a m PI ( σ ) m i σ i i I, a m = m j for i NT (2.) inter-sectoral input-output linkages.

5 The imperfectly competitive sectors are characterised by monopolistic competition á la Dixit and Stiglitz (977). Producer prices on differentiated goods are given by a mark up over firms marginal costs: PPI σ i = M C ITG σi i (3.) consumer prices, however, are subject to trade costs. These are of three types: Export taxes, transport costs, and tariffs. m ( + EXTAX ) ( + TRANS ) ( TAREG ) PI = PPI + i ITG (4.) m Transport costs are of iceberg-type while taxes and tariffs are lump-sum transfers to the representative consumer. Demand for each variety of the good i may now be derived, and is given by: m m X m a P σ i C im = m im ITG PI m i (5.) Prices and demand for non traded differentiated goods are derived in the same way as for traded goods, but we don t need to distinguish between producer and consumer prices since there is only domestic consumption of these goods. The price index for differentiated intermediate goods is industry specific by purchasing industry. The price aggregates for the individual i goods are weighted by the parameter g ihm, which denotes the input use of good i in the production of the purchasing industry h. The parameter sq denotes the elasticity of substitution among imperfectly competitive goods used as intermediates. Q hm sq I ( sq) = g ihm Pim h AG (6.) i= The price indices for perfectly competitive goods as intermediates are constructed in the same way. QPC hm sq PC ( sq) = g ihm PPCi h AG (7.) i PC

6 PV is a price aggregate for all primary factors used in the production in sector i in region j. The use of each individual factor is industry and country specific and given by the parameter β. si K s i PV = βk Wjk i AG (8.) k= Finally, the marginal cost is a sum of index for primary inputs, differentiated intermediates, and homogenous intermediates, where S top denotes the elasticity of substitution between the indices. M Stop S S i top top [ ( ) ( ) i S BV PV + BZ Q + BZPC ( QPC ) i ] top i C = (9.) The use of intermediates from own as well as other industries, implies the existence of interand intra-industry cost linkages. The presence of these linkages, together with trade costs, means that firms costs are affected by the number of other firms producing in the region, i.e. they generate pecuniary externalities. Firms located in a region where a relatively large share of industries from which they demand the major share of their intermediates, are located, will be relatively more competitive. Agglomeration forces do not directly affect the PC sectors. These sectors, however, expand or contract as a consequence of competition for factors with the other sectors. The decreasing returns in these sectors (due to a specific factor) act to dampen the expansion of the ITG sectors. 2.2 Data Data sources are EUROSTAT (input-output tables for Europe), GTAP and NBER World Trade Flows (see Feenstra et al, 997). A detailed description of what kind of data that have been used, and from where each type of data have been taken, can be found in Forslid et al (999). The same paper also provides a descriptive analysis of the data material, focusing on the distribution of production across regions, trade flows and trade volume, differences in technology and factor use across industries.

7 2.3 Industry and Region characteristics Here we present some key elements of interest to the present study. In particular we concentrate on aspects that are expected to influence the location of various sectors as trade costs are lowered. Four factors affect the strength of the backward- and forward-linkages in this model: trade costs, scale elasticities, input-output structure (intermediate demand bias), and the size of regions (home market effects). In addition to these agglomeration forces, location is affected by standard comparative advantage - especially for low trade costs - due to differences in endowment or technology. Finally, tariffs and export subsidies may affect location, but they are accounted for in the trade cost aggregate. Total trade costs are given by the product of the three terms in equation (4). Table A in appendix shows the full matrix for the base case, while Table 3 gives a summary. In trade liberalisation experiments we lower trade costs equiproportionate over sectors, which implies that we would expect more action in sectors with initially high trade costs. Let us therefore note that Food products, Minerals, Chemicals and Wood Products are all sectors that are characterised by relatively significant trade distortions. Table 3: Summary of trade distortions Low Unweighted High Mean Textiles Leather and Products Wood Products (-). Metals Minerals Chemicals Food Products Transport Equipment Machinery Other Manufacturing The next factor affecting agglomeration forces is scale elasticity. 2 Table 4 shows that this is highest for Metals, Transport equipment, Chemicals and Machinery industry, which all have economies of scale above average. According to the theory (see Krugman, 98; Krugman 2 Pratten (988) offers a ranking of industries according to economies of scale, that have been transformed into scale elasticities by Cawley and Davenport (988).

8 and Venables, 995; Amiti, 998) we would, ceteris paribus, expect these to agglomerate the most. Table 4: Economies of scale Industry Reduction in AC (%) with a % increase in output Textiles.6 Leather and Products.6 Wood Products.2 Metals.6 Minerals. Chemicals.24 Food Products.8 Transport Equipment.26 Machinery.2 Other Manufacturing.8 MEAN.4 The use of intermediates is also a factor determining the location of production and the degree of concentration. Industries purchase their intermediates from it s own sector as well as from other sectors. Table 5 gives a summary of key characteristics regarding the average European intermediate use. Column (a) gives use of input from own sector as share of output value; column (b) gives total use of intermediates from all sectors as share of value of output. In column (c) the dependence on own relative to other sectors inputs is shown (the difference between the diagonal input-output coefficient and the off-diagonal): if the sign is negative then linkages between industries are stronger than those within industries. Finally, column (d) gives use of public and private services which by assumption are non-traded goods as share of output. While purchases from own sector create a positive feedback and make agglomeration self-reinforcing, the use of intermediates from other sectors may work both for and against agglomeration depending on the location of the supplying sectors. A strong dependence on sectors that are rather dispersed across regions or alternatively concentrated in another region than the purchasing sector, discourage agglomeration. In general we would ceteris paribus expect industries with a strong bias towards use of inputs from own industries (high (a)), and with intra-industry linkages that are stronger than inter-industry linkages (high (c)), to be

9 relatively more concentrated geographically. 3 From Table 5 we can see that Textiles, Wood Products, Metals and Chemicals are industries with an above average use of inputs from own sector and which also have stronger within than between industry linkages. Table 5: Use of intermediates (a) Own input share (b) Intermedia te share (c) Own Rest= (a)-[(b)-(a)] (d) Service input share Textiles Leather and Products Wood Products Metals Minerals Chemicals Food Products Transport Equipment Machinery Other Manufacturing MEAN For low trade costs, agglomeration forces become weak. Instead comparative advantage forces will tend to dominate. Industries have different factor intensities, which opens up for location of production based on comparative advantage. This does however, not necessarily imply a greater geographical dispersion of production in an industry, depending on the interaction among the total set of forces determining location, comparative advantage may reinforce or discourage geographical concentration of industries. Table 6: Value added shares and factor intensity ratios Unskille d labour Skilled labour Capital Unskilled/skill ed ratio Labour/ capital ratio Textiles Leather and Products Wood Products Metals See Fujita et al (999) for a discussion of the impact of inter- versus intra-industry linkages on agglomeration.

10 Minerals Chemicals Food Products Transport Equipment Machinery Other Manufacturing MEAN European averages for value added shares and factor intensities ratios are shown in Table 6. Since the rankings of different sectors in terms of factor intensities are similar across the European regions, like in the case with intermediates use, we shall only focus on the European averages. Chemicals, Transport equipment and Machinery are skill-intensive sectors. Textiles and Leather use unskilled labour intensively. In order to say something about the importance of comparative advantage for the location of production, we need to know something about relative factor endowments across regions. We cannot, however, in our model separate factor prices and factor stocks. We therefore turn to other data sources for this purpose, and use the factor endowments provided by Maskus and Penubarti (995). These are displayed in Table 7. Table 7: Relative Factor Endowments Unskilled/Skill Labour/Capit ed labour force al stock Europe Central Europe North.69.7 Europe South Europe West MEAN It should not come as any surprise that Europe South is relatively abundant endowed with unskilled labour, while Europe North is relatively abundant endowed with skilled labour. As for capital endowment, Europe Central and Europe North are relatively more capital abundant than Europe South and Europe West. Table 8: Real GDP (base case ) Real GDP Share of

11 Europe Real GDP Europe Central % Europe North % Europe South % Europe West % SUM Europe The last key factor we want to focus on is the size of regions, since we know that home market effects may have a strong impact on the location of production. Table 8 gives real GDP for the Western European regions. While Europe West and Central are about the same size, South is around considerably smaller, while Europe North appears to be around /7 the size of the large core regions of Europe. 3. The location of production We now turn to the question of how the pattern of industrial production in Europe will change as trade impediments are dismantled within the European union. We first discuss the movement of individual manufacturing sectors in Europe resulting from trade liberalisation. Where do industries expand and where do they contract? We thereafter go on to analyse locational patterns by the use of concentration indices. We will use two types of indices. The first one - the industrial concentration index - tells us to what extent different industries tend to concentrate geographically as a consequence of economic integration. The second index is an index of regional specialisation. Finally we construct a measure of overall industrial concentration to measure whether various industries concentrate in the same region or whether a geographically dispersed production pattern is maintained. Our experiment consists of successive lowering of all three types of trade costs: transport cost, tariffs and exports tax with % per step. We, however, also show the result for a few steps of increase in trade costs. We will focus on the ITG sectors. Services are nontraded and therefore not directly affected by changes in trade costs. Agriculture and energy are modelled with perfect competition and free trade, which implies that agglomeration forces are absent. Agriculture and energy can in effect be viewed as residuals to the other sectors.

12 3. Changing patterns of production We shall here only try to describe the simulated production patterns, while leaving further analysis to the next sections. Figure shows how production in different sectors changes as trade costs are lowered. The horizontal axis depicts trade costs in relation to the base case. (e.g..5 means half of base case trade costs). {Figure about here} Four sectors Textiles, Leather, Wood Products, and Food Products show the most dramatic patterns in terms of changing locations. Textiles moves out of Europe Central and into Europe West and Europe South. Leather expands in Europe South, while contracting in all other regions. Wood Products leave Europe North and increase in Europe Central and West. Food production leaves South and Central, moves into North but particularly into Europe West. Consider first textiles. This sector displays a locational pattern that looks very much like a bifurcation, where for very low trade costs production abruptly disappears from central Europe and agglomerates in Europe West and Europe South. The possibility of abrupt changes in location as trade costs are lowered is well known from theory (e.g. Krugman 99). The reason why textiles expand so substantially in Europe South seems rather clear: Textiles is one of the most unskilled labour intensive industries, and Europe South has a comparative advantage in the production of unskilled labour intensive goods. But why is it that production moves out of Europe Central and into Europe West and not vice versa? Factor endowments can not explain this change in production patterns. Still, for a true bifurcation an infinitesimal difference will suffice to tip the balance in favour of one location. In our case Europe-West does have a slightly larger production than Europe Central initially. Table 5 moreover shows that within industry linkages are relatively strong in textile production, which implies that self-reinforcing forces of agglomeration are likely to be important for the location of production textiles and probably explains the observed patterns.

13 The leather industry exhibits a locational pattern similar to textiles, where low trade costs lead to a core periphery outcome. The difference is that relocation of production is more continuos and that agglomeration only takes place in one region: Europe South. The leather sector s characteristics are similar to textiles. However, at the base case the leather production of Europe South is more than twice as large as in any other region, which together with South s Comparative advantage in unskilled intensive production, probably are the main explanations for the resulting agglomeration in this region. Moreover the leather industry is small compared to other sectors, which implies that large swings in this sector can occur without causing much pressure in the factor market. The Wood Products industry is a particular case. The big action here is the loss of production in Europe North and a corresponding gain in the other regions. The driving force behind this result is most certainly the 5% export subsidy in Europe North, which is dismantled as all trade distortions are lowered. The large swings in production of Food products is understandable given this industry s initially high trade costs. (c.f. Table 3) One surprise, perhaps, is that this industry starts to agglomerate in Europe North for low trade costs, even though this region initially has production that is only one third or less of the other s production volume. The explanation for this seems to be that Food Products is a relatively capital intensive industry, which gives Europe North a comparative advantage. Food Products are also characterised by rather low increasing returns to scale, which ceteris paribus makes proximity to a large market less important for its location, and further justify the movement into the Northern periphery of Europe. What about the remaining ITG industries? These industries exhibit rather stable patters of localisation. Among these industries are the four sectors with the most significant increasing returns to scale technology: Metals, Chemicals, Transport equipment and Machinery. In the base case they are all rather concentrated in the two largest regions: Europe Central and Europe West. Substantial increasing returns to scale and the presence of intraindustry linkages suggest that proximity to markets and self-reinforcing agglomeration forces

14 are important determinants of the location of production in these industries. This is probably an explanation why these sectors remain concentrated in the core of Europe when trade costs are reduced. A more detailed discussion of the differences between the four sectors with respect to location and technology will be provided in the proceeding section. To conclude this section, it does seem that comparative advantage is an important element in determining the location of several industries in particular when trade costs become low. So far we have investigated the location of different industrial sectors as Europe integrate. It is, however, also interesting to investigate what happen to industrial concentration on a more general level. Will overall European manufacturing become more or less concentrated as a consequence of lower trade costs? Will production of individual industries agglomerate, and will they in that case agglomerate in the same region? One way to analyse questions like these is to use summary indices of concentration a task we will turn to in this section Industrial Concentration We shall use a measure for absolute industrial concentration of the following form 4, i 2 [ ( s s ) / N] s C = / j with s = X / X being the share of production in industry i that takes place in region j, j and with N depicting the number of regions (4) in Europe. The index of absolute concentration C i is the coefficient of variation of the distribution of s. A high value of this statistic indicates a highly concentrated industry. Figure 2 illustrates how increased integration affects the degree of concentration of the respective ITG industries. {Figure 2 about here}

15 Consider first Metals, Chemicals, Transport Equipment and Machinery - a group of industries where concentration displays a - shaped curve as regions are integrated. These industries all have high scale elasticities (c.f. Table 4), which indicates strong agglomeration forces. When trade costs are reduced from a high level concentration initially increases. However, lower trade costs also decreases the agglomeration forces so that, when a critical level of trade costs is reached, the process is reversed as other forces such as comparative advantage starts to dominate. Further reductions in trade costs therefore imply that production starts to become increasingly dispersed across the European regions. We would expect these industries of high economies of scale to concentrate in large markets. It therefore comes as no surprise, that initially they are all rather concentrated in the large core regions in Europe: Europe Central and West. Metals and Chemicals moreover exhibit relatively strong intra-industry linkages. Even though the movement in concentration that we observe are modest, we see a clear pattern: When trade costs are reduced, agglomeration is first reinforced, which confirms the forces for agglomeration are strongest for intermediate levels of trade costs. This development is then proceeded by declining concentration. Further integration and reduced trade costs seems to move us in one clear direction: industrial dispersion. The second group of industries becomes increasingly concentrated when integration proceeds and allows for reduced trade costs. The industries where lower trade costs imply agglomeration, are exactly the same industries as the ones that exhibit the most dramatic changes in location patterns: Textiles, Leather, Wood Products and Food Products. As argued in the previous section comparative advantage is a dominating factor for Textiles and Leather, while high subsidies and trade costs is an important explanation for the large movements of the other two sectors. 4 The differing size of the units (the regions) makes relative indices a less attractive choice as a measure of industrial concentration. See Haaland et al, 999 and Midelfart-Knarvik et al, 999 for discussion of the use of relative and absolute measures of concentration.

16 This non-monotonic relationship between economic integration and industrial concentration is borne out in several theoretical models. An issue of great political interest in Europe in this context is where on the curve we are. That is: Will further integration increase or decrease concentration. These simulations give a tentative answer. It seems that European industry with high economies of scale is close to the peak in terms of concentration, while smaller industries where location is determined by comparative advantage may continue to concentrate as integration proceeds. We next turn to the issue of regional specialisation. 3.3 Regional Specialization Regional specialization is measured similarly to industrial concentration using with r = ( X X ) ( X / X ) j i j 2 [ ( r r ) / M ] r R = / i /. r is location j s share of production in industry i j i relative to the location s share of total production in Europe including services as well as manufacturing. A low index implies that regions have a share of each industry in proportion to their overall size which indicates a low degree of specialisation. A high index, on the contrary, means a high degree of regional specialisation. { Figure 3 about here} Figure 3 reveals a different pattern among regions. Europe North displays a U-curve, and further integration will slightly decrease specialisation until very low trade costs are reached. The other regions display and increasing degree of specialisation, with Europe South showing a degree of specialization that goes far beyond any of the other regions. This is mainly explained by expanding Textile and Leather Industries and a decline in Food products. Europe Central s increase in specialization is due to a loss of Textiles and Food Products, while Agriculture and Energy sectors expand. The North loses Textiles, Agriculture and Energy, but expands it Food Production; a Pattern that also very much resembles the one found in Europe West with the major difference being that here Textiles actually expands. What is worth noting is that in both the latter regions the perfect competition industries contract.

17 Having analysed regional specialisation and industrial concentration a natural question is whether industries will concentrate in the same region or whether they will concentrate in different regions. We turn to this question next. 3.4 Overall Concentration We will measure the degree of overall industrial concentration by the following index: i 2 [ ( h h ) / N] h H = / j with h = X / X being the share of manufacturing production that takes place in i j i region j, and with N depicting the number of regions (4) in Europe. {Figure 4 about here} Figure 4 shows that overall concentration of ITG industry in Europe. Theory tells us that agglomeration forces will tend to dominate for intermediate trade costs, while dispersion forces may dominate for high and low trade costs. The question is only what intermediate means in reality. Figure 4 gives a tentative answer to this question. The figure shows that Europe is fairly close to the peak of concentration, but that significant liberalisation is necessary before any signs of increased dispersion will show up. 4. Welfare Finally, it is interesting to see the link that exists between the presence of ITG industries and a region s real income (GDP). ITG industries allows for pecuniary externalities to be generated, and from the theory we knows that the movement of such industries may imply a rent ( externality ) shifting across region. {Figure 5 about here}

18 Figure 5 reveals the close link that seems to exist between a region s specialisation in ITG manufacturing industries and real income. They illustrate well the importance of attaining an equal distribution of these industries across Europe in order to decrease regional and national inequalities. 5. Conclusions

19 Figure : Production Textiles EUROPEC EUROPEN EUROPES EUROPEW Leather Products EUROPEC EUROPEN EUROPES EUROPEW Wood Products EUROPEC EUROPEN EUROPES EUROPEW Metals EUROPEC EUROPEN EUROPES EUROPEW Minerals EUROPEC EUROPEN EUROPES EUROPEW Chemicals EUROPEC EUROPEN EUROPES EUROPEW Food Products EUROPEC EUROPEN EUROPES EUROPEW Transport Equipment EUROPEC EUROPEN EUROPES EUROPEW Machinery EUROPEC EUROPEN EUROPES EUROPEW

20 Other Manufacturing EUROPEC EUROPEN EUROPES EUROPEW

21 Figure continues Agriculture EUROPEC EUROPEN EUROPES EUROPEW Energy Goods EUROPEC EUROPEN EUROPES EUROPEW

22 Figure 2: Industrial Concentration Textiles Chemicals Ci Leather Products Ci Ci Food Products Ci Wood Products Transport Equipment Ci.4 Ci Metals Machinery Ci.4 Ci Minerals Other Manufacturing Ci.3 Ci

23 Figure 3 Regional Specialisation REGIONAL SPECIALIZATION,8,7,6,5 Rj(all),4,3 EUROPEC EUROPEN EUROPES EUROPEW,2,,2,3,4,5,6,7,8,9,,2,3

24

25 Figure 4 Overall industrial concentration ITG Industries Ci ITG

26 Figure 5: Real GDP and ITG share Europe Central Real GDP ITG share Europe North Real GDP ITG share

27 Europe South Real GDP ITG share Europe West Real GDP ITG share

28 5

29 References Cawley and Davenport (988) Feenstra, Robert C. (997): World Tradeflows, , with Production and Tariff Data, NBER Working Paper No. 59 Forslid, Rikard and Ian Wooton (998): Fujita, Masahisa, Paul R. Krugman and Anthony J. Venables (999): Haaland, Jan I. and Victor D. Norman Krugman, Paul (99a): Increasing Returns and Economic Geography, Journal of Political Economy 99(3), Krugman, Paul (99b): Geography and Trade, Cambridge, MA: MIT Press. Krugman, Paul and Anthony Venables (995): Globalization and the Inequality of Nations, Quarterly Journal of Economics CX(4), Ludema, Rodney D. and Ian Wooton (997): Regional Integration, Trade and Migration: Are Demand Linkages Relevant in Europe?, CEPR Discussion Paper No Ludema, Rodney D. and Ian Wooton (998): Economic Geography and the Fiscal Effects of Regional Integration, CEPR Discussion Paper No. 822 Maskus, Keith E: and Mohan Penubarti (995): How Trade Related are Intellectual Prpoerty Rights?, Journal of International Economics 39, Pratten, Cliff (988): Puga, Diego and Anthony J. Venables (996): The Spread of Industry: Spatial Agglomeration in Economic Development, Journal of the Japanese and International Economies, Venables, Anthony J.(994): Economic Integration and Industrial Agglomeration, Economic and Social Review 26(), 7 Venables, Anthony J. (996): 6