Trade models in the European Union

Gräbner, Claudius; Tamesberger, Dennis; Heimberger, Philipp; Kapelari, Timo; Kapeller, Jakob Working Paper Trade models in the European Union ifso working paper, No. 6 Provided in Cooperation with: University of Duisburg-Essen, Institute for Socioeconomics (ifso) Suggested Citation: Gräbner, Claudius; Tamesberger, Dennis; Heimberger, Philipp; Kapelari, Timo; Kapeller, Jakob (2020) : Trade models in the European Union, ifso working paper, No. 6, University of Duisburg-Essen, Institute for Socio-Economics (ifso), Duisburg This Version is available at: https://hdl.handle.net/10419/218900 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ uni-due.de/soziooekonomie/wp ifso working paper Jan Behringer Till van Treeck 2019 no.5 The Corporate Sector and the Current Account ifso working paper Claudius Gräbner Dennis Tamesberger Philipp Heimberger Timo Kapelari Jakob Kapeller 2020 no.6 Trade Models in the European Union uni-due.de/soziooekonomie/wp 1 Trade Models in the European Union Claudius Gräbner a , Dennis Tamesberger b , Philipp Heimberger c , Timo Kapelari d , Jakob Kapeller e Abstract By studying the factors underlying differences in trade performance across European economies, this paper derives six different “trade models” for 22 EU-countries and explores their developmental and distributional dynamics. We first introduce a typology of trade models by clustering countries based on four key dimensions of trade performance: endowments, technological specialization, labour market characteristics and regulatory requirements. The resulting clusters comprise countries that base their export success on similar trade models. Our results indicate the existence of six different trade models: the ‘primary goods model’ (Latvia, Estonia), the ‘finance model’ (Luxembourg), the ‘flexible labour market model’ (UK), the ‘periphery model’ (Greece, Portugal, Spain, Italy, France), the ‘industrial workbench model’ (Slovenia, Slovakia, Poland, Hungary, Czech Republic), and the ‘high-tech model’ (Sweden, Denmark, Netherlands, Belgium, Ireland, Finland, Germany and Austria). Subsequently, we comparatively analyse the economic development and trends in inequality across these trade models. We observe a shrinking wage share and increasing personal income inequality in most of the trade models. The ‘high-tech model’ is an exceptional case, being characterised by a relatively stable economic development and an institutional setting that managed to counteract rising inequality. Keywords: Trade policy, cluster analysis, European Union, growth models, trade models. JEL classification: F 10, F 16, F43, J3, J5, K2 a Corresponding Author; Institute for Comprehensive Analysis of the Economy (ICAE), Johannes Kepler University Linz, Austria; Institute for Socio-Economics, University of Duisburg-Essen, Germany. Email: [email protected] b Department for Economic, Welfare and Social Policy, Chamber of Labour, Linz, Austria. The opinions expressed in this article are those of the author and do not necessarily reflect those of the Chamber of Labour, Email: [email protected]. c Vienna Institute for International Economic Studies, Austria; and Institute for Comprehensive Analysis of the Economy (ICAE), Johannes Kepler University Linz, Austria. d Institute for Comprehensive Analysis of the Economy (ICAE), Johannes Kepler University Linz, Austria. e Institute for Comprehensive Analysis of the Economy (ICAE), Johannes Kepler University Linz, Austria; Institute for Socio-Economics, University of Duisburg-Essen, Germany 2 1. Introduction Differences in trade performance and trade policy feature prominently in public discourse as well as in discussions about the development of different growth models in Europe. The literature argues that while most European countries experienced a decrease in domestic demand due to increasing inequality from the 1980s onwards (e.g. Stockhammer 2015; Behringer and van Treeck 2019), those with a competitive export sector were able to counteract this trend through an increase in exports, thereby following an export-led growth model (e.g. Gräbner et al. 2019a). Before the financial and economic crisis hit, countries lacking international competitiveness accumulated high levels of private (and, in few cases, public) debt, which proved unsustainable once the crisis started (e.g. Gräbner et al. 2019b). Countries with such a debt-led led growth model experienced protracted recessions with high socio-economic costs. This paper complements this stream of the growth model literature: since international trade and competitiveness play such an important part in the discussion about growth models, a closer investigation of the patterns of trade and competitiveness is warranted. The present paper supplies such an investigation by taking a closer look at the trade patterns of European countries, which we call “trade models”. To delineate distinct trade models we investigate differentials in international competitiveness, the composition of trade as well as trade policies. We also study which developmental and distributional patterns accompany the different trade models in the European Union. In the literature on growth models, typologies are a well-established instrument for analysing commonalities and differences across countries (e.g. Simonazzi et al. 2013; Gräbner et al. 2019a; Behringer and van Treeck 2019). These typologies group countries according to some fundamental similarities and can go beyond simple classifications by capturing systemic aspects of policy or institutional arrangements. Hence, such typologies are useful when it comes to developing the “big picture” of how identified regimes work (Ebbinghaus 2012). In the present case, our main interest is to highlight the different strategies countries pursue to achieve success in international competition, and to ask whether these strategies are accompanied by consistent developmental and distributional patterns. To this end we develop a typology of trade models among EU countries by applying hierarchical clustering tools to a selection of factors derived from theoretical considerations, which allow for describing different strategies of developing a trade model. We identify six different country clusters in the European Union, with each cluster representing a different trade model. The factors used for the clustering were extracted from the existing literature based on theoretical considerations, and they consist of natural endowments, technological capabilities, labour market characteristics and the regulatory environment. It also turns out that the trade models we identify are 3 accompanied by different - but within each trade model consistent - developmental and distributional patterns. The rest of this paper is structured as follows: in the next section we clarify our theoretical vantage point and delineate trade models using a hierarchical cluster analysis. In section 3, we discuss the developmental and distributional patterns that accompany different trade models. Section 4 discusses the findings and offers concluding remarks. 2. Trade models in the European Union: theoretical and empirical considerations In this section, we clarify our theoretical vantage point and introduce the concept of growth models (2.1), justify the factors we use to delineate different growth models (2.2), describe the details of the clustering approach (2.3) and present its results (2.4). 2.1. Growth models and trade: different determinants of export success Our theoretical vantage point is the literature on theories of path-dependency in economic development (Myrdal 1958; Krugman 1991). Kaldor (1980) argues that past “success breeds further success and failure begets more failure”, and this may lead “to a ‘polarisation process’ which inhibits the growth of such (manufacturing, the authors) activities in some areas and concentrates them in others.” Consequently, from a political economy perspective, economic development can be considered as a path dependent process, so that countries may be classified according to their structural characteristics (e.g. Celi et al. 2018: Iversen et al. 2016). In its simplest form, such classification 1 distinguishes between ‘core’ and ‘periphery’ countries, where the main idea is that both political and economic power are distributed strongly in favour of the core. The reasons for this asymmetry may be long-term: Ahlborn and Schweickert (2019), for example, point out, that economic systems in developing countries are still determined by their colonial heritage. An area in which such typologies have been used extensively in the more recent past is the analysis of different ‘growth models’. The growth model literature classifies countries according to their demand drivers of economic growth (e.g. Baccaro and Pontusson 2016; Hope and Soskice 2016; Regan 2017). Export-led growth refers to a strategy where exports serve as the main driver of growth: companies are substituting foreign demand for an existing lack of domestic demand; exportled economies, therefore, typically export more goods and services than they do import, and these 1 The analytical use of country typologies has a long tradition in comparative social sciences: Esping-Andersen (1990) was among the first to develop a prominent typology of welfare states, suggesting a distinction between ‘liberal’, ‘conservative’, and ‘socialdemocratic' welfare states. Typologies are also a prominent tool in the comparative analysis of economic systems. An example is the Varieties of Capitalism (VoC) approach pioneered by Crouch and Streeck (1995) and Hollingsworth and Boyer (1997), which categorises market economies as a whole rather than only with regard to their welfare state apparatus. 4 net exports coincide with net capital outflows. Debt-driven growth, on the other hand, refers to a process in which a demand for credit (in the private sector) is met by corresponding credit supply, and increasing (private sector) debt serves as the main growth driver, so that these economies are prone to experiencing (debt-fuelled) asset-price bubbles in boom times and vulnerable to suffering from sudden stops in capital inflows in bad times, as such stops will typically trigger deleveraging processes that hinder economic growth. The literature points out that developmental paths throughout the EU have been shaped by these strategies to different degrees, with export-based expansion prevailing in some countries and private debt-led models in others (e.g. Stockhammer and Wildauer 2016). This paper contributes to the literature on growth models by introducing the concept of trade models, through which we describe different strategies countries pursue to achieve success in international competition. While the growth model literature is based on the demand-drivers of growth in general, we focus on one particular aspect of aggregate demand that has received considerable attention in the literature on Europe, namely exports. We systematically account for factors that shape different strategies for achieving success in international competition and thereby affect the possibility for a country to follow an export-led growth model. To delineate different trade models we use a hierarchical clustering approach. This will show similarity of countries belonging to specific groups in terms of the factors that shape their success on international markets. Notably, our approach does not suggest an uni-causal relationship running from trade models to growth models, economic development and distribution. Rather, the causality may actually run in both directions. Therefore, our contribution is descriptive in the sense that we systemize the different trade models in the Europe and, thereby, describe one important aspect of growth models in considerably more detail than the literature has been doing so far. 2.2. Dimensions of trade models The development of any typology must start with a selection of variables according to which countries are classified. In line with the existing literature, we take into account variables from four dimensions: natural endowments, technological capabilities, labour market institutions and regulatory environment (see Figure 1). 5 Figure 1: Dimensions of trade models. Since Adam Smith’s seminal contributions, natural endowments are seen as a key factor in coining patterns of trade and economic development (e.g. Barbier 2003; Dosi and Tranchero 2018; Wright 1990). Possessing scarce resources needed for further processing represents an advantage for a given country. The developmental implications of such resource endowments are, however, mixed: while countries such as Norway or Saudi Arabia have acquired considerable wealth due to their natural endowments, many other resource-rich countries remain poor, either because of negative exchange rate effects (à la the Dutch Disease) or because of higher corruption, which often results from personal short-term gains related to resource appropriation. The importance of technological capabilities for trade performance has been highlighted in a number of recent studies (e.g. Dosi et al. 2015; Gräbner et al. 2019b; Storm and Naastepad 2015). 2 The accumulation of technological capabilities is usually also associated with positive developmental implications. Lee (2011), for instance, analysed 71 countries and showed that those countries exporting high-technology products grew more rapidly than countries exporting low or medium technology products. For Hidalgo (2015), technological capabilities are the ultimate source of economic development, a view motivated by recent contributions to the science of economic complexity (Cristelli et al. 2015; Felipe et al. 2012; Hidalgo and Hausmann 2009; Tacchella et al. 2013). The third set of variables is concerned with labour market institutions and labour market outcomes. The relevance of institutions that ensure relatively low unit labour costs as a key source for international competitiveness is regularly highlighted (Chen et al. 2012; Cuñat and Melitz 2012; Lapavitsas et al. 2011; Samuelson 2004). 3 Consequently, boosting export-led growth is said to 2 Storm and Naastepad (2015a, 2015b) also raise this argument in the context of Germany’s export-success; they explain Germany’s stellar export performance not by price competitiveness, but rather by its superior technological competitiveness. 3 The actual relevance of low labour unit costs for relative export-success, however, is surrounded by many doubts. A typical counter-argument is that labour market flexibility and low labour unit-costs are mainly reducing domestic demand as well as 6 require more labour market flexibility, which implies the need to reduce employment protection legislation, unemployment benefits and the influence of trade unions. In more general terms, strong labour market institutions can be seen as a protection of employees from the uncertainty caused by globalisation and are able to explain a large part of cross-country differences in income inequality and wage mobility (Aristei and Perugini 2015; Esping-Andersen, 1990; Crouch and Streeck 1995; Hall and Soskice 2001). Rodrik (1996) and more recently Manow (2018) argue that the well-developed welfare state is mainly a promise to compensate potential losers of international trade. The final category of variables covers the regulatory environment of countries: the ability of a country to attract international investments and/or incentivize firms to migrate to this country is considered a major determinant for international competitiveness. A common line of argument relates this ability to low corporate taxes and loose regulations. Being aware of their significance for job creation and international competitiveness, firms influence the political discourse and try to avoid new regulations. In a highly interconnected global economy, however, politicians try to convince firms to stay in a respective country by relocating the tax-burden or by weakening regulatory requirements, especially for the financial sector. This setup can lead to a general race to the bottom in regulatory standards (e.g. Carruthers and Laboureaux 2016; Egger et al. 2019; Kapeller et al. 2016) and foster distributional conflicts (Baccaro and Pontusson 2016). 2.3 Data and Method To develop a typology of trade models, we compose a data set for EU countries that comprises indicators for all four main dimensions of competitiveness highlighted in the previous section in the time period between 1994 and 2016 (see table 1). We operationalize the dimension of endowments via (a) the employment share in agriculture, (b) the share of oil in total exports, (c) the share of general primary goods in total exports, (d) the share of value added coming from manufacturing and (e) natural resources rents (in % of GDP). To address the complexity of technological capabilities, we refer to the gross domestic expenditure on R&D and government expenditure on education as indicators for how countries foster the development of high-technology products by education and research. The capital share of Information and Communication Technology in relation to GDP (ICT) and employment in the industrial sector are used to proxy for the economic structure of countries. Finally, the index of economic complexity (Hausmann and Hidalgo 2009) is used as a proxy for the amount of technological capabilities accumulated within a given country. imports and thereby contributing to increasing trade surpluses (Dias-Sanches and Varoudakis 2013; Flassbeck and Lapavitsas 2013). 7 Dimension Indicator Unit Natural endowments Employment in agriculture Share of total employment Natural resources rents Share of GDP Oil Share of total exports Primary goods Share of total exports Share of Value Added from manufacturing Percent of GDP Technological capabilities Economic complexity index Index Employment in the industrial sector Percent of total employment Government expenditures on education Percent of GDP Gross domestic expenditure on research and development Percent of GDP ICT capital share in GDP Percent of GDP Adjusted wage share Percent of GDP Labour Market Average wages per year PPP Dollar Coordination of wage-setting Index Strictness of regulation on dismissals and the use of temporary contracts. Index Unemployment Benefit Net Replacement Rates for single earner in initial phase of unemployment Percent Corporate Tax Tax revenue as percent of GDP Regulatory environment De jure component of the KOF econ index Index Foreign direct investment (FDI) Percent of GDP Share of financial sector in gross output Percent of all sectors Taxes on estates and other wealth taxes Tax revenue as percent of GDP Taxes on estates and other wealth taxes Tax revenue as percent of GDP Table 1: Indicators and Dimensions of trade models. To operationalize the dimension of labour market institutions, we consider the employment protection legislation and net replacement rate of unemployment benefits. We also include an index for the coordination of wage bargaining since the literature suggests that wage moderation – which is considered a major determinant for export success – requires a high degree of wage coordination (Traxler et al. 2001). As an indication of a low labour cost strategy, we use two indicators: the average national wages and the adjusted wage share. A low or a decreasing wage share would mean that employees benefit less from economic growth and from international trade than owners of assets. Finally, with regard to the dimension of the regulatory environment, we use the revenues of three categories of taxes (as percent of GDP), which are relevant for companies’ (re)location choices: corporate taxes, estate taxes and all other wealth taxes. Furthermore, the share of the financial sector in gross output and foreign direct investment (FDI) in relation to GDP are included as indicators for capturing deregulation strategies that are geared towards attracting foreign 14 also due to the low absolute values of their GDP per capita: the Eastern countries are still the poorest in our sample, and have so far only managed to catch up to the countries in the periphery, who have experienced the by far lowest growth rates among all countries. Figure 3: Growth of real GDP per capita (PPP), source: World Bank; own calculations. Between these extremes, we find the countries following the ‘high-tech model’, as well as ‘flexible labour market model’ and the ‘financial hub’. All these countries – despite following very different trade models – experienced similar growth rates since 1994, although the focus on finance in Luxembourg leads to a much more volatile development. When considering the levels of GDP per capita, the exceptional state of affairs in Luxembourg becomes obvious. In addition, we also note significant higher per capita incomes in the ‘high-tech cluster’ as compared to the ‘flexible labour market model’. Given that labour market institutions played an essential role in delineating the different growth models, we might expect employment dynamics to be different between trade models. Figure 4a confirms this conjecture by suggesting a kind of dichotomous polarization across trade models: unemployment has fallen considerably in the countries following the “industrial workbench model’, indicating that they are harvesting the benefits of their successful industrialization (although regional differences continue to play a role). The ‘flexible labour market model’ and the high-tech countries also managed to reduce unemployment significantly, the former mainly through a very flexible labour market with strong incentives to accept work, the latter mainly 0% 1% 2% 3% 4% 5% ITA GRC FRA PRTESP GBR LUX DNK BEL DEU AUT NLD FIN SWE IRL SVN HUN CZE SVK POL EST LVA Mean GDP per capita growth (1995−2017) A) ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 25k 50k 75k 100k 1995 2000 2005 2010 2015 Real GDP per capita B) High tech model Periphery Flexible labor markets model Industrial workbench model Primary goods model Financel hub 15 through their competitiveness in terms of technological capabilities and a strong export industry. 4 On the other hand, unemployment was growing considerably in the ‘finance model’, but this is mainly the result of an exceptionally low unemployment in the year 1994, which was the lowest of all models. The high increase of unemployment in the countries following the primary goods model is more serious. This indicates that – despite rising incomes in the past - these countries do face a challenge of structural change towards more future-fit industrial sectors. The by far worst development of employment can be observed in the periphery countries, who not only face severe problems of international competitiveness, but above all suffered from harsh austerity measures and a continuing recession after the financial crisis. Figure 4: Unemployment rate in percent, source: AMECO; own calculations. The relevance of the crisis in shaping employment patterns becomes obvious when inspecting figure 4b: while there are some convergence tendencies of the unemployment rate until the year 2007, countries following different trade models showed very different reactions to the financial crisis: all countries experienced a spike in unemployment, but this effect was barely noticeable in Luxembourg, rather moderate in the high-tech and industrial workbench and the flexible labour market model, and extreme for the countries following the periphery and the primary goods model. Compared to the latter, the periphery barely recovered from this shock and still experiences the by far highest unemployment rates among all countries. The countries following the primary goods models managed to recover to some extent, but still record significantly higher unemployment rates than the rest, including the other Eastern European 4 At least Germany has also introduced restrictive labour market reforms (the “Hartz – Reforms”, see e.g. Mohr 2012), which put high pressure on unemployed and led to wage moderation. Its superior technological competitiveness, however, still seems to be the main determinant for its export success (Storm and Naastepad 2015a, 2015b). −3% −2% −1% 0% 1% 2% 3% 4% 5% POL HUN SVK CZE SVN GBR DEU FIN SWE IRL BEL NLD DNK AUT LVA EST LUX FRA ESP ITAPRT GRC Average change in the unemployment rate (1995−2017) A) ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 5% 10% 15% 20% 1995 2000 2005 2010 2015 Unemployment rate (1995−2018) B) High tech model Periphery Flexible labor markets model Industrial workbench model Primary goods model Financel hub 16 countries following the industrial workbench model, whose strong industrial sector seems to be a better job provider than the primary goods sector in Latvia and Estonia. The remaining clusters (high-tech, finance and the UK) now all experience similar levels of unemployment. 5.2. Trade performance We now assess the various trade models with regard to their current account. As shown in figure 5a, only Luxembourg and the countries following the high-tech trade model (except Ireland) achieved a positive current account balance on average, although as the result of different dynamics (figure 5b): while the surplus in the high-tech countries was stable over time, Luxembourg experienced a considerable reduction of its surplus in the past 22 years, which was on an exceptionally high level in the year 1995. The constant current account surplus in the high-tech countries is most likely due to their advanced industrial sector with the capability to produce complex products for which they are confronted with fewer competition, but a stable demand, as compared to the technologically less sophisticated products produced by the periphery countries or those following the primary good model. The latter two groups show the worst average current accounts, with only Spain and Italy being the exceptions. This has to do with the regional polarization within those countries: in Spain, for example, companies in the North have a strong position in the world markets and contribute positively to the current account of Spain as a whole. But the Spanish South is rarely industrialized and the companies possess only few technological capabilities. A similar divide can be observed within Italy. The positive trend since the financial crisis (figure 5b) can be traced back to shrinking imports, which themselves are due to a considerable reduction of citizens’ disposable income. The current account balance of the UK has worsened continuously since 1995, indicating the failure to manage structural change into a more technologically advanced direction. Given its focus on a strong service sector focused on financial activities, and the lack of effective industrial policy in the North of the country, this is not barely surprising. The industrial workbench countries still show a negative current account on average, but the trend in recent years points towards continuous current account surpluses, indicating that their newly established industries are increasingly competitive on international markets. 17 Figure 5: Current account in % of GDP, source: AMECO. 3.3. Inequality Finally, we study whether different trade models are also accompanied by distinct inequality dynamics. With regard to the functional income distribution, we observe a reduction of the wage share in all trade models except for the UK and the ‘finance’ model, indicating that in most trade models, employees did not benefit markedly from economic growth and increasing international integration (see figure 4a). The exceptional role of Luxembourg and the UK is most likely due to the many well-paid jobs in the large financial sectors of these countries. Because of their different economic structure, this does not imply a high level of personal inequality in Luxembourg, where the vast majority of the population enjoys high salaries, but it does so for the UK, where the wellpaid employees are concentrated in the South, particularly the City of London, but especially the North is characterized by lower wages and higher unemployment. This becomes immediately obvious in the right panel of figure 4, where the UK belongs the group of very unequal clusters, while Luxembourg still enjoys moderate levels of income inequality, although it suffers from the most pronounced increase in personal income inequality since 1995 and has surpassed the hightech and industrial workbench countries, whose level of personal income inequality remains moderate as compared to the other trade models. −6% −4% −2% 0% 2% 4% 6% GRC PRTESP ITAFRA LVA EST GBR SVK HUN CZE POL SVN IRL AUT FIN BEL DEU DNK SWE NLD LUX Average Current Account in % of GDP (1995−2017) A) ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● −20% −15% −10% −5% 0% 5% 10% 1995 2000 2005 2010 2015 Current Account in % of GDP (1995−2017) B) High tech model Periphery Flexible labor markets model Industrial workbench model Primary goods model Financel hub 18 Figure 6: Development of wage-share and Gini index between 1994-2016. Source: AMECO for the wage share and Solt (2019) for inequality data. The consideration of inequality highlights important differences between trade models that appeared to be similar with regard to their growth and employment dynamics (5.1) and foreign trade performance (5.2): for example, while the industrial workbench economies still enjoy comparatively low levels of inequality, inequality is high in those countries following the primary goods model, despite both models enjoying respectable growth rates of GDP per capita. Here, the low unemployment rates and the less volatile development dynamics associated with the focus on industrialization inherent to the industrial workbench model seem to be important parts of the explanation. In addition, while the UK at first sight seems to be similar to the countries following a high-tech trade model, the focus on the production of high-tech products comes with significantly lowers levels of inequality than the focus on flexible labour markets and a concentrated financial sector in the UK. 4. Discussion In this paper, we complement the literature on growth models in Europe by systematically analysing one component of aggregate demand that has featured particularly prominent in the literature so far: international trade. Building on the four theoretical dimensions natural endowments, technological capabilities, labour market characteristics and regulation, we delineated a typology of trade models in 22 EU countries. Based on 20 variables, we have used a hierarchical Gini (post) Gini (pre) Wage share −20% −10% 0% 10% 20% Change in % Inequality in 1994 and 2016 A) ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 25% 28% 30% 32% 35% 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 Income inequality (Gini post tax) B) High tech model Periphery Flexible labor markets model Industrial workbench model Primary goods model Financel hub 19 cluster analysis to identify six trade models in the EU: the ‘primary goods model’ (Latvia, Estonia), the ‘finance model’ (Luxembourg), the ‘flexible labour market model’ (UK), the ‘periphery model’ (Greece, Portugal, Spain, Italy, France), the ‘industrial workbench model’ (Slovenia, Slovakia, Poland, Hungary, Czechia), and the ‘high-tech model’ (Sweden, Denmark, Netherlands, Belgium, Ireland, Finland, Germany and Austria). This typology complements previous findings from the existing literature. Our results align well with the findings of Gräbner et al. (2019a), who develop their taxonomy based on macroeconomic data, countries’ reactions to increasing economic openness and theoretical considerations. Most importantly, the countries that follow the high-tech model in our case are almost the same countries that Gräbner et al. (2019a) consider as core countries and the periphery in their study is almost the same as in our analysis of trade models. This suggests that trade models strongly relate to the more general positioning of a country within the political economic environment of the EU. We also find some similarities to the results of Esping-Andersen (1990), although our focus on trade patterns differs from their focus on welfare regimes. The ‘flexible labour market model’ resembles the liberal regime (United States, Canada, Australia) in EspingAndersen (1990) with regard to their composition and welfare state characteristics. Furthermore, the ‘high-tech model’ shares some similarities with the social democratic regime of EspingAndersen (1990) but also includes conservative countries like Germany and Austria. Our trade typology also complements to the literature on technological capabilities and regulation. A result that sticks out is that the ‘high-tech model’ is characterized by a large stock of technological capabilities and that it seems to provide institutions and a political setting ensuring stability even in times of economic turmoil, as indicated, for example, by the relatively stable GDP growth and unemployment rates during and after the 2008/2009 crisis. At the same time, the ‘hightech’ trade model shows one of the highest wage shares and the lowest income inequality of all trade models in Europe. Thus, lower inequality does not necessarily hamper economic performance and trade and there is an alternative to wage moderation when it comes to achieving international competitiveness and economic prosperity. A possible explanation is the relationship of economic growth and the economic complexity of a country. According to Hidalgo and Hausman (2009), economies that produce and export more complex goods also follow a sustained growth path that leads to higher prosperity than in countries that produce simpler products. In order to facilitate the development of a more complex product pool, the state has an essential role to play when it comes to fostering collective knowledge, human capital accumulation and setting the legal and institutional framework in a way that allows for improving an economy’s capabilities for innovation (Felipe et al. 2012; Mazzucato 2013). Our results indicate that labour market 20 institutions, an active government and investments in R&D may play an important role in achieving these goals. Finally, this paper leaves room for further research. One possible extension to this paper would be to analyse how trade patterns have changed over time. In developing our trade models in the EU, we have used data from 1994 to 2016. Due to the introduction of the Euro during this period, it is reasonable to assume that economies have changed their trading strategies as well as their institutional settings. Unfortunately, most of the relevant OECD data are only available after a country has joined the OECD club. Consequently, available data are very limited for new OECD countries. Further research on the development of trade models on the basis of improved data availability could provide a better picture about how trade models change over time. 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