TY - JOUR
AU1 - López González,, Javier
AU2 - Meliciani,, Valentina
AU3 - Savona,, Maria
AB - Abstract This article looks at the determinants of a country’s participation in business services (BS) global value chains (GVCs). BS GVCs are comparatively less explored than traditional manufacturing ones, and there is a gap in the literature on the relative positions of countries in BS GVCs and the opportunities they might open for development. This article puts forward and finds empirical support to the conjecture that the domestic structure of backward and forward linkages à la Hirschman, alongside the domestic representative demand for BS à la Linder, are of high importance. The results, based on the World Input-Output Database, suggest that the presence of strong domestic backward-linked industries to BS makes an emerging country more likely to create domestic value within BS GVC. Our findings contribute to the debate on a “premature de-industrialization” in emerging countries and on the relationship between levels of development and engagement in BS GVCs. 1. Introduction It is often argued that the international fragmentation of production offers developing countries the opportunity to “fast-track” the process of industrialization. Indeed, with the emergence of global value chains (GVCs), emerging countries can now specialize in particular tasks along the value chain rather than having to set-up entire processes of production from scratch (see De Backer and Miroudot, 2013; Kaplinsky, 2013; Timmer et al., 2014; Baldwin and López González, 2015). Baldwin (2011) has defined this phenomenon as globalization’s “second unbundling,” transforming the terms of international competition and shifting the barycenter of the world’s global headquarters and peripheries. The emerging empirical studies on whether GVCs provide new development opportunities (Gereffi, 2015) are in general limited to participation in manufacturing activities. However, in the context of the rising service content of exports, and the “servicification” of manufacturing (Pilat and Wölfl, 2005; Pilat et al., 2006; Kommerskollegium, 2012; Lanz and Maurer, 2015; Miroudot and Cadestin, 2017), it is relevant to ask whether domestic value creation within service GVCs responds to the same drivers and therefore presents similar opportunities for emerging countries. The question is all the more relevant in the case of business services (BS),1 the most dynamic branch of services, and one which plays an essential role in the creation and diffusion of new technologies and non-technological modes of innovation (Guerrieri and Meliciani, 2005; Gallouj and Savona, 2008; Ciarli et al., 2012; Meliciani and Savona, 2014). The emerging country context is especially interesting if participation in BS GVCs offers an additional channel for technology transfer to occur, and provides opportunities for domestic technological upgrading. Scholars looking at the link between global trade and local upgrading have rarely explicitly focused on BS GVC links (Fu et al., 2011; Pietrobelli and Rabellotti, 2011). A few recent contributions, based on qualitative evidence on specific country cases, suggest that participation in BS GVC can open up new opportunities for catching up in emerging countries (Blinder, 2006; Gereffi and Fernandez-Stark, 2010; Hernández et al., 2014a, b). Similarly, only a few, recent, quantitative contributions (Banga, 2014; Francois et al., 2015; Miroudot and Cadestin, 2017) have looked at the new trends of services and BS tradability in the context of GVCs. Some of this evidence shows that the relative position of developed and emerging countries in terms of services value added content of export is quite different, with emerging countries having comparatively less service content in trade (Francois et al., 2015) and more foreign services value added embodied in (manufacturing) exports (see López González, 2016 for the case of Southeast Asia). What drives countries toward participation in BS GVCs remains relative unexplored and yet relevant for trade and development policy. This article aims to identify the main determinants of participation in BS GVCs in both developed and emerging countries.2 Our main conjecture is that, differently from manufacturing GVCs, it is more difficult for emerging countries to create domestic value in BS GVCs by mainly relying on foreign demand from headquarter economies. This conjecture is grounded in empirical evidence, showing that BS tend to locate closely to the sectors representing their pool of demand, most often manufacturing sectors (Meliciani and Savona, 2014), and contribute to knowledge accumulation and leveraging for the rest of the economy (for a review, see Gallouj and Savona, 2008; Ciarli et al., 2012). We therefore expect that countries where the lack of core domestic intermediate demand for BS is particularly salient, such as emerging countries, may find it more difficult to export domestic value added in BS relative to those that are able to exploit these linkages. Due to the on-going process of servicification of manufacturing—and international fragmentation of production processes—we expect the specific domestic structure of inter-sectoral linkages between BS and other industries (particularly manufacturing) to be one of the key determinants of a country’s participation in BS GVCs. As a consequence, in the absence of a strong domestic base of backward-linked industries to BS it is more difficult for emerging countries to engage in forward participation in BS GVCs. While we do not attempt to formalize our conjecture in a formal theoretical model, we show that this is grounded in the observation of recent empirical evidence on trends of GVCs (illustrated in Sections 2.1 and 2.2 below). Further, our conjecture is theoretically embedded in a careful revisitation of classical contributions to development economics (Hirschman, 1958) and trade theory (Burenstam Linder, 1961) often neglected in these circles (illustrated in Section 2.3). We formulate and empirically test a joint Hirschman–Linder hypothesis as we expect that both domestic inter-sectoral linkages (Hirschman) and the presence of a “representative domestic (derived) demand” for BS (Linder) affect participation in BS GVCs.3 We test our hypothesis using the World Input-Output Database (WIOD), which we draw upon to construct indicators of forward participation in BS GVCs and a range of proxy measures for domestic and international linkages. In the econometric specification, we consider that a Hirschman–Linder effect might also occur in close trade partners. Hirschman linkages and Linder effect favoring participation in BS GVCs of trade partners’ countries might also affect a representative country’s participation in BS GVCs. We expect this effect to be positive or negative depending on whether Hirschman–Linder linkages in trade partners act as an (additional) international derived demand for BS or, rather, when a competition effect dominates. In this latter case, Hirschman–Linder linkages in trade partners displace participation in BS GVCs in the representative country. Our results suggest that the determinants of participation in BS GVCs partly differ from those that determine engagement in manufacturing GVCs. The domestic industrial structure, particularly if intensive in industries that are backward-linked to BS, plays a central role in explaining participation in BS GVCs. However, differently from participation in manufacturing GVC, proximity to countries involved in BS GVCs does not help emerging countries to participate in GVCs. This casts doubt on BS GVCs presenting the same type of opportunities for emerging countries as they do for developed countries. We attempt reflections on the implications of our results in terms of policies for development and suggest some caution when considering unconditional participation in BS GVCs as a new development pathway in the absence of sectoral and technological upgrading linked to the presence of domestic backward-linked sectors, particularly a domestic manufacturing base. We therefore offer, albeit from a different theoretical perspective, empirical ground to some of the concerns of “premature de-industrialization” put forward by development scholars (Rodrik, 2015). Our findings also support the conjectures recently put forward by Lee et al. (2017), Lee and Malerba (2017), Baldwin (2012), and López González and Holmes (2011), who have looked at the relationship between levels of development and participation in GVCs. According to these, countries tend to predominantly rely on foreign inputs at early stages of development (high intensity of backward participation) but predominantly contribute with domestic value added to foreign exports at later stages of development (high intensity of forward participation).4 The remainder of the article is structured as follows: the next section reviews the relevant theoretical and empirical literature on BS GVCs. We lay out our main conjecture and argument in Section 3. Section 4 details the empirical strategy: the indicators that we construct on the basis of the WIOD with respect to extant measurements of value chains in the literature and the econometric strategy. We then discuss the econometric results in Section 5 and conclude in Section 6. 2. Trends of GVC in services A defining feature of global trade today is the international fragmentation of production, which has led to more trade of intermediates through the emergence of GVCs. These have been the object of an increasing amount of theoretical and empirical interest and a flourishing number of contributions on methods to measure participation in GVCs (see among others, Grossman and Rossi-Hansberg, 2006; Costinot et al., 2013; OECD, 2013; Timmer et al., 2013; Koopman et al., 2014; Kowalski et al., 2015). Baldwin (2011) first put forward the idea of globalization’s “second unbundling,” which started after 1985 and was driven by a reduction in Information and Communication Technology (ICT) costs, resulting in the unpacking of factories and leading to widespread offshoring and growing trade in intermediate products. This second unbundling shifted the nature of international competition toward stages of production rather than products and led to the spatial redistribution of global economic activity between “headquarter”5 and “factory” economies. The latter are mainly emerging countries, specializing in the lower-tech (usually low-skilled) phases of manufacturing, while the high-tech (usually high-skilled) segments tend to remain within the boundaries of the headquarter economy. Participation in GVCs has been claimed to be a unique opportunity for emerging and developing countries, allowing these to industrialize in a fraction of the time that developed countries took to take off (Baldwin, 2011).6 However, Baldwin’s (2011) first and second unbundlings refer mainly to manufacturing value chains. But there is an emerging literature highlighting the growing “servicification” of manufacturing, and the growing service content of exports (Pilat and Wölfl, 2005; Pilat et al., 2006; Gereffi and Fernandez-Stark, 2010; Kommerskollegium, 2012; OECD, 2013; Hernández et al., 2014a, b; Lanz and Maurer, 2015). Evidence shows, for example, that Europe’s value added that is used by China to produce exports comes predominantly from the service sectors which China uses to engage in the low-skill manufacturing elements of the value chain (Koopman et al., 2008). Two other key findings are worth highlighting. The first is the relative importance of BS in value added terms over gross exports (Figure A1). In 2011, gross BS exports represented nearly 5% of total gross exports (Figure A1a), but in value added terms, when considering BS embodied in other exported products, the importance of BS more than doubles to 11% of gross exports (Figure A1b). In terms of both gross exports and the value added embodied in gross exports, the importance of BS has increased (by around 1% point), unlike that of manufacturing which has declined by around 8% points in both gross exports and value added terms. This is in line with the evidence shown by Banga (2014), Francois et al. (2015), and Miroudot and Cadestin (2017) suggesting that trade specialization in BS might need to be re-assessed. As put by Koopman et al. (2014: 461): “(.) with gross trade data, the business services sector is a revealed comparative advantage sector for India. In contrast, if one uses our estimated domestic value added in exports instead, the same sector becomes a revealed comparative disadvantage sector for India in 2004. The principal reason for this is how the indirect exports of business services are counted in high income countries. Consider Germany. Most of its manufacturing exports embed German domestic business services. In comparison, most of Indian goods exports use comparatively little Indian business services. Once indirect exports of domestic business services are taken into account, Indian’s business services exports become much less impressive relative to Germany and many other developed countries.” The second is the uneven distribution, or the concentration, of global suppliers of intermediate BS (Figure 1).7 Indeed, “headquarters economies”8 such as the United States, the United Kingdom, and Germany provide over one-third of global BS value added in exports (VAE) (18%, 9%, and 8%, respectively). By contrast, developing countries such as China and India tend to be net recipients of BS value added. Comparing this table to that of manufacturing in Baldwin and López González (2015) shows that, globally, BS VAE tends to be more concentrated than manufacturing VAE. Figure 1. Open in new tabDownload slide Business Services Value Added in Export (BSVAE). Source: Own calculations using WIOD. Figure 1. Open in new tabDownload slide Business Services Value Added in Export (BSVAE). Source: Own calculations using WIOD. Overall, emerging countries have been the destination of an increasing volume of standardized Information Technology Outsourcing, due to a combination of decreasing Information Technology (IT) costs, increasing opportunities for standardization of typical IT functions, and a very recent drive to look for “talents” across the whole world, that for the first time does not exclude the participation of emerging countries (Lewin et al., 2009). The top segments of offshore services are Business Process Outsourcing and Knowledge Process Outsourcing, which are more intensive in high-skilled human capital and knowledge and typically remain within headquarter economies. However, it has been argued that in most recent years an increasing trade share of these high-skilled activities have involved Latin American countries, the Philippines and Malaysia. The tone of the emerging discourse seems to depict a rosy picture, in terms of developmental opportunities for periphery countries to join BS GVCs, and the role of industrial policy to favor this process (Gereffi and Fernandez-Stark, 2010). However, the reflection on service GVCs is still at its embryonic stage, with much empirical evidence still limited to qualitative, single industry case studies, which, although highly informative, lack generalizability, calling for some cautiousness. To summarize, while the literature has looked mainly at GVCs in manufacturing and the relative position of developed and emerging countries within these (see for instance Baldwin, 2016), based on the traditional view on technology transfer embodied in tangible intermediates, GVCs in BS are in general much less explored, despite a recent surge in interest (Koopman et al., 2014; Francois et al., 2015; Miroudot and Cadestin, 2017). A relevant question within the growing GVC literature is whether participation in manufacturing and BS GVCs responds to similar determinants and whether they can open up new opportunities for industrial development. To address these questions, we argue that it is important to understand if emerging countries are able to create domestic value in BS GVCs without an adequate domestic capacity, where this latter, we argue, is linked to the presence of domestic (backward) linked industries, such as the manufacturing sectors. 3. When Linder meets Hirschman: a reappraisal of BS GVCs The study of the effects of structural change on economic performance of countries has traditionally brought about concerns about de-industrialization processes and the erosion of capital accumulation in advanced countries.9 In some cases, positive expectations on knowledge accumulation and leveraging for the rest of the economy, intrinsic in some BS10 and the widespread diffusion of ICTs have counter-balanced this view (for a review, see Gallouj and Savona, 2008; Ciarli et al., 2012; Meliciani and Savona, 2014). The empirical evidence on the emergence of Knowledge Intensive Business Services has often sided with this narrative.11 When it comes to patterns of structural change in emerging countries, involving shifts from agriculture to low-tech industries and services, the empirical evidence is more mixed and controversial (Dasgupta and Singh, 2005,, 2006; Bah, 2011), and rarely takes into account the global dimensions of structural changes, with notable exceptions (McMillan et al., 2014; Rodrik, 2015). Despite this, the theoretical and empirical debates within the trade and GVCs literatures seem to suggest that structural changes toward BS in developing countries could be desirable, and eased by joining BS GVCs. Borrowing from Baldwin (2011), it can be argued that the increasing involvement of services in GVCs is a sort of “third unbundling,” equivalent in importance to the processes of tertiarization that followed industrialization in developed countries, occurring now on a global scale, albeit at different levels of aggregate income (McMillan et al., 2014; Rodrik, 2015). For the purpose of identifying the determinants of the emergence of service GVCs, we put forward four questions and attempt to provide a testable framework that can answer them: What are the determinants of countries’ participation in BS GVCs and are they different from those relevant for participation in manufacturing GVCs? Are the determinants of participation in BS GVCs different in developed and emerging countries? Relatedly, does proximity to large headquarter economies matter for participation in BS GVCs? Alternatively, to what extent do countries need to develop their own capacity internally—in the form of domestic presence in high BS user sectors? What are the implications in terms of industrial policy for development? While we do not attempt to tackle these questions in a formal theoretical model, we articulate the intuition that, in the absence of a strong domestic presence of backward-linked industries to BS (industries demanding BS as intermediates), emerging countries will find it more difficult to create domestic value within BS GVCs. Our conjecture is based on the empirical evidence on trends in GVCs illustrated above and is theoretically embedded in a careful revisitation of classical contributions to development economics (Hirschman, 1958) and trade theory (Burenstam Linder, 1961), often neglected in these circles (Lundhal, 2006). In a seminal text on economic development, Hirschman (1958) identified the structure of sectoral intermediate linkages within regional economies as the main determinant of specialization and growth polarization. According to Hirschman, there are different types of externalities, depending on whether activities are related to one another by backward or forward inducement mechanisms, i.e. whether certain sectors, by demanding inputs, induce the growth of supplier industries (input-provision or backward linkage effect) or, rather, by supplying output induce the growth of client industries (output-provision or forward linkage effect).12 Hirschman took a remarkably original stand with respect to the mainstream growth theory of the time based on factor endowments. Sectoral specialization and structural change had hitherto rarely been considered of much relevance in explaining growth polarization across local and national economies.13 The role of linkages in Hirschman’s work serves the purpose of creating new sectors by way of scalable intermediate demand, and therefore represents a useful device to explain structural change of the sectoral composition of economies. Hirschman’s work, however, remained relatively silent on the conditions and specific mechanisms by which intermediate demand is translated into the creation of new supplier sectors,14 and how this, in turn, leads to upgrading. Recently, the role of structural transformation is being increasingly brought back in the development debate (Lin, 2012; Stiglitz et al., 2013). The work of Linder (Burenstam Linder, 1961) also emerged as a radical stand against mainstream trade theory based on the Heckscher -Ohlin -Samuelson (HOS) model. According to the HOS model, foreign trade is determined by cross-country differences in factor endowments, and trade specialization emerges as a result of endowment abundance. Capital-intensive countries would specialize and trade in capital-intensive goods, while countries with a higher relative endowment of labor would specialize and trade in labor-intensive goods. In this context, Linder put forward what is now known as the Linder Thesis. According to Burenstam Linder (1961), the Heckscher–Ohlin model was able to explain trade in raw materials, but less so the patterns of trade in manufactured goods between similar nations (in terms of their level of development). Manufacturing trade depended on whether a country reached a certain level of domestic representative demand. This benchmark level of domestic demand, in turn, provided the necessary information from purchasers to producers, which eventually allowed them to face competition in foreign markets. Therefore, countries with a similar structure of final demand—owing, for instance, to similar levels of per capita income—tended to have similar structures of trade specialization. This then helped explain the prevalence of intra-industry trade between similar economies. In his 1961 “Essay on Trade and Transformation” Linder mentions (p. 94): “The more similar the demand structure of two countries, the more intensive, potentially, is the trade between these two countries”; and that (p. 94) “similarity of average income levels could be used as an index of similarity of demand structure”. Indeed, as it emerges clearly in his book, the core and novelty of his thesis as to what affects trade is (i) the emergence of a domestic need; (ii) the development of domestic capabilities to satisfy it; and (iii) as a consequence, the achievement of a critical mass of “representative domestic demand” that eventually becomes a comparative advantage for trade.15 Here, we adopt and re-propose Linder’s classical notion of a “representative domestic demand” with a view of including not only its original meaning—that is the domestic structure of (final) demand associated with the specific level of development of a country—but also, and in the same vein, that such specific level of development affects the structure of derived demand for BS coming from different sectors.16 We therefore formulate and empirically test a joint Hirschman–Linder hypothesis as we expect that both domestic inter-sectoral linkages (Hirschman) and the presence of a “representative domestic (derived) demand” for BS (Linder) affect participation in BS GVCs. Our implicit conjecture is that countries that develop a critical mass of domestic activities linked to BS are more likely to develop a comparative advantage in BS GVCs. Moreover, given the “servicification” of manufacturing (Pilat and Wölfl, 2005; Pilat et al., 2006; Kommerskollegium, 2012; Lanz and Maurer, 2015, Miroudot and Cadestin, 2017), we suggest a special role to be played by the presence of a domestic manufacturing base for BS domestic VAE through strong manufacturing-BS inter-sectoral linkages. 4. Empirical strategy The empirical strategy aims to identify the determinants of participation in BS GVCs. It operationalizes a joint Hirschman–Linder hypothesis and combines this with traditional cost and factor endowment measures. Alongside these, we take into account three sets of new determinants affecting participation in BS GVCs: The domestic Hirschman–Linder linkage. This identifies the domestic structure of inter-sectoral linkages and the level of derived demand for BS in the representative country. We expect this variable to have a positive impact on our outcome variable, BS GVCs. The domestic Hirschman–Linder linkage of trade partners. This identifies the domestic structure of inter-sectoral linkages and the level of derived demand for BS in distance-weighted trade partners. This variable can have a positive or negative effect, depending on whether domestic Hirschman–Linder linkages in trade partners act as an (additional) international derived demand for BS for the representative country or, rather, if a competition effect dominates and displaces participation in BS GVCs. The spillovers, or GVC linkage, with trade partners. Capturing the participation in BS GVCs in distance-weighted trade partners, which, in turn, might have a positive or negative effect depending on whether geographical closeness and partner country participation in BS GVCs entails positive or negative spillovers. We also control for more traditional cost and endowments factors, such as skills, wages, technology, as well as for a set of BS-specific factors, such as trade agreements in services and telecommunication infrastructure. We consider differences across sectors (BS and manufacturing) and across countries (developed and emerging). 4.1 Data We use the WIOD (November 2013 release), which covers 40 economies (including all EU-27 countries as well as Australia, Brazil, Canada, China, India, Indonesia, Japan, Korea, Mexico, the Russian Federation, Chinese Taipei, Turkey, and the United States) and a rest of the world aggregate grouping across 35 sectors (20 of which are services, 11 manufacturing, and 4 primary sectors) and 15 years (annually from 1995 to 2009).Tables A4and A5 in the Appendix, respectively, list the sectors and countries included in our analysis. The database has two key components: (i) an annual inter-country input-output (ICIO) table and (ii) an accompanying set of Socio Economic Accounts (SEAs).17 The ICIO tables lend themselves to the calculation of indicators that capture the extent and nature of GVC participation across different sectors (see Timmer et al., 2013). The SEAs then give us valuable information on the wage bills or indeed the hours worked by labor of different skills within countries, which we exploit and combine with indicators of GVC participation to test our hypotheses. As mentioned, comparative analysis is undertaken across countries at different stages of development to identify whether there are significant differences between developed and emerging economies (for a list of emerging economies in the sample, see Table A5).18 Finally, we use the Panel Dataset for Cross-Country Analyses of National Systems, Growth and Development (CANA) (Castellacci and Natera, 2011) to construct proxies of countries’ technology endowment and the DESTA database (Dür et al., 2014) to identify the service related trade policy environment. We cover the period 1995–2009 only due to data limitations. Although ICIO tables are now available from 2000 to 2014 (whether from the WIOD or the OECD-WTO TiVA database), the SEA containing information on wages and hours worked for workers of different skills, important control variables, are only available till 2009. 4.2 Variables Our choice of indicators is informed by the mushrooming literature on GVCs based on ICIO models. We exploit different indicators based on these models to construct both dependent and independent variables paying particular heed to avoiding mechanical associations between these in the estimations. 4.2.1 Engagement in BS GVCs Our interest lies in the determinants of GVC participation in BS. The literature on GVCs typically employs two measures of participation. These are the backward and the forward participation indicators, which are, respectively, the importing and exporting elements of GVCs (see Figure A2). The figure illustrates how gross exports can be decomposed into many different constituent elements. At their most basic, gross exports are composed of domestic and foreign value added which can themselves be further decomposed using Input-Output tables. For example, the domestic value added that is embodied in exports can serve to produce final goods and services [element (1) in Figure A2] or it can be used to produce intermediates which are then used domestically (2) or exported (3 + 4). Forward participation refers to the domestic value added in foreign exports (3 + 4), while backward participation refers to the foreign value added in domestic exports (5 + 6). Importantly, backward and forward participation are related: the backward participation of Country A with respect to the world is the sum of the forward participation of all other countries with respect to Country A.19 However, their determinants vary widely (see Kowalski et al., 2015). Much work on GVCs to date uses these gross export decompositions to calculate GVC participation indicators (see, e.g. OECD, 2013; Koopman et al., 2014). The focus on backward or forward participation indicators depends, among other things, on the specific research question and the aimed contribution.20 In this article, we are interested in explaining countries’ capability to export (directly and indirectly) BS value added (the exporting element of GVCs). We, therefore, focus on participation on the seller side, proxied by BS domestic value added in foreign exports—a measure of forward GVC participation in BS.21 We also report robustness checks using as dependent variable BS domestic value added in total exports (elements 1–4 in Figure A2) which proxies the overall capability of the domestic country to create value (Table A7).22 The domestic BS value added in foreign exports (DBSVAE) is identified from an underlying matrix of VAE calculated from the WIOD database as: VAE=V'I-A-1EXP. (1) Where: V′ is an ni × ni matrix with n countries (n = {1, 2, …, 41}) and i sectors of activity (i = {1, 2, …, 35}). It is populated with elements vni=VniXnicapturing the direct value added (V) share of sector i in country n in the output (X) of the industry across the diagonal (with zeros elsewhere). The I-A-1 is the Leontief inverse matrix that captures the inter-linkages within and between sectors across all countries. It is obtained from inverting the product of the subtraction of the technical coefficient matrix (A) with elements ani=Ini,jXnifrom the identity matrix (I). Finally, EXP represents a diagonalized vector of gross exports. The resulting VAE matrix has an ni × cj dimension where n refers to the selling country and c to the buying country (n = c{1, 2, …, 41}) (see Table A5); i to the selling sector and j to the buying sector (i = j {1, 2, …, 35}) (see Table A4). It decomposes the origin of value added embodied in gross exports. The domestic BS element of foreign exports (DBSVAE) is identified from this VAE matrix as the row corresponding to BS (where BS is defined as ISIC sectors 71–74; see Table A4): DBSVAEn=∑jVAEn,c,i,jif n≠c and i=BS. (2) It captures the domestic BS value added that is exported by foreign countries. A manufacturing equivalent of this indicator, DmanufVAE, is also calculated, it uses the same VAE matrix but only takes the sum of the non-domestic rows of the manufacturing sector (see Appendix). 4.2.2 Domestic Hirschman–Linder linkages Our independent variables aim to capture different domestic linkages arising from the intermediate and final demand for BS. One key concern in identifying such linkages is avoiding mechanical associations (spurious correlations) between the dependent and independent variables used. The domestic Hirschman–Linder linkage should capture the strength of the BS linkages with respect to domestic activity in a way that does not introduce mechanical associations with the indicator of engagement in BS GVCs.23 These are avoided by calculating a new set of indicators that focus solely on domestic final demand (DFD) [following a similar method to that in Los et al. (2012) but removing foreign final demand]. The Hirschman–Linder linkage variables therefore capture domestic derived demand linkages net of those that are related to trading activities. The difference between these indicators and the dependent variable lies in the use of final domestic demand rather than gross exports in the Leontief system (i.e. the export vector EXP is now a vector of DFD).24 Two Hirschman–Linder linkage indicators are calculated. Domestic linkages for BS with respect to all activities in the economy (bsDDEM), and with respect to manufacturing activities only (bsDDEMmanuf). In this instance manuf is defined as ISIC sectors 15–37 see Table A4: VADFD=V'I-A-1DFD (3) bsDDEMn=∑jVAFDn,c,i,jif n=c and i=BS (4) bsDDEMmanufn=∑jVAFDn,c,i,jif n=c, i=BS and j=manuf (5) bsDDEM is the row corresponding to BS in the VADFD matrix and includes the use of BS across all sectors in the economy capturing both direct and indirect contributions of this sector to DFD. bsDDEMmanuf is the sum of the domestic BS row over the domestic manufacturing activities in the VADFD matrix. It therefore captures the domestic BS sector value added used by domestic manufacturing sectors to satisfy DFD. This second indicator is used to test whether linkages between BS and manufacturing are particularly relevant. Similar indicators are also calculated for the manufacturing sector (see Appendix). 4.2.3 Domestic Hirschman–Linder linkages of distance-weighted trade partners The extent to which partner countries are exploiting their own domestic Hirschman–Linder linkages might also have an effect on a representative country’s participation in BS GVCs if, for example, these linkages displace or complement country participation in BS GVCs. To account for this we identify the domestic Hirschman–Linder linkages of distance-weighted trade partners for both BS, bsDDEM_par (Equation 6), and manufacturing, manufDDEM_par (see Appendix):25 bsDDEM_parn=∑nbsDDEMn. distancen,c∑ndistancen,c if n≠c. (6) 4.2.4 Potential international spillover or GVC linkages The emergence of GVCs offers countries the possibility of relying on foreign linkages in order to enhance their economic activity. To capture the potential for such spillover effects arising from GVCs we take the mirror image of our dependent variable for partner countries. That is, the DBSVAE_par, the DBSVAE, but of trade partners, weighted by distance to the representative country (Equation 7). A similar indicator is calculated for the manufacturing activities of partner countries—DmanufVAE_par (see Appendix). The indicators are a measure of how other countries engage in GVCs in both BS and manufacturing and are therefore a proxy for the potential to develop foreign GVC linkages. DBSVAE_parn=∑nDBSVAEn. distancen,c∑ndistancen,c if n≠c. (7) 4.2.5 Other control variables We also control for more traditional cost and endowments factors, such as skills, wages, technology, as well as for a set of BS-specific factors, such as trade agreement in services and telecommunication infrastructure. As a proxy for skills, we use the share of direct value added attributed to high-skill labor obtained from the SEAs and the share of public spending education on GDP obtained from Castellacci and Natera (2011). As a proxy for cost we use the hourly wage of high-skilled workers,26 which we compute from the SEAs of the WIOD by dividing the aggregate wage bill associated with high-skilled labor by the amount of hours worked by high-skill workers. We also control for capital per worker taken also from the SEAs. Technology is proxied by R&D over GDP and communication infrastructure by Internet users per 100 people as taken from Castellacci and Natera (2011).27 Finally, as a policy variable more specific to BS, we measure the number of service provisions in a country’s trade agreements (from the DESTA database). Tables A1–A3 in the Appendix describe the different variables used, report some descriptive statistics and the correlation matrix among explanatory variables. One important caveat of the analysis relates to the level of aggregation. As reported in Table A4, the WIOD database captures only 35 sectors, within these there can be wide variations in the composition of value added and therefore the nature of participation in GVCs. For instance, the BS sector includes activities such as renting of machinery, research and development, as well as data processing, legal services, advertising, or packaging activities. Differences in the composition of countries’ BS are therefore not appropriately captured. This also affects the analysis in the manufacturing sectors where specialization within say, motor vehicles can also not differentiate between selling motor bikes versus selling luxury cars. 4.3 Pattern of BS VAE in developed and developing countries We use some of the above detailed indicators to paint a portrait of potential differences between developed and emerging economies in their patterns of participation in BS GVCs and the association between these and their domestic and distance-weighted trade partners’ demand. For developed countries there seems to be a complementarity between DBSVAE and that of partner countries (left panel of Figure 2). Countries with a higher DBSVAE share cluster with larger poles of DBSVAE activity. However, this relationship does not hold for emerging economies thereby providing some prima facie evidence that the links between developing a competitive BS sector in emerging countries might not be contingent on having strong BS neighbors. However, when looking at the link between domestic BS VAE and domestic manufacturing value added in final domestic demand (right panel of Figure 2) we find that for both emerging and developing countries there is a positive relationship. This supports the importance of domestic Hirschman–Linder linkages.28 Figure 2 Open in new tabDownload slide Domestic Business Services Value Added in Foreign Export and domestic and GVC linkages. Source: Own calculations using WIOD. Note: The vertical axis represents the share of domestic business services value added in foreign gross exports. The left panel relates this to the log of BSVA of distance-weighted trade partners to capture international linkages. The right panel then uses the log of business service value added used by domestic manufacturing industries to satisfy final domestic demand to represent domestic linkages. Figure 2 Open in new tabDownload slide Domestic Business Services Value Added in Foreign Export and domestic and GVC linkages. Source: Own calculations using WIOD. Note: The vertical axis represents the share of domestic business services value added in foreign gross exports. The left panel relates this to the log of BSVA of distance-weighted trade partners to capture international linkages. The right panel then uses the log of business service value added used by domestic manufacturing industries to satisfy final domestic demand to represent domestic linkages. Another salient feature of the data relates to the positioning of countries according to their level of development. It is clear from Figure 2 that emerging countries tend to lie below the developed country grouping in terms of their DBSVAE share of gross exports. This might highlight the presence of a developmental pathway in terms of GVC participation where more developed economies predominantly participate in GVCs via exports (as evidenced by the higher domestic value added share of their exports) while emerging economies might tend to initially participate via imports (see López González and Holmes, 2011; Lee et al., 2017). 4.4 Econometric specification We synthesize our hypotheses in the following dynamic model: Where X is a vector of control variables capturing: R&D and education expenditure as a share of GDP; hourly wages; Internet users; service provisions in Free Trade Areas (FTAs); and the share of value added attributed to high-skilled workers (see Table A1) and αi and αt are, respectively, country and time fixed effects (FE). In the estimated equation DBSVAEit is a function of αi, and so is DBSVAEit−1. This makes the Ordinary Least Squares estimator biased and inconsistent. The FE estimator eliminates αi but will be biased for short time-series since DBSVAEit−1 will be correlated with the FE-transformed residual by construction. Omitting the lagged dependent variable and estimating a static FE model could lead to problems of omitted variables and autocorrelated residuals due to the persistence in the series. We, therefore, adopt a dynamic specification and use a Generalized Method of Moments (GMM) estimator. This estimator also helps dealing with potential problems of endogeneity. In particular, we allow domestic BS and domestic manufacturing value added in final domestic demand to be endogenous by instrumenting them with suitable lags of their own first differences. A problem with the original Arellano–Bond estimator is that lagged levels are often poor instruments for first differences, especially for variables that are close to a random walk. Arellano and Bover (1995) described how, if the original equations in levels were added to the system, additional moment conditions could be brought to bear to increase efficiency. In these equations, predetermined and endogenous variables in levels are instrumented with suitable lags of their own first differences. We, therefore, use the system GMM developed by Blundell and Bond (1998) that has been shown to give more robust results than first-differenced GMM in the estimation of models with high persistence. Table A6 in the Appendix reports the results of the robustness checks using the traditional Arellano–Bond estimator. The system GMM gives consistent estimates provided that there is no second order serial correlation among the errors. Therefore, we choose the number of lags in order to remove second order correlation and we report tests for first and second order autocorrelation. 5. Econometric results We turn now to the regression results for the entire sample of countries in Table 1, including both advanced and emerging economies, and then compare the results of the estimations distinguishing between the two groups of countries (see Table A5 for details of the countries included). Table 1. System GMM estimations of BS value added in foreign exports (1a) (2a) (3a) (1b) (2b) (3b) BS value added in foreign exports lag 1 0.672 0.510 0.515 0.957 0.900 0.822 (4.15)*** (3.31)*** (3.27)*** (9.41)*** (8.69)*** (8.48)*** BS value added in foreign exports lag 2 −0.053 −0.053 −0.050 −0.136 −0.156 −0.150 (−0.72) (−0.77) (−0.72) (−2.26)** (−2.74)*** (−2.86)*** BS value added in total final demand 0.352 0.506 0.457 (3.79)*** (5.62)*** (4.65)*** BS value added in manufacturing final demand 0.143 0.167 0.163 (2.59)*** (2.77)*** (3.14)*** BS VA in foreign exports of partners 1.855 1.821 1.076 1.237 (2.78)*** (2.20)** (3.36)*** (2.72)*** BS VA in final demand of partners −0.956 −1.385 −0.400 −1.547 (−3.21)*** (−2.46)** (−2.68)*** (−2.66)*** Manufacturing VA in foreign exports of partners 0.064 0.128 (0.14) (0.34) Manufacturing VA in final demand of partners 0.416 1.004 (0.89) (2.09)** Public expenditure on education over GDP 0.131 0.043 0.089 0.392 0.356 0.406 (0.79) (0.24) (0.53) (2.68)*** (2.56)** (2.99)*** R&D over GDP 0.067 −0.003 −0.014 0.007 −0.028 −0.036 (0.53) (−0.04) (−0.2) (0.14) (−0.93) (−1.53) Hourly wage of high-skilled workers −0.22 −0.427 −0.358 0.007 −0.093 −0.013 (−2.36)** (−4.14)*** (−3.82)*** (0.07) (−1.03) (−0.14) Internet users per 100 people 0.018 0.076 0.051 −0.049 −0.047 −0.062 (0.40) (2.19)** (1.38) (−1.11) (−1.03) (−1.39) Count of provisions stimulating the liberalization of trade in services 0.008 0.006 0.007 0.004 0.004 0.008 (3.61)*** (2.29)** (2.47)** (1.94)* (1.43) (3.52)*** Share of direct VA attributed to high-skilled labor returns 0.17 0.181 0.131 0.131 0.235 0.089 (1.13) (1.17) (0.88) (1.29) (1.84)* (0.64) Capital labor ratio 0.084 0.097 0.118 −0.012 −0.008 0.042 (2.44)** (3.08)*** (3.31)*** (−0.57) (−0.34) (−1.47) Constant −0.569 −3.387 −2.088 −0.06 −1.933 −2.81 (−0.82) (1.67)* (−1.41) (−0.13) (−1.55) (1.79)* Arellano–Bond test for AR(1) −2.73*** −2.27** −2.26** −3.44*** −3.42*** −3.35*** Arellano–Bond test for AR(2) −0.74 −0.60 −0.46 −0.60 −0.60 −0.48 Observations 417 417 417 417 417 417 (1a) (2a) (3a) (1b) (2b) (3b) BS value added in foreign exports lag 1 0.672 0.510 0.515 0.957 0.900 0.822 (4.15)*** (3.31)*** (3.27)*** (9.41)*** (8.69)*** (8.48)*** BS value added in foreign exports lag 2 −0.053 −0.053 −0.050 −0.136 −0.156 −0.150 (−0.72) (−0.77) (−0.72) (−2.26)** (−2.74)*** (−2.86)*** BS value added in total final demand 0.352 0.506 0.457 (3.79)*** (5.62)*** (4.65)*** BS value added in manufacturing final demand 0.143 0.167 0.163 (2.59)*** (2.77)*** (3.14)*** BS VA in foreign exports of partners 1.855 1.821 1.076 1.237 (2.78)*** (2.20)** (3.36)*** (2.72)*** BS VA in final demand of partners −0.956 −1.385 −0.400 −1.547 (−3.21)*** (−2.46)** (−2.68)*** (−2.66)*** Manufacturing VA in foreign exports of partners 0.064 0.128 (0.14) (0.34) Manufacturing VA in final demand of partners 0.416 1.004 (0.89) (2.09)** Public expenditure on education over GDP 0.131 0.043 0.089 0.392 0.356 0.406 (0.79) (0.24) (0.53) (2.68)*** (2.56)** (2.99)*** R&D over GDP 0.067 −0.003 −0.014 0.007 −0.028 −0.036 (0.53) (−0.04) (−0.2) (0.14) (−0.93) (−1.53) Hourly wage of high-skilled workers −0.22 −0.427 −0.358 0.007 −0.093 −0.013 (−2.36)** (−4.14)*** (−3.82)*** (0.07) (−1.03) (−0.14) Internet users per 100 people 0.018 0.076 0.051 −0.049 −0.047 −0.062 (0.40) (2.19)** (1.38) (−1.11) (−1.03) (−1.39) Count of provisions stimulating the liberalization of trade in services 0.008 0.006 0.007 0.004 0.004 0.008 (3.61)*** (2.29)** (2.47)** (1.94)* (1.43) (3.52)*** Share of direct VA attributed to high-skilled labor returns 0.17 0.181 0.131 0.131 0.235 0.089 (1.13) (1.17) (0.88) (1.29) (1.84)* (0.64) Capital labor ratio 0.084 0.097 0.118 −0.012 −0.008 0.042 (2.44)** (3.08)*** (3.31)*** (−0.57) (−0.34) (−1.47) Constant −0.569 −3.387 −2.088 −0.06 −1.933 −2.81 (−0.82) (1.67)* (−1.41) (−0.13) (−1.55) (1.79)* Arellano–Bond test for AR(1) −2.73*** −2.27** −2.26** −3.44*** −3.42*** −3.35*** Arellano–Bond test for AR(2) −0.74 −0.60 −0.46 −0.60 −0.60 −0.48 Observations 417 417 417 417 417 417 Note: Year dummies included but not reported. Standard errors are heteroscedasticity robust. *, **, and *** indicate statistical significance at 10%, 5%, and 1%, respectively. Open in new tab Table 1. System GMM estimations of BS value added in foreign exports (1a) (2a) (3a) (1b) (2b) (3b) BS value added in foreign exports lag 1 0.672 0.510 0.515 0.957 0.900 0.822 (4.15)*** (3.31)*** (3.27)*** (9.41)*** (8.69)*** (8.48)*** BS value added in foreign exports lag 2 −0.053 −0.053 −0.050 −0.136 −0.156 −0.150 (−0.72) (−0.77) (−0.72) (−2.26)** (−2.74)*** (−2.86)*** BS value added in total final demand 0.352 0.506 0.457 (3.79)*** (5.62)*** (4.65)*** BS value added in manufacturing final demand 0.143 0.167 0.163 (2.59)*** (2.77)*** (3.14)*** BS VA in foreign exports of partners 1.855 1.821 1.076 1.237 (2.78)*** (2.20)** (3.36)*** (2.72)*** BS VA in final demand of partners −0.956 −1.385 −0.400 −1.547 (−3.21)*** (−2.46)** (−2.68)*** (−2.66)*** Manufacturing VA in foreign exports of partners 0.064 0.128 (0.14) (0.34) Manufacturing VA in final demand of partners 0.416 1.004 (0.89) (2.09)** Public expenditure on education over GDP 0.131 0.043 0.089 0.392 0.356 0.406 (0.79) (0.24) (0.53) (2.68)*** (2.56)** (2.99)*** R&D over GDP 0.067 −0.003 −0.014 0.007 −0.028 −0.036 (0.53) (−0.04) (−0.2) (0.14) (−0.93) (−1.53) Hourly wage of high-skilled workers −0.22 −0.427 −0.358 0.007 −0.093 −0.013 (−2.36)** (−4.14)*** (−3.82)*** (0.07) (−1.03) (−0.14) Internet users per 100 people 0.018 0.076 0.051 −0.049 −0.047 −0.062 (0.40) (2.19)** (1.38) (−1.11) (−1.03) (−1.39) Count of provisions stimulating the liberalization of trade in services 0.008 0.006 0.007 0.004 0.004 0.008 (3.61)*** (2.29)** (2.47)** (1.94)* (1.43) (3.52)*** Share of direct VA attributed to high-skilled labor returns 0.17 0.181 0.131 0.131 0.235 0.089 (1.13) (1.17) (0.88) (1.29) (1.84)* (0.64) Capital labor ratio 0.084 0.097 0.118 −0.012 −0.008 0.042 (2.44)** (3.08)*** (3.31)*** (−0.57) (−0.34) (−1.47) Constant −0.569 −3.387 −2.088 −0.06 −1.933 −2.81 (−0.82) (1.67)* (−1.41) (−0.13) (−1.55) (1.79)* Arellano–Bond test for AR(1) −2.73*** −2.27** −2.26** −3.44*** −3.42*** −3.35*** Arellano–Bond test for AR(2) −0.74 −0.60 −0.46 −0.60 −0.60 −0.48 Observations 417 417 417 417 417 417 (1a) (2a) (3a) (1b) (2b) (3b) BS value added in foreign exports lag 1 0.672 0.510 0.515 0.957 0.900 0.822 (4.15)*** (3.31)*** (3.27)*** (9.41)*** (8.69)*** (8.48)*** BS value added in foreign exports lag 2 −0.053 −0.053 −0.050 −0.136 −0.156 −0.150 (−0.72) (−0.77) (−0.72) (−2.26)** (−2.74)*** (−2.86)*** BS value added in total final demand 0.352 0.506 0.457 (3.79)*** (5.62)*** (4.65)*** BS value added in manufacturing final demand 0.143 0.167 0.163 (2.59)*** (2.77)*** (3.14)*** BS VA in foreign exports of partners 1.855 1.821 1.076 1.237 (2.78)*** (2.20)** (3.36)*** (2.72)*** BS VA in final demand of partners −0.956 −1.385 −0.400 −1.547 (−3.21)*** (−2.46)** (−2.68)*** (−2.66)*** Manufacturing VA in foreign exports of partners 0.064 0.128 (0.14) (0.34) Manufacturing VA in final demand of partners 0.416 1.004 (0.89) (2.09)** Public expenditure on education over GDP 0.131 0.043 0.089 0.392 0.356 0.406 (0.79) (0.24) (0.53) (2.68)*** (2.56)** (2.99)*** R&D over GDP 0.067 −0.003 −0.014 0.007 −0.028 −0.036 (0.53) (−0.04) (−0.2) (0.14) (−0.93) (−1.53) Hourly wage of high-skilled workers −0.22 −0.427 −0.358 0.007 −0.093 −0.013 (−2.36)** (−4.14)*** (−3.82)*** (0.07) (−1.03) (−0.14) Internet users per 100 people 0.018 0.076 0.051 −0.049 −0.047 −0.062 (0.40) (2.19)** (1.38) (−1.11) (−1.03) (−1.39) Count of provisions stimulating the liberalization of trade in services 0.008 0.006 0.007 0.004 0.004 0.008 (3.61)*** (2.29)** (2.47)** (1.94)* (1.43) (3.52)*** Share of direct VA attributed to high-skilled labor returns 0.17 0.181 0.131 0.131 0.235 0.089 (1.13) (1.17) (0.88) (1.29) (1.84)* (0.64) Capital labor ratio 0.084 0.097 0.118 −0.012 −0.008 0.042 (2.44)** (3.08)*** (3.31)*** (−0.57) (−0.34) (−1.47) Constant −0.569 −3.387 −2.088 −0.06 −1.933 −2.81 (−0.82) (1.67)* (−1.41) (−0.13) (−1.55) (1.79)* Arellano–Bond test for AR(1) −2.73*** −2.27** −2.26** −3.44*** −3.42*** −3.35*** Arellano–Bond test for AR(2) −0.74 −0.60 −0.46 −0.60 −0.60 −0.48 Observations 417 417 417 417 417 417 Note: Year dummies included but not reported. Standard errors are heteroscedasticity robust. *, **, and *** indicate statistical significance at 10%, 5%, and 1%, respectively. Open in new tab We start from the simplest specification, where we include only variables related to the domestic economy (specifications 1). Here, we distinguish between the broader measure of domestic Hirschman–Linder linkages capturing the use of BS across all sectors—bsDDEM (specification 1a) and the more targeted manufacturing domestic Hirschman–Linder linkages, identifying the use of BS by manufacturing industries only—bsDDEMmanuf (specification 1b). We then add the international dimension through the BS value added in final domestic demand and the value of BS forward participation of distance-weighted trade partners (specifications 2a and 2b). The first variable captures the Hirschman–Linder linkages in partner countries. This variable can have a positive or negative effect, depending on whether domestic Hirschman–Linder linkages in trade partners act as an (additional) international derived demand for BS or, rather, if a competition effect dominates and displaces participation in BS GVCs. The second variable (value of BS forward participation of distance-weighted trade partners) captures whether there is a “spillover” or GVC linkage effect. Bahar et al. (2014) argued, for the case of exports, that economies can benefit from knowledge spillovers ensuing from geographical proximity to countries having a comparative advantage in same products. More recently, López González (2016) showed how countries can increase their domestic export capacity by relying on foreign value added through GVC linkages. A positive coefficient of this variable would therefore suggest the presence of spillover or GVC linkages effect, while a negative coefficient would indicate a further displacement effect. We also estimate a full specification that includes the BS and manufacturing value added in final domestic demand and BS forward GVC participation of distance-weighted trade partners (specifications 3a and 3b). This allows us to capture the role of cross-sectoral international linkages between BS and manufacturing. Table 1 shows the positive effect of both total domestic Hirschman–Linder linkages (proxied by BS value added in total domestic demand) and manufacturing-based ones (proxied by BS value added in manufacturing domestic demand) in explaining BS forward GVC participation. This confirms the importance of a domestic Hirschman–Linder effect. The elasticity is higher for total domestic linkages (the short and long run elasticities are 0.46 and 0.94, respectively, in the full specification) than for manufacturing-based ones (0.16 and 0.49, respectively). This is not surprising, as the total linkages comprise the demand for BS coming from a larger number of sectors and also includes own demand or the direct linkage of the BS sector: on average, manufacturing-based linkages account for less than 10% of total linkages. The evidence shows the importance of domestic Hirschman–Linder linkages driving a wider participation in BS GVCs. The specific role played by manufacturing-based linkages for BS forward GVC participation is also in line with the evidence of “servicification” of manufacturing (Pilat and Wölfl, 2005; Pilat et al., 2006; Kommerskollegium, 2012; Lanz and Maurer, 2015). The result is also consistent with the finding of the importance of manufacturing demand for regional specialization in BS (Meliciani and Savona, 2014) and for attracting BS foreign direct investments (Castellani et al., 2014). Also, it might offer support to the argument of “premature de-industrialization” (Rodrik, 2015) mentioned earlier, when a (developing) country aims to increase the global competitiveness of BS. A second, notable result is the negative impact of BS value added in final demand of distance-weighted trade partners. It suggests the presence of competition effects among countries in providing BS showing how domestic demand linkages might dominate over foreign demand. At the same time, there exist complementarities (positive spillovers) in BS forward GVC participation with respect to neighbor partner countries. That is, when countries are strong suppliers of BS within GVCs (as proxied by their forward participation in BS GVCs), neighboring countries can benefit from positive spillovers from GVC linkages. The net effect is ambiguous and depends on the strength of the direct negative effect and the indirect positive effect (partner countries internal demand positively affects their participation in BS GVCs, which in turn positively affects one country’s BS forward GVC participation).29 Finally, when introducing simultaneously BS and manufacturing value added in final domestic demand of distance-weighted trade partners (specification 3), the former has a displacing effect while the latter has either no effect (specification 3a) or a positive effect (specification 3b). This shows that competition effects prevail within the same sector, that is, being surrounded by countries with high levels of direct and indirect domestic demand for BS has a negative impact on BS exports from the domestic country, but there can be complementarities between sectors. Looking at control variables, unsurprisingly the most stable determinant of BS forward GVC participation is the count of service provisions within trade agreements attesting to their importance in developing BS export capacity. On the other hand, public spending on education, the availability of high-skilled labor, the capital labor ratio, Internet users, and labor costs are significant only in some specifications while R&D is never significant. Table A5 in the Appendix reports robustness checks using the Arellano–Bond GMM estimator. Result are very similar, although the impact of manufacturing domestic value added in final demand of partners is negative pointing to an additional displacing effect. Table 2 shows the results of the full specification (specification 3) on the subsamples of advanced and emerging economies (columns 1 and 2, respectively). It also separates manufacturing and BS forward GVC participation to identify differences in the results across sectors (columns 3 and 4). This allows capturing whether the importance of domestic Hirschman–Linder linkages is specific to BS or if these apply also to manufacturing. In addition, it allows us to assess how the interplay between domestic and international linkages affects manufacturing relative to BS. We report only estimates including total, rather than manufacturing only, Hirschman–Linder linkages.30 Table 2. System GMM estimations of BS and manufacturing value added in foreign exports for advanced and emerging economies Business services Manufacturing Emerging Advanced Emerging Advanced BS value added in foreign exports lag 1 0.532 0.515 (2.72)*** (9.29)*** BS value added in foreign exports lag 2 −0.044 0.059 (−0.46) (1.25) BS value added in total final demand 0.38 0.232 (3.82)*** (4.45)*** Manufacturing VA in foreign exports lag 1 0.441 0.755 (2.86)*** (6.46)*** Manufacturing VA in foreign exports lag 2 0.007 0.087 (0.22) (0.8) Manufacturing value added in total final demand 0.472 0.076 (5.43)*** (2.55)** BS VA in foreign exports of partners 1.968 1.369 −1.262 −0.379 (1.5) (5.42)*** (−2.21)** (−3.04)*** Manufacturing VA in foreign exports of partners −0.212 0.157 3.511 1.319 (−0.19) (1.07) (3.60)*** (7.71)*** BS VA in final demand of partners −2.028 −0.468 −1.835 −0.776 (2.71)*** (2.58)*** (−2.97)*** (−3.82)*** Manufacturing VA in final demand of partners 1.023 −0.034 0.341 0.358 (1.51) (−0.17) (0.7) (1.75)* Public expenditure on education over GDP −0.051 0.137 0.071 −0.014 (−0.21) (1.25) (0.43) (−0.3) R&D over GDP −0.077 −0.021 0.008 −0.125 (−1.73)* (−0.28) (0.2) (−2.22)** Hourly wage of high-skilled workers −0.357 −0.35 −0.272 −0.156 (−2.50)** (−3.26)*** (−5.50)*** (−2.57)** Internet users per 100 people −0.025 −0.038 −0.11 0.006 (−0.29) (−1.27) (−1.05) (0.25) Count of provisions stimulating the liberalization of trade in services 0.004 0.00 0.005 −0.002 (1.17) (0.08) (1.27) (−1.31) Share of direct VA attributed to high-skilled labor returns 0.207 0.12 0.257 0.106 (1.01) (1.19) (1.64) (1.42) Capital labor ratio 0.142 0.31 0.041 0.229 (2.50)** (2.05)** (0.63) (3.00)*** Constant −1.083 −2.875 −3.212 −2.483 (−0.47) (−2.67)*** (−1.5) (−3.85)*** Arellano–Bond test for AR(1) −1.49 −2.14** −1.53 −2.43** Arellano–Bond test for AR(2) −1.25 −0.26 −0.11 −1.34 Observations 165 252 165 252 Business services Manufacturing Emerging Advanced Emerging Advanced BS value added in foreign exports lag 1 0.532 0.515 (2.72)*** (9.29)*** BS value added in foreign exports lag 2 −0.044 0.059 (−0.46) (1.25) BS value added in total final demand 0.38 0.232 (3.82)*** (4.45)*** Manufacturing VA in foreign exports lag 1 0.441 0.755 (2.86)*** (6.46)*** Manufacturing VA in foreign exports lag 2 0.007 0.087 (0.22) (0.8) Manufacturing value added in total final demand 0.472 0.076 (5.43)*** (2.55)** BS VA in foreign exports of partners 1.968 1.369 −1.262 −0.379 (1.5) (5.42)*** (−2.21)** (−3.04)*** Manufacturing VA in foreign exports of partners −0.212 0.157 3.511 1.319 (−0.19) (1.07) (3.60)*** (7.71)*** BS VA in final demand of partners −2.028 −0.468 −1.835 −0.776 (2.71)*** (2.58)*** (−2.97)*** (−3.82)*** Manufacturing VA in final demand of partners 1.023 −0.034 0.341 0.358 (1.51) (−0.17) (0.7) (1.75)* Public expenditure on education over GDP −0.051 0.137 0.071 −0.014 (−0.21) (1.25) (0.43) (−0.3) R&D over GDP −0.077 −0.021 0.008 −0.125 (−1.73)* (−0.28) (0.2) (−2.22)** Hourly wage of high-skilled workers −0.357 −0.35 −0.272 −0.156 (−2.50)** (−3.26)*** (−5.50)*** (−2.57)** Internet users per 100 people −0.025 −0.038 −0.11 0.006 (−0.29) (−1.27) (−1.05) (0.25) Count of provisions stimulating the liberalization of trade in services 0.004 0.00 0.005 −0.002 (1.17) (0.08) (1.27) (−1.31) Share of direct VA attributed to high-skilled labor returns 0.207 0.12 0.257 0.106 (1.01) (1.19) (1.64) (1.42) Capital labor ratio 0.142 0.31 0.041 0.229 (2.50)** (2.05)** (0.63) (3.00)*** Constant −1.083 −2.875 −3.212 −2.483 (−0.47) (−2.67)*** (−1.5) (−3.85)*** Arellano–Bond test for AR(1) −1.49 −2.14** −1.53 −2.43** Arellano–Bond test for AR(2) −1.25 −0.26 −0.11 −1.34 Observations 165 252 165 252 *, **, and *** indicate statistical significance at 10%, 5%, and 1%, respectively. Open in new tab Table 2. System GMM estimations of BS and manufacturing value added in foreign exports for advanced and emerging economies Business services Manufacturing Emerging Advanced Emerging Advanced BS value added in foreign exports lag 1 0.532 0.515 (2.72)*** (9.29)*** BS value added in foreign exports lag 2 −0.044 0.059 (−0.46) (1.25) BS value added in total final demand 0.38 0.232 (3.82)*** (4.45)*** Manufacturing VA in foreign exports lag 1 0.441 0.755 (2.86)*** (6.46)*** Manufacturing VA in foreign exports lag 2 0.007 0.087 (0.22) (0.8) Manufacturing value added in total final demand 0.472 0.076 (5.43)*** (2.55)** BS VA in foreign exports of partners 1.968 1.369 −1.262 −0.379 (1.5) (5.42)*** (−2.21)** (−3.04)*** Manufacturing VA in foreign exports of partners −0.212 0.157 3.511 1.319 (−0.19) (1.07) (3.60)*** (7.71)*** BS VA in final demand of partners −2.028 −0.468 −1.835 −0.776 (2.71)*** (2.58)*** (−2.97)*** (−3.82)*** Manufacturing VA in final demand of partners 1.023 −0.034 0.341 0.358 (1.51) (−0.17) (0.7) (1.75)* Public expenditure on education over GDP −0.051 0.137 0.071 −0.014 (−0.21) (1.25) (0.43) (−0.3) R&D over GDP −0.077 −0.021 0.008 −0.125 (−1.73)* (−0.28) (0.2) (−2.22)** Hourly wage of high-skilled workers −0.357 −0.35 −0.272 −0.156 (−2.50)** (−3.26)*** (−5.50)*** (−2.57)** Internet users per 100 people −0.025 −0.038 −0.11 0.006 (−0.29) (−1.27) (−1.05) (0.25) Count of provisions stimulating the liberalization of trade in services 0.004 0.00 0.005 −0.002 (1.17) (0.08) (1.27) (−1.31) Share of direct VA attributed to high-skilled labor returns 0.207 0.12 0.257 0.106 (1.01) (1.19) (1.64) (1.42) Capital labor ratio 0.142 0.31 0.041 0.229 (2.50)** (2.05)** (0.63) (3.00)*** Constant −1.083 −2.875 −3.212 −2.483 (−0.47) (−2.67)*** (−1.5) (−3.85)*** Arellano–Bond test for AR(1) −1.49 −2.14** −1.53 −2.43** Arellano–Bond test for AR(2) −1.25 −0.26 −0.11 −1.34 Observations 165 252 165 252 Business services Manufacturing Emerging Advanced Emerging Advanced BS value added in foreign exports lag 1 0.532 0.515 (2.72)*** (9.29)*** BS value added in foreign exports lag 2 −0.044 0.059 (−0.46) (1.25) BS value added in total final demand 0.38 0.232 (3.82)*** (4.45)*** Manufacturing VA in foreign exports lag 1 0.441 0.755 (2.86)*** (6.46)*** Manufacturing VA in foreign exports lag 2 0.007 0.087 (0.22) (0.8) Manufacturing value added in total final demand 0.472 0.076 (5.43)*** (2.55)** BS VA in foreign exports of partners 1.968 1.369 −1.262 −0.379 (1.5) (5.42)*** (−2.21)** (−3.04)*** Manufacturing VA in foreign exports of partners −0.212 0.157 3.511 1.319 (−0.19) (1.07) (3.60)*** (7.71)*** BS VA in final demand of partners −2.028 −0.468 −1.835 −0.776 (2.71)*** (2.58)*** (−2.97)*** (−3.82)*** Manufacturing VA in final demand of partners 1.023 −0.034 0.341 0.358 (1.51) (−0.17) (0.7) (1.75)* Public expenditure on education over GDP −0.051 0.137 0.071 −0.014 (−0.21) (1.25) (0.43) (−0.3) R&D over GDP −0.077 −0.021 0.008 −0.125 (−1.73)* (−0.28) (0.2) (−2.22)** Hourly wage of high-skilled workers −0.357 −0.35 −0.272 −0.156 (−2.50)** (−3.26)*** (−5.50)*** (−2.57)** Internet users per 100 people −0.025 −0.038 −0.11 0.006 (−0.29) (−1.27) (−1.05) (0.25) Count of provisions stimulating the liberalization of trade in services 0.004 0.00 0.005 −0.002 (1.17) (0.08) (1.27) (−1.31) Share of direct VA attributed to high-skilled labor returns 0.207 0.12 0.257 0.106 (1.01) (1.19) (1.64) (1.42) Capital labor ratio 0.142 0.31 0.041 0.229 (2.50)** (2.05)** (0.63) (3.00)*** Constant −1.083 −2.875 −3.212 −2.483 (−0.47) (−2.67)*** (−1.5) (−3.85)*** Arellano–Bond test for AR(1) −1.49 −2.14** −1.53 −2.43** Arellano–Bond test for AR(2) −1.25 −0.26 −0.11 −1.34 Observations 165 252 165 252 *, **, and *** indicate statistical significance at 10%, 5%, and 1%, respectively. Open in new tab The results show that the positive role of domestic Hirschman–Linder linkages for BS forward GVC participation holds for both advanced and emerging economies. The elasticity is, however, higher in the case of emerging countries (0.38 versus 0.23 for the short run elasticity and 0.81 and 0.47 for the long run elasticity), suggesting the stronger need for emerging countries to develop an internal final and intermediate demand for BS to export such services (indirectly). The most notable difference between advanced and emerging economies is the lack of significance, for emerging countries, of distance-weighted trade partners’ BS forward GVC participation. This suggests, in conjunction with the negative impact of BS value added in domestic demand of distance-weighted trade partners that, for emerging economies, international GVC linkages do not facilitate domestic value creation in BS GVCs. Therefore, for emerging countries, contrary to common wisdom, it seems even more important to develop domestic capabilities in sectors that are backward-linked with BS in order to create domestic value in BS GVCs. In the absence of such capabilities, having neighbor partners with high levels of BS value added in final demand might only have a displacing effect. This last result is in contrast with those obtained when looking at the determinants of forward GVC participation in manufacturing (columns 3 and 4). Domestic Hirschman–Linder linkages play an important role also in the case of manufacturing, especially for emerging countries. Moreover, as in the case for BS, there is a negative competition effect (the manufacturing value added in DFD of distance-weighted trade partners is negative and significant). However, unlike the case of BS, the evidence shows the existence of complementary/spillover effects arising from a strong potential supply of manufacturing value added from neighboring countries, that is, being surrounded by countries with a high forward GVC participation in manufacturing increases a country’s chances to increase its own participation in manufacturing GVCs. This suggests that proximity to large headquarter economies with a high level of manufacturing value added in foreign exports helps developing economies create domestic value added in manufacturing GVCs (Baldwin and López González, 2014). This is not the case for BS in emerging countries implying that there are key differences in the determinants of domestic value added creation in manufacturing and BS GVCs. It suggests that Baldwin’s (2011) conjectures that countries can rely on foreign linkages to develop domestic capacity might be true for manufacturing, but not for developing BS value added in emerging countries. These results are not in contrast with the evidence that some developing countries relied on the GVC to initiate their BS exports31 (see, e.g., the case of India’s IT service sector, Lee et al., 2014). 6. Concluding remarks This article has contributed to the literature on GVCs by putting forward and empirically testing the conjecture that (direct and indirect) domestic demand for BS affects the capability of countries to engage in BS GVCs. The question has been framed within the recent debate on the development opportunities of joining a BS GVC, sparked in both academic and policy circles. More generally, we argue that part of this debate is linked to the importance of developing domestic capacity and capabilities in sectors that are crucial to facilitate processes and achieve outcomes of sectoral and technological upgrading, to fully gain from insertion in GVCs. Recent developments in international trade theory (Antràs et al., 2006; Grossman and Rossi-Hansberg, 2006, 2008,, 2012; Costinot et al., 2013; Baldwin and Robert-Nicoud, 2014) suggest that the emergence of GVC has changed the object of comparative advantage—now based on tasks rather than products, whereas the determinants of it, i.e. relative endowment of factors, skills, and factors’ prices remain largely unchanged. From an empirical perspective, scholars have argued that proximity to headquarters countries, which tend to offshore the low value adding segments of production to neighboring factor economies, might be an important driver of participation in manufacturing GVCs (Baldwin, 2011; Baldwin and López González, 2015). Along these lines, qualitative evidence on country cases that supports the idea of favoring GVC in BS as an opportunity for development has emerged (Gereffi and Fernandez-Stark, 2010; Hernández et al., 2014a, b). This article has proposed a different framework to explain the emergence of BS GVCs, and drawn different implications in terms of conditions to participating in BS GVCs in the absence of a core domestic demand and presence of backward-linked sectors. Our results show that the higher the domestic presence in BS backward-linked industries, and particularly manufacturing sectors, the higher the propensity to participate in BS GVCs. This is in line with what Linder claimed to be the case for the composition of final domestic demand favoring trade in similar sectors. In particular, our findings show that our Hirschman–Linder hypothesis holds for the (WIOD) sample of developed and emerging countries and, indeed, for the subsample of emerging countries only. However, when we look at whether participation in BS GVC is driven by domestic demand of close trade partners, we find that this has a negative effect. This is at odds with the idea that countries can enter BS GVCs by relying exclusively or mainly on demand coming from trade partner countries, regardless of their own domestic productive structure. This result emerges more clearly for emerging countries, for which it seems that it is even more important to develop domestic capabilities in sectors that are vertically integrated with BS in order to enter BS GVCs. Although the investigation of how the determinants of participation in GVCs change as countries grow is out of the scope of this article, our findings are in line with the conjectures put forward by Lee et al. (2017), Lee and Malerba (2017), Baldwin (2012), and López González and Holmes (2011), who have looked at the relationship between levels of development and participation in GVCs. According to these, countries tend to predominantly rely on foreign inputs at early stages of development (high intensity of backward participation) and predominantly contribute to foreign exports at later stages of development (high intensity of forward participation). Further analyses based on data that cover also low income countries might shed more light on this relevant issue. The descriptive evidence on cases such as (a few states in) India, the Philippines, or Uruguay, whereby trade specialization and participation in service GVCs has been mainly driven by external demand, offer counter-evidence to our findings.32 However, recent developments in measurement of trade specialization in terms of trade in value added rather than gross exports, seem to put these claims largely in perspective [see mainly Koopman et al., 2014, but also Banga, 2014; Francois et al., 2015; Miroudot and Cadestin, 2017]. These are indeed interesting cases to observe over the next decades, to assess their long-term development paths. Given the link between domestic and trade specialization, and in a context where the debate is putting back to the forefront the risks of a “premature de-industrialization” (Rodrik, 2015), it is all the more relevant to provide generalizable evidence on this phenomenon. Indeed, empirical evidence in Dasgupta and Singh (2005,, 2006), Bah (2011), and Di Meglio et al. (2018) shows that most Latin American and African countries are de-industrializing at levels of aggregate incomes that are much lower than those at which developed countries started to shift to services, with consequences that at best are a slowdown of aggregate growth and employment. This literature rarely takes into account the role of global trade, particularly how the changes in domestic demand and sectoral structure affect the opportunities to benefit from trade and how this is conducive to upgrading and economic development, with notable exceptions (McMillan et al., 2014; Rodrik, 2015). There are two main directions worth pursuing in our research agenda. The first one is to provide a better conceptual and empirical ground to understand the impact of GVC participation on the polarization of income, both within and between countries.33 Assessing these processes by means of quantitative analysis allows contributing to a different, yet established stream of scholarship, interested in the distribution of rents along the value chains. Kaplinsky (2000), for instance, points to the sources of income inequality linked to the spatial distribution of production activities between headquarters and factory economies. Much of the unequal distribution of the gains resulting from being part of GVCs is attributable to issues of GVC governance (Kaplinsky, 2000; Gereffi et al., 2005). More broadly, it would be important to disentangle the inevitable nexus between being a headquarter versus a factory economy, and give empirical content to the dynamics of rent appropriation along different portions of the value chain. It is in the dynamics of this nexus that different development scenarios might arise for emerging countries. The second, related, one is providing an explicit conceptual and empirical link between GVC scholarship and the debate over industrial policy for development (Lin, 2012; Stiglitz et al., 2013). One of the relevant questions to this debate is, for instance, whether entering GVCs in BS allows or speeds up the processes of technological upgrading of domestic manufacturing that BS have been found to facilitate internally. Informing this debate requires generalizable, longitudinal, and cross-country empirical evidence on the extent of these phenomena, to track the “upgrading” process and derive implications in terms of industrial policy. As a consequence, the policy implications based on our evidence are necessarily tentative here. Overall, the evidence shown here calls for some caution on the opportunities to favour participation in BS GVCs as a development strategy. In particular, it warns countries that relying first and foremost, let alone exclusively, on foreign demand, while overlooking efforts to build capabilities by developing domestic backward-linked industries to BS, might not result in gaining from GVC participation, or even in lock-ins in low value added segments of GVCs. Such efforts would require a coherent set of innovation and industrial policy in emerging countries, that would need to achieve “quality” industrialization (e.g. in high-value intermediates) rather than simply augmenting their production capacity to serve foreign demand. Similarly, although mainly focusing on regional development in advanced countries, the literature on related and unrelated variety has pointed to the importance of the domestic structure of related activities to tackle regional development unbalances (Boschma and Iammarino, 2009; Boschma and Frenken, 2011). Based on our evidence, and drawing on the literatures on GVCs, technological upgrading and related variety, we propose tentative policy implications to achieve domestic structural change that aligns to a ‘quality’ participation in GVCs. First, countries should build upon their initial specialization to identify related (backward and forward linked) sectors, that represent feasible pathways for structural transformation. This view has been largely supported in the economic geography literature (Frenken et al., 2007) but also, more recently, by the product space framework (Hausmann et al., 2007; Hidalgo et al., 2007). This essentially puts forward the argument that the ability of countries to transition from one set of activities to another is based on their existing capabilities, the nestedness of their specialization and relative positions in global trade networks. However, capabilities building as a policy goal might need to go beyond the density of countries’ product space and requires a direct, deliberate effort to support technological upgrading via targeted innovation policies (Ciarli et al., 2018). A second step should therefore entail support of traditional technology transfer during the initial stages of development, assuming that this fits the local characteristics and contributes to the development of domestic capabilities. Currently, there is little reflection—mostly based on case studies—on whether inclusion in GVCs, let alone BS GVCs, facilitates technological upgrading via some form of transfer (Fu et al., 2011). Again, this would require a dedicated effort to identify technological opportunities that best fit the initial indigenous capability for technological upgrading, which is core to the quality and direction of structural change and development (Bell, 2009; Barrientos et al., 2011; Fu et al., 2011; Ciarli et al., 2018). At any rate, forms of learning linked to GVCs participation would require a minimal, critical mass of competitive domestic sectors, to maximize the renting positions linked to serving foreign demand (Kaplinsky, 2019, forthcoming), and facilitate strengthening of domestic linkages and further upgrading. This argument is far from discouraging tout court participation in BS GVC at the initial stages of development. Rather, we suggest that joining BS GVC can indeed be an opportunity for emerging countries, but that in order to avoid being locked in low value added activities, they might need to develop closely related (backward and forward linked) domestic sectors. Recent evidence seems to support these suggestions. A recent OECD report (OECD, 2017) shows that, despite India being considered a key services exporter and China considered a manufacturing hub, the services employment content of GDP has increased much faster in China than in India. Arguably, “a supporting services sector has been essential, but largely overlooked part of China’s industrial development” (OECD, 2017: 13). Along the same lines, data reported in the GVC Development Report (World Bank et al., 2017: 11) show that: “Emerging market economies that are major exporters of manufactured products have somewhat lower but still surprisingly high services shares. For example, China, Mexico, and Vietnam have very little direct export of services, but in value added terms about 40% of their exports come from services. They can expect that share to rise as they develop further and move up the value chain.” In addition: “India offers an example of ‘premature deindustrialization’, where direct exports of business services are high but indirect exports are low, perhaps because of the relative weakness of goods sectors” (World Bank et al., 2017: 152). We trust that the present work, alongside recent OECD evidence, not only signposts a fruitful direction for empirical efforts but also informs concerted directions of policy action, that coherently addresses the need for domestic technological upgrading and sectoral transformation while ensuring a gainful insertion in GVCs for emerging countries. Footnotes 1 BS include ICT-related services [International Standard Industrial Classification (ISIC) code 72], Research & Development (73), and all intermediate services such as engineering, technical consultancy, legal aid, and other business services (74). See Table A4 in the Appendix for a detailed list of sectors. 2 There is a flourishing literature on the determinants of GVC participation in developing countries (see Kowalski et al., 2015; Taglioni and Wrinkler, 2016). 3 We articulate the Hirschman–Linder hypothesis more at length in Section 2.3. Interestingly, albeit from a very different perspective, our conjecture resonates with what has most recently been put forward by Baldwin and Venables (2015) and in line with what Poncet and Starosta de Waldemar (2013) find. 4 Differently from these papers the aim of our analysis is not to study pathways that emerging and developing countries take to develop domestic capacity and participate in GVCs, such as those outlined in the in-out-in conjecture of Lee et al. (2017). Rather, we focus on countries that have already reached a certain level of development (emerging) and we look at the importance of domestic linkages to create domestic value added in business services exports. Identifying what countries should do first, or what type of policy would be most helpful at different levels of development, is an important issue which we hope to turn to in future work. 5 The term was coined by Baldwin (2006) and then used in Baldwin (2011) and Baldwin and López González (2015). In Baldwin and López González (2015), headquarter economies are identified as those that have strong forward participation links with emerging and developing nations located in close proximity 6 In terms of gains for developing countries, as Baldwin (2011: 33) puts it: “The 2nd unbundling made industrialization less meaningful. Before the 2nd unbundling a nation had to have a deep and wide industrial base before it could export, e.g. car engines. Exporting engines was a sign of victory. Now it is a sign that the nation is located in a particular segment of an international value chain.” This view, however, abstracts from the risk of a specialisation trap in the low-end segments of the value chain and from considerations related to the conditions that ensure successful upgrading. 7 The entries in Figure 1 mark the value of the row nations sales of BS to the column nation divided by global trade in BS value added in exports. 8 The term was coined by Baldwin (2006) and then used in Baldwin (2011) and Baldwin and López González (2015). In Baldwin and López González (2015), headquarter economies are identified as those that have strong forward participation links with emerging and developing nations located in close proximity. 9 A seminal contribution on the topic remains that by Kaldor (1966), followed by Baumol (1967) and Fuchs (1968). 10 Classical contributions to the opposite stand—i.e. the optimism toward the progress and “third industrial revolution” are (Fourastié 1949; Bell, 2009). 11 More specifically, concerns about tertiarization have been cyclical: a further evidence of this is the very recent “re-assessment” of the benefits of industry—most likely due to the second public outrage following the tarnish consequences of the latest global financial crisis—as reported in the EC 2013 Competitiveness Report “Towards Knowledge-Driven Re-industrialisation” or the Juncker Plan in Europe aiming at an “industrial renaissance” of Europe. 12 “The input-provision, derived demand, or backward linkage effects, i.e. every non-primary economic activity, will induce attempts to supply through domestic production the inputs needed in that activity. The output-utilization or forward linkage effects, i.e. every activity that does not by its nature cater exclusively to final demands, will induce attempts to utilize its outputs as inputs in some new activities” (Hirschman, 1958). 13 These intuitions have on some occasions been taken up and operationalized in the literature (Jones, 1976); see also, more recently, Hausmann et al. (2008), although it is out of the scope of this paper to go more in depth into these. 14 We owe to Martin Bell reflections on structural change within Hirschman’s work. 15 Interestingly, in the same essay Burenstam Linder (1961: 90) states: “We have now given three reasons which lend support to the assertion that a particular good will not be produced at a comparative advantage unless there is a domestic market for the good. We have argued that (i) it is unlikely that an entrepreneur will ever think of satisfying a need that does not exist at home; (ii) even if this alien need was seen, the basically correct product to fill it might not be conceived of; and (iii) even if the basically correct product was conceived of, it is still improbable that the product could be finally adapted to unfamiliar conditions without prohibitive costs being incurred. In all, what our arguments amount to is the proposition that production functions are not identical in all countries, but that the production functions of goods demanded at home are the relatively most advantageous ones. The necessity of ‘the support of the home market’ is probably stressed by active businessmen as a reflection of the importance of relationships emphasized here.” 16 It is worth highlighting that the reference to Linder in our context slightly departs from what is generally known as the Linder Thesis in trade theory, i.e. the proposition that countries with similar levels of per capita Gross Domestic Product (GDP) should trade more. Rather, we refer to his original notion of representative domestic demand for a particular good as a determinant of trade in that good. 17 See Los et al., (2012). The ICIO has recently been extended to incorporate data till 2011 but the SEAs only go as far as 2009. 18 Countries are defined as emerging following the International Monetary Fund (IMF) definition in 2009 (the last year in the sample, see https://www.imf.org/external/pubs/ft/weo/2009/02/weodata/groups.htm). 19 Globally, backward and forward participation will be the same since what is exported within GVCs has to be equal to what is imported within GVCs. 20 Forward and backward participation are also interrelated. Indeed, the backward participation of Country A is the sum of the forward participation of all other countries with country A. 21 A variant of this indicator decomposes value added, similarly across countries and sectors, but according to final demand (Erumban et al., 2011; Los et al., 2012). This tracks not just the value added traded in the production of exports but also that used to satisfy domestic and international final demand. Both indicators involve similar calculation techniques but the former is solely concerned with exporting activities whereas the latter considers the origin of value added in GDP. The difference is important because domestic final demand and gross export vectors differ. 22 BS domestic value added in total exports captures the ability of a country to add BS domestic value to exports while BS domestic value added in foreign exports, which represents a subset of the former indicator, relates only to the domestic value added that serves as input into other countries exports. Both measures are suited to test the Hirschman–Linder hypothesis but the second indicator is more focused on the GVC elements. Indeed, in BS on average around 30% of domestic value added in exports is composed by forward participation sales. But there is strong variance. For instance, in India 26% of the BS value added in exports is forward participation and in the UK the share is closer to 31%. Data for each country are available on request. 23 Identifying the linkage by reading off the IO relations would not work since the linkages serve the purpose of producing for final domestic and foreign demand. 24 Domestic final demand includes domestic final consumption by households or government as well as investment, i.e. gross fixed capital formation. 25 Distance variables are obtained from the CEPII gravity database, see Mayer and Zignago (2011). It uses geodesic distances calculated following the great circle formula using latitudes and longitudes of most important cities or agglomerations (in terms of the population) and accounting for internal distances using population weights. 26 Since not all business services are knowledge intensive, we also tried the hourly wage of medium- and low-skilled workers but these were never significant. 27 As a proxy for technology, we have also tried trademarks but they were not significant. We have also tried a number of other proxies for telecommunication infrastructure (all those available for our country sample) such as mobile phone subscribers, telephone lines, and telecommunication expenditure but neither of those was significant. 28 We compare a share to a logged value for several reasons. First, to avoid confounding factors such as size which would drive a positive correlation (i.e. larger countries would have both larger BSVAE and larger domestic demand). Second, because our conjecture relates to using domestic or foreign value added links within GVCs where the size element is likely to matter (in the same way that larger countries have smaller foreign value added shares in their exports, the size of the domestic and foreign linkage is likely to matter). 29 In order to disentangle the net effect a proper spatial GMM model should be estimated. This is left for future research. 30 Results on manufacturing Hirschman–Linder linkages are qualitatively similar and are available on request. 31 As a robustness check, we have tried out a specification that tests our Hirschman Linder hypothesis by considering countries according to their stage of development in each period (see Table A5). The findings of this specification (Table A8) are robust to our main conclusion for upper-middle income countries (emerging countries) and, in addition, the coefficients for spillovers are significant for low and low middle income. Although based on a small sample of countries, and limited to the forward participation, the results shown in Table A8 seem to be in line with Lee at al. (2017), suggesting that countries at early stages of development can start from joining GVC but at later stages it is more difficult to create BS domestic value added in GVCs without developing internal capabilities through domestic linkages. 32 BS might behave differently, as not all BS are knowledge intensive, or have to rely on domestic demand. For instance, India initially promoted BPO by relying on foreign demand. However, the data at our disposal do not allow us to further disaggregate BS into low and high knowledge intensive to test whether they actually behave differently. Indeed, as included in footnote 19 above, we also run the main regressions using the hourly wage of medium and low-skilled workers, which could indirectly capture differences between subsectors of BS, but these were never significant. 33 See López González et al. (2015) for a preliminary appraisal of the role of GVCs in determining within country wage inequality. Acknowledgements The authors wish to thank two anonymous referees for the SPRU Working Papers Series; Martin Bell for extensive discussions on the topic. Preliminary versions of the paper have benefited from all the participants to the Conference on the Geography of innovation, held at the University of Utrecht (2014), and especially Bart Los; the DIG Seminar at Politecnico, Milan (2014); the Conference “Explaining Economic Change” held at the University “La Sapienza,” Rome (2014); the faculty of economics seminar at the University of Ferrara (2015); the DRUID (Rome) and the GLOBELICS (L’Havana) 2015 Conferences. Further versions of the paper have been presented at the Inter-American Development Bank lunch seminar (Washington DC) (2015); EMAEE Conference (Strasbourg, 2017); and several research seminars across European Universities in 2016 and 2017 (Jena; Bremen; Berlin; School of Slavonic Studies, London; Rome; Naples Parthenope). 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It is calculated from the VAE matrix (Equation 1) by taking the sum of the domestic rows of the manufacturing sector. DmanufVAEn=∑j∑iVAEn,c,i,j if n≠c and i=manuf (a1) Domestic Hirschman–Linder linkages for manufacturing The manufacturing Hirschman–Linder linkages (manufDDEM) is calculated by taking the sum of the domestic element of the manufacturing rows of the VADFD matrix: manufDDEMn=∑j∑iVAEn,c,i,j if n=c and i=manuf (a2) manufDDEMmanufn=∑j∑iVAEn,c,i,j if n=c and i=j=manuf (a3) Domestic Hirschman–Linder linkages of distance-weighted trade partners manufDDEM_parn=∑nmanufDDEMn. distancen,c∑ndistancen,c if n≠c (a3) Potential international spillover or GVC linkages DmanufVAFE_parn=∑nDmanufVAE_parn. distancen,c∑ndistancen,c if n≠c (a4) Figure A1. Open in new tabDownload slide Share of Gross Exports (a) and share of Value Added in Gross Exports (b) by Category. Source: Own calculations using WIOD. Note: Gross exports show direct exports across selected sectors. Value added figures show the contribution of each sector toward the creation of these gross exports. Business Services are identified as sector c30 in the WIOD which corresponds to ISIC sectors 71–74. Figure A1. Open in new tabDownload slide Share of Gross Exports (a) and share of Value Added in Gross Exports (b) by Category. Source: Own calculations using WIOD. Note: Gross exports show direct exports across selected sectors. Value added figures show the contribution of each sector toward the creation of these gross exports. Business Services are identified as sector c30 in the WIOD which corresponds to ISIC sectors 71–74. Figure A2. Open in new tabDownload slide Gross trade accounting framework. Source: Adapted from WBG-IDE-OECD-UIBE-WTO (2017). Figure A2. Open in new tabDownload slide Gross trade accounting framework. Source: Adapted from WBG-IDE-OECD-UIBE-WTO (2017). Table A1. Description of the variables Variables Description of variables Measure for Source DBSVAE Domestic business service value added used to produce foreign gross exports Domestic participation in BS GVCs Own calculations WIOD DmanufVAE Domestic manufacturing value added used to produce foreign gross exports Domestic participation in manufacturing GVCs Own calculations WIOD bsDDEMmanuf Domestic business service value added used by domestic manufacturing sector to satisfy domestic final demand Domestic BS Hirschman–Linder linkages with respect to manufacturing demand Own calculations WIOD bsDDEM Domestic business service value added used by all domestic sectors to satisfy domestic final demand Domestic BS Hirschman–Linder linkage with respect to all sectors Own calculations WIOD manufDDEM Domestic manufacturing value added used by all domestic sectors to satisfy domestic final demand Domestic manufacturing Hirschman–Linder linkage with respect to all sectors Own calculations WIOD manufDDEMmanuf Domestic manufacturing value added used by domestic manufacturing sector to satisfy domestic final demand Domestic manufacturing Hirschman–Linder linkage with respect to manufacturing demand Own calculations WIOD bsDDEM_par Distance-weighted domestic BS value added of partner countries used to satisfy their domestic demand Domestic BS Hirschman–Linder linkages of distance-weighted trade partners Own calculations WIOD manufDDEM_par Distance-weighted domestic manufacturing value added of partner countries used to satisfy their domestic demand Domestic manufacturing Hirschman–Linder linkages of distance-weighted trade partners Own calculations WIOD DBSVAE_par Distance-weighted partner domestic BS value added in foreign gross exports Potential spillover effects or GVC linkages in BS Own calculations WIOD DmanufVAE_par Distance-weighted partner domestic manufacturing value added in foreign gross exports Potential spillover effects or GVC linkages in manufacturing Own calculations WIOD rd R&D over GDP Proxy for technology or innovative capacity Castellacci and Natera (2011) waw_hs Average hourly wage of highly skilled workers Wages WIOD—SEAs internetusers Number of Internet users Proxy for technology or digital infrastructure Castellacci and Natera (2011) services Count of trade agreements with service provisions Degree of service openness DESTA toths Share of direct value added attributed to highly skilled labor As measure of factor endowments WIOD—SEAs edu Public expenditure on education over GDP Proxy for human capital Castellacci and Natera (2011) kl Capital labor ratio As measure of productivity WIOD—SEAs Variables Description of variables Measure for Source DBSVAE Domestic business service value added used to produce foreign gross exports Domestic participation in BS GVCs Own calculations WIOD DmanufVAE Domestic manufacturing value added used to produce foreign gross exports Domestic participation in manufacturing GVCs Own calculations WIOD bsDDEMmanuf Domestic business service value added used by domestic manufacturing sector to satisfy domestic final demand Domestic BS Hirschman–Linder linkages with respect to manufacturing demand Own calculations WIOD bsDDEM Domestic business service value added used by all domestic sectors to satisfy domestic final demand Domestic BS Hirschman–Linder linkage with respect to all sectors Own calculations WIOD manufDDEM Domestic manufacturing value added used by all domestic sectors to satisfy domestic final demand Domestic manufacturing Hirschman–Linder linkage with respect to all sectors Own calculations WIOD manufDDEMmanuf Domestic manufacturing value added used by domestic manufacturing sector to satisfy domestic final demand Domestic manufacturing Hirschman–Linder linkage with respect to manufacturing demand Own calculations WIOD bsDDEM_par Distance-weighted domestic BS value added of partner countries used to satisfy their domestic demand Domestic BS Hirschman–Linder linkages of distance-weighted trade partners Own calculations WIOD manufDDEM_par Distance-weighted domestic manufacturing value added of partner countries used to satisfy their domestic demand Domestic manufacturing Hirschman–Linder linkages of distance-weighted trade partners Own calculations WIOD DBSVAE_par Distance-weighted partner domestic BS value added in foreign gross exports Potential spillover effects or GVC linkages in BS Own calculations WIOD DmanufVAE_par Distance-weighted partner domestic manufacturing value added in foreign gross exports Potential spillover effects or GVC linkages in manufacturing Own calculations WIOD rd R&D over GDP Proxy for technology or innovative capacity Castellacci and Natera (2011) waw_hs Average hourly wage of highly skilled workers Wages WIOD—SEAs internetusers Number of Internet users Proxy for technology or digital infrastructure Castellacci and Natera (2011) services Count of trade agreements with service provisions Degree of service openness DESTA toths Share of direct value added attributed to highly skilled labor As measure of factor endowments WIOD—SEAs edu Public expenditure on education over GDP Proxy for human capital Castellacci and Natera (2011) kl Capital labor ratio As measure of productivity WIOD—SEAs Open in new tab Table A1. Description of the variables Variables Description of variables Measure for Source DBSVAE Domestic business service value added used to produce foreign gross exports Domestic participation in BS GVCs Own calculations WIOD DmanufVAE Domestic manufacturing value added used to produce foreign gross exports Domestic participation in manufacturing GVCs Own calculations WIOD bsDDEMmanuf Domestic business service value added used by domestic manufacturing sector to satisfy domestic final demand Domestic BS Hirschman–Linder linkages with respect to manufacturing demand Own calculations WIOD bsDDEM Domestic business service value added used by all domestic sectors to satisfy domestic final demand Domestic BS Hirschman–Linder linkage with respect to all sectors Own calculations WIOD manufDDEM Domestic manufacturing value added used by all domestic sectors to satisfy domestic final demand Domestic manufacturing Hirschman–Linder linkage with respect to all sectors Own calculations WIOD manufDDEMmanuf Domestic manufacturing value added used by domestic manufacturing sector to satisfy domestic final demand Domestic manufacturing Hirschman–Linder linkage with respect to manufacturing demand Own calculations WIOD bsDDEM_par Distance-weighted domestic BS value added of partner countries used to satisfy their domestic demand Domestic BS Hirschman–Linder linkages of distance-weighted trade partners Own calculations WIOD manufDDEM_par Distance-weighted domestic manufacturing value added of partner countries used to satisfy their domestic demand Domestic manufacturing Hirschman–Linder linkages of distance-weighted trade partners Own calculations WIOD DBSVAE_par Distance-weighted partner domestic BS value added in foreign gross exports Potential spillover effects or GVC linkages in BS Own calculations WIOD DmanufVAE_par Distance-weighted partner domestic manufacturing value added in foreign gross exports Potential spillover effects or GVC linkages in manufacturing Own calculations WIOD rd R&D over GDP Proxy for technology or innovative capacity Castellacci and Natera (2011) waw_hs Average hourly wage of highly skilled workers Wages WIOD—SEAs internetusers Number of Internet users Proxy for technology or digital infrastructure Castellacci and Natera (2011) services Count of trade agreements with service provisions Degree of service openness DESTA toths Share of direct value added attributed to highly skilled labor As measure of factor endowments WIOD—SEAs edu Public expenditure on education over GDP Proxy for human capital Castellacci and Natera (2011) kl Capital labor ratio As measure of productivity WIOD—SEAs Variables Description of variables Measure for Source DBSVAE Domestic business service value added used to produce foreign gross exports Domestic participation in BS GVCs Own calculations WIOD DmanufVAE Domestic manufacturing value added used to produce foreign gross exports Domestic participation in manufacturing GVCs Own calculations WIOD bsDDEMmanuf Domestic business service value added used by domestic manufacturing sector to satisfy domestic final demand Domestic BS Hirschman–Linder linkages with respect to manufacturing demand Own calculations WIOD bsDDEM Domestic business service value added used by all domestic sectors to satisfy domestic final demand Domestic BS Hirschman–Linder linkage with respect to all sectors Own calculations WIOD manufDDEM Domestic manufacturing value added used by all domestic sectors to satisfy domestic final demand Domestic manufacturing Hirschman–Linder linkage with respect to all sectors Own calculations WIOD manufDDEMmanuf Domestic manufacturing value added used by domestic manufacturing sector to satisfy domestic final demand Domestic manufacturing Hirschman–Linder linkage with respect to manufacturing demand Own calculations WIOD bsDDEM_par Distance-weighted domestic BS value added of partner countries used to satisfy their domestic demand Domestic BS Hirschman–Linder linkages of distance-weighted trade partners Own calculations WIOD manufDDEM_par Distance-weighted domestic manufacturing value added of partner countries used to satisfy their domestic demand Domestic manufacturing Hirschman–Linder linkages of distance-weighted trade partners Own calculations WIOD DBSVAE_par Distance-weighted partner domestic BS value added in foreign gross exports Potential spillover effects or GVC linkages in BS Own calculations WIOD DmanufVAE_par Distance-weighted partner domestic manufacturing value added in foreign gross exports Potential spillover effects or GVC linkages in manufacturing Own calculations WIOD rd R&D over GDP Proxy for technology or innovative capacity Castellacci and Natera (2011) waw_hs Average hourly wage of highly skilled workers Wages WIOD—SEAs internetusers Number of Internet users Proxy for technology or digital infrastructure Castellacci and Natera (2011) services Count of trade agreements with service provisions Degree of service openness DESTA toths Share of direct value added attributed to highly skilled labor As measure of factor endowments WIOD—SEAs edu Public expenditure on education over GDP Proxy for human capital Castellacci and Natera (2011) kl Capital labor ratio As measure of productivity WIOD—SEAs Open in new tab Table A2. Descriptive statistics of variables used in regressions Variables Obs Mean Std. Dev. Min Max BS forward linkagesa 580 4650.62 9722.83 1.39 66,045.30 Manuf. forward linkagesa 580 15,018.85 26,888.77 11.75 175,823.00 BS value added in manufacturing final demanda 580 4594.54 14,061.84 0.16 93,857.17 BS value added in total final demanda 580 55,352.00 166,288.40 7.55 1,190,219.00 Manuf. value added in total final demanda 580 86,837.88 210,068.80 20.91 1,301,799.00 BS VA in final demand of partnersa 580 1306.88 995.64 117.47 6144.92 Manufacturing VA in final demand of partnersa 580 1661.11 1453.63 145.40 9124.29 BS VA in forward linkages of partnersa 580 146.00 98.24 13.70 558.77 Manuf. VA in forward linkages of partnersa 580 471.30 284.98 46.30 1906.77 R&D over GDP % 565 1.38 0.92 0.01 4.24 Hourly wage of high-skilled workers 580 14.55 10.93 0.46 49.89 Internet users per 100 people 570 30.28 26.11 0.00 91.00 Count of provisions for the liberalization of trade in serv. 545 21.69 19.15 0.00 70.00 Share of direct VA attributed to high-skilled labor returns 580 0.13 0.05 0.02 0.36 Public expenditure on education over GDP % 441 4.93 1.28 0.00 8.74 Capital labor ratio 580 95.85 91.01 0.00 364.01 Variables Obs Mean Std. Dev. Min Max BS forward linkagesa 580 4650.62 9722.83 1.39 66,045.30 Manuf. forward linkagesa 580 15,018.85 26,888.77 11.75 175,823.00 BS value added in manufacturing final demanda 580 4594.54 14,061.84 0.16 93,857.17 BS value added in total final demanda 580 55,352.00 166,288.40 7.55 1,190,219.00 Manuf. value added in total final demanda 580 86,837.88 210,068.80 20.91 1,301,799.00 BS VA in final demand of partnersa 580 1306.88 995.64 117.47 6144.92 Manufacturing VA in final demand of partnersa 580 1661.11 1453.63 145.40 9124.29 BS VA in forward linkages of partnersa 580 146.00 98.24 13.70 558.77 Manuf. VA in forward linkages of partnersa 580 471.30 284.98 46.30 1906.77 R&D over GDP % 565 1.38 0.92 0.01 4.24 Hourly wage of high-skilled workers 580 14.55 10.93 0.46 49.89 Internet users per 100 people 570 30.28 26.11 0.00 91.00 Count of provisions for the liberalization of trade in serv. 545 21.69 19.15 0.00 70.00 Share of direct VA attributed to high-skilled labor returns 580 0.13 0.05 0.02 0.36 Public expenditure on education over GDP % 441 4.93 1.28 0.00 8.74 Capital labor ratio 580 95.85 91.01 0.00 364.01 a Values in million USD deflated to 1995 prices using value added deflators. Open in new tab Table A2. Descriptive statistics of variables used in regressions Variables Obs Mean Std. Dev. Min Max BS forward linkagesa 580 4650.62 9722.83 1.39 66,045.30 Manuf. forward linkagesa 580 15,018.85 26,888.77 11.75 175,823.00 BS value added in manufacturing final demanda 580 4594.54 14,061.84 0.16 93,857.17 BS value added in total final demanda 580 55,352.00 166,288.40 7.55 1,190,219.00 Manuf. value added in total final demanda 580 86,837.88 210,068.80 20.91 1,301,799.00 BS VA in final demand of partnersa 580 1306.88 995.64 117.47 6144.92 Manufacturing VA in final demand of partnersa 580 1661.11 1453.63 145.40 9124.29 BS VA in forward linkages of partnersa 580 146.00 98.24 13.70 558.77 Manuf. VA in forward linkages of partnersa 580 471.30 284.98 46.30 1906.77 R&D over GDP % 565 1.38 0.92 0.01 4.24 Hourly wage of high-skilled workers 580 14.55 10.93 0.46 49.89 Internet users per 100 people 570 30.28 26.11 0.00 91.00 Count of provisions for the liberalization of trade in serv. 545 21.69 19.15 0.00 70.00 Share of direct VA attributed to high-skilled labor returns 580 0.13 0.05 0.02 0.36 Public expenditure on education over GDP % 441 4.93 1.28 0.00 8.74 Capital labor ratio 580 95.85 91.01 0.00 364.01 Variables Obs Mean Std. Dev. Min Max BS forward linkagesa 580 4650.62 9722.83 1.39 66,045.30 Manuf. forward linkagesa 580 15,018.85 26,888.77 11.75 175,823.00 BS value added in manufacturing final demanda 580 4594.54 14,061.84 0.16 93,857.17 BS value added in total final demanda 580 55,352.00 166,288.40 7.55 1,190,219.00 Manuf. value added in total final demanda 580 86,837.88 210,068.80 20.91 1,301,799.00 BS VA in final demand of partnersa 580 1306.88 995.64 117.47 6144.92 Manufacturing VA in final demand of partnersa 580 1661.11 1453.63 145.40 9124.29 BS VA in forward linkages of partnersa 580 146.00 98.24 13.70 558.77 Manuf. VA in forward linkages of partnersa 580 471.30 284.98 46.30 1906.77 R&D over GDP % 565 1.38 0.92 0.01 4.24 Hourly wage of high-skilled workers 580 14.55 10.93 0.46 49.89 Internet users per 100 people 570 30.28 26.11 0.00 91.00 Count of provisions for the liberalization of trade in serv. 545 21.69 19.15 0.00 70.00 Share of direct VA attributed to high-skilled labor returns 580 0.13 0.05 0.02 0.36 Public expenditure on education over GDP % 441 4.93 1.28 0.00 8.74 Capital labor ratio 580 95.85 91.01 0.00 364.01 a Values in million USD deflated to 1995 prices using value added deflators. Open in new tab Table A3. Correlation coefficients (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) BS value added in total final demand (1) 1 BS value added in manufacturing final demand (2) 0.96 1.00 BS VA in forward linkages of partners (3) 0.52 0.42 1.00 BS VA in final demand of partners (4) 0.66 0.59 0.79 1.00 Manufacturing VA in forward linkages of partners (5) 0.59 0.51 0.92 0.85 1.00 Manufacturing VA in final demand of partners (6) 0.63 0.60 0.49 0.88 0.72 1.00 Public expenditure on education over GDP (7) 0.07 0.02 0.09 −0.12 −0.13 −0.35 1.00 R&D over GDP (8) 0.56 0.57 0.32 0.24 0.33 0.18 0.42 1.00 Hourly wage of high-skilled workers (9) 0.51 0.45 0.37 0.18 0.24 −0.04 0.59 0.65 1.00 Internet users per 100 people (10) 0.23 0.17 0.60 0.29 0.48 0.01 0.48 0.55 0.67 1.00 Count of provisions stimulating the liberalization of services (11) 0.17 0.12 0.25 −0.17 0.04 −0.41 0.41 0.27 0.62 0.39 1.00 Share of direct VA attributed to high-skilled labor returns (12) 0.23 0.20 0.02 −0.09 −0.02 −0.14 0.57 0.54 0.60 0.42 0.29 1.00 Capital labor ratio (13) 0.48 0.51 0.25 0.12 0.16 −0.03 0.56 0.78 0.78 0.57 0.50 0.60 1.00 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) BS value added in total final demand (1) 1 BS value added in manufacturing final demand (2) 0.96 1.00 BS VA in forward linkages of partners (3) 0.52 0.42 1.00 BS VA in final demand of partners (4) 0.66 0.59 0.79 1.00 Manufacturing VA in forward linkages of partners (5) 0.59 0.51 0.92 0.85 1.00 Manufacturing VA in final demand of partners (6) 0.63 0.60 0.49 0.88 0.72 1.00 Public expenditure on education over GDP (7) 0.07 0.02 0.09 −0.12 −0.13 −0.35 1.00 R&D over GDP (8) 0.56 0.57 0.32 0.24 0.33 0.18 0.42 1.00 Hourly wage of high-skilled workers (9) 0.51 0.45 0.37 0.18 0.24 −0.04 0.59 0.65 1.00 Internet users per 100 people (10) 0.23 0.17 0.60 0.29 0.48 0.01 0.48 0.55 0.67 1.00 Count of provisions stimulating the liberalization of services (11) 0.17 0.12 0.25 −0.17 0.04 −0.41 0.41 0.27 0.62 0.39 1.00 Share of direct VA attributed to high-skilled labor returns (12) 0.23 0.20 0.02 −0.09 −0.02 −0.14 0.57 0.54 0.60 0.42 0.29 1.00 Capital labor ratio (13) 0.48 0.51 0.25 0.12 0.16 −0.03 0.56 0.78 0.78 0.57 0.50 0.60 1.00 Open in new tab Table A3. Correlation coefficients (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) BS value added in total final demand (1) 1 BS value added in manufacturing final demand (2) 0.96 1.00 BS VA in forward linkages of partners (3) 0.52 0.42 1.00 BS VA in final demand of partners (4) 0.66 0.59 0.79 1.00 Manufacturing VA in forward linkages of partners (5) 0.59 0.51 0.92 0.85 1.00 Manufacturing VA in final demand of partners (6) 0.63 0.60 0.49 0.88 0.72 1.00 Public expenditure on education over GDP (7) 0.07 0.02 0.09 −0.12 −0.13 −0.35 1.00 R&D over GDP (8) 0.56 0.57 0.32 0.24 0.33 0.18 0.42 1.00 Hourly wage of high-skilled workers (9) 0.51 0.45 0.37 0.18 0.24 −0.04 0.59 0.65 1.00 Internet users per 100 people (10) 0.23 0.17 0.60 0.29 0.48 0.01 0.48 0.55 0.67 1.00 Count of provisions stimulating the liberalization of services (11) 0.17 0.12 0.25 −0.17 0.04 −0.41 0.41 0.27 0.62 0.39 1.00 Share of direct VA attributed to high-skilled labor returns (12) 0.23 0.20 0.02 −0.09 −0.02 −0.14 0.57 0.54 0.60 0.42 0.29 1.00 Capital labor ratio (13) 0.48 0.51 0.25 0.12 0.16 −0.03 0.56 0.78 0.78 0.57 0.50 0.60 1.00 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) BS value added in total final demand (1) 1 BS value added in manufacturing final demand (2) 0.96 1.00 BS VA in forward linkages of partners (3) 0.52 0.42 1.00 BS VA in final demand of partners (4) 0.66 0.59 0.79 1.00 Manufacturing VA in forward linkages of partners (5) 0.59 0.51 0.92 0.85 1.00 Manufacturing VA in final demand of partners (6) 0.63 0.60 0.49 0.88 0.72 1.00 Public expenditure on education over GDP (7) 0.07 0.02 0.09 −0.12 −0.13 −0.35 1.00 R&D over GDP (8) 0.56 0.57 0.32 0.24 0.33 0.18 0.42 1.00 Hourly wage of high-skilled workers (9) 0.51 0.45 0.37 0.18 0.24 −0.04 0.59 0.65 1.00 Internet users per 100 people (10) 0.23 0.17 0.60 0.29 0.48 0.01 0.48 0.55 0.67 1.00 Count of provisions stimulating the liberalization of services (11) 0.17 0.12 0.25 −0.17 0.04 −0.41 0.41 0.27 0.62 0.39 1.00 Share of direct VA attributed to high-skilled labor returns (12) 0.23 0.20 0.02 −0.09 −0.02 −0.14 0.57 0.54 0.60 0.42 0.29 1.00 Capital labor ratio (13) 0.48 0.51 0.25 0.12 0.16 −0.03 0.56 0.78 0.78 0.57 0.50 0.60 1.00 Open in new tab Table A4. WIOD sectors (International Standard Industry Classification codes) ISIC Description i Type AtB Agriculture, hunting, forestry, and fishing 1 Primary C Mining and quarrying 2 Primary 15t16 Food, beverages, and tobacco 3 Manufacturing 17t18 Textiles and textile products 4 Manufacturing 19 Leather, leather, and footwear 5 Manufacturing 20 Wood and products of wood and cork 6 Manufacturing 21t22 Pulp, paper, paper, printing, and publishing 7 Manufacturing 23 Coke, refined petroleum, and nuclear fuel 8 Manufacturing 24 Chemicals and chemical products 9 Manufacturing 25 Rubber and plastics 10 Manufacturing 26 Other nonmetallic mineral 11 Manufacturing 27t28 Basic metals and fabricated metal 12 Manufacturing 29 Machinery, nec 13 Manufacturing 30t33 Electrical and optical equipment 14 Manufacturing 34t35 Transport equipment 15 Manufacturing 36t37 Manufacturing, nec; recycling 16 Manufacturing E Electricity, gas, and water supply 17 Other services F Construction 18 Other services 50 Sale, maintenance, and repair of motor vehicles and motorcycles; retail sale of fuel 19 Other services 51 Wholesale trade and commission trade, except of motor vehicles and motorcycles 20 Other services 52 Retail trade, except of motor vehicles and motorcycles; repair of household goods 21 Other services H Hotels and restaurants 22 Other services 60 Inland transport 23 Other services 61 Water transport 24 Other services 62 Air transport 25 Other services 63 Other supporting and auxiliary transport activities; activities of travel agencies 26 Other services 64 Post and telecommunications 27 Other services J Financial intermediation 28 Other services 70 Real estate activities 29 Other services 71t74 Renting of M&Eq and other business activities 30 Business Services L Public admin and defense; compulsory social security 31 Other services M Education 32 Other services N Health and social work 33 Other services O Other community, social, and personal services 34 Other services P Private households with employed persons 35 Other services ISIC Description i Type AtB Agriculture, hunting, forestry, and fishing 1 Primary C Mining and quarrying 2 Primary 15t16 Food, beverages, and tobacco 3 Manufacturing 17t18 Textiles and textile products 4 Manufacturing 19 Leather, leather, and footwear 5 Manufacturing 20 Wood and products of wood and cork 6 Manufacturing 21t22 Pulp, paper, paper, printing, and publishing 7 Manufacturing 23 Coke, refined petroleum, and nuclear fuel 8 Manufacturing 24 Chemicals and chemical products 9 Manufacturing 25 Rubber and plastics 10 Manufacturing 26 Other nonmetallic mineral 11 Manufacturing 27t28 Basic metals and fabricated metal 12 Manufacturing 29 Machinery, nec 13 Manufacturing 30t33 Electrical and optical equipment 14 Manufacturing 34t35 Transport equipment 15 Manufacturing 36t37 Manufacturing, nec; recycling 16 Manufacturing E Electricity, gas, and water supply 17 Other services F Construction 18 Other services 50 Sale, maintenance, and repair of motor vehicles and motorcycles; retail sale of fuel 19 Other services 51 Wholesale trade and commission trade, except of motor vehicles and motorcycles 20 Other services 52 Retail trade, except of motor vehicles and motorcycles; repair of household goods 21 Other services H Hotels and restaurants 22 Other services 60 Inland transport 23 Other services 61 Water transport 24 Other services 62 Air transport 25 Other services 63 Other supporting and auxiliary transport activities; activities of travel agencies 26 Other services 64 Post and telecommunications 27 Other services J Financial intermediation 28 Other services 70 Real estate activities 29 Other services 71t74 Renting of M&Eq and other business activities 30 Business Services L Public admin and defense; compulsory social security 31 Other services M Education 32 Other services N Health and social work 33 Other services O Other community, social, and personal services 34 Other services P Private households with employed persons 35 Other services Open in new tab Table A4. WIOD sectors (International Standard Industry Classification codes) ISIC Description i Type AtB Agriculture, hunting, forestry, and fishing 1 Primary C Mining and quarrying 2 Primary 15t16 Food, beverages, and tobacco 3 Manufacturing 17t18 Textiles and textile products 4 Manufacturing 19 Leather, leather, and footwear 5 Manufacturing 20 Wood and products of wood and cork 6 Manufacturing 21t22 Pulp, paper, paper, printing, and publishing 7 Manufacturing 23 Coke, refined petroleum, and nuclear fuel 8 Manufacturing 24 Chemicals and chemical products 9 Manufacturing 25 Rubber and plastics 10 Manufacturing 26 Other nonmetallic mineral 11 Manufacturing 27t28 Basic metals and fabricated metal 12 Manufacturing 29 Machinery, nec 13 Manufacturing 30t33 Electrical and optical equipment 14 Manufacturing 34t35 Transport equipment 15 Manufacturing 36t37 Manufacturing, nec; recycling 16 Manufacturing E Electricity, gas, and water supply 17 Other services F Construction 18 Other services 50 Sale, maintenance, and repair of motor vehicles and motorcycles; retail sale of fuel 19 Other services 51 Wholesale trade and commission trade, except of motor vehicles and motorcycles 20 Other services 52 Retail trade, except of motor vehicles and motorcycles; repair of household goods 21 Other services H Hotels and restaurants 22 Other services 60 Inland transport 23 Other services 61 Water transport 24 Other services 62 Air transport 25 Other services 63 Other supporting and auxiliary transport activities; activities of travel agencies 26 Other services 64 Post and telecommunications 27 Other services J Financial intermediation 28 Other services 70 Real estate activities 29 Other services 71t74 Renting of M&Eq and other business activities 30 Business Services L Public admin and defense; compulsory social security 31 Other services M Education 32 Other services N Health and social work 33 Other services O Other community, social, and personal services 34 Other services P Private households with employed persons 35 Other services ISIC Description i Type AtB Agriculture, hunting, forestry, and fishing 1 Primary C Mining and quarrying 2 Primary 15t16 Food, beverages, and tobacco 3 Manufacturing 17t18 Textiles and textile products 4 Manufacturing 19 Leather, leather, and footwear 5 Manufacturing 20 Wood and products of wood and cork 6 Manufacturing 21t22 Pulp, paper, paper, printing, and publishing 7 Manufacturing 23 Coke, refined petroleum, and nuclear fuel 8 Manufacturing 24 Chemicals and chemical products 9 Manufacturing 25 Rubber and plastics 10 Manufacturing 26 Other nonmetallic mineral 11 Manufacturing 27t28 Basic metals and fabricated metal 12 Manufacturing 29 Machinery, nec 13 Manufacturing 30t33 Electrical and optical equipment 14 Manufacturing 34t35 Transport equipment 15 Manufacturing 36t37 Manufacturing, nec; recycling 16 Manufacturing E Electricity, gas, and water supply 17 Other services F Construction 18 Other services 50 Sale, maintenance, and repair of motor vehicles and motorcycles; retail sale of fuel 19 Other services 51 Wholesale trade and commission trade, except of motor vehicles and motorcycles 20 Other services 52 Retail trade, except of motor vehicles and motorcycles; repair of household goods 21 Other services H Hotels and restaurants 22 Other services 60 Inland transport 23 Other services 61 Water transport 24 Other services 62 Air transport 25 Other services 63 Other supporting and auxiliary transport activities; activities of travel agencies 26 Other services 64 Post and telecommunications 27 Other services J Financial intermediation 28 Other services 70 Real estate activities 29 Other services 71t74 Renting of M&Eq and other business activities 30 Business Services L Public admin and defense; compulsory social security 31 Other services M Education 32 Other services N Health and social work 33 Other services O Other community, social, and personal services 34 Other services P Private households with employed persons 35 Other services Open in new tab Table A5. WIOD country coverage and countries’ classification 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Low income (L) ≤765 ≤785 ≤785 ≤760 ≤755 ≤755 ≤745 ≤735 ≤765 ≤825 ≤875 ≤905 ≤935 ≤975 ≤995 Lower-middle income (LM) 766–3035 786–3115 786–3125 761–3030 756–2995 756–2995 746–2975 736–2935 766–3035 826–3255 876–3465 906–3595 936–3705 976–3855 996–3945 Upper-middle income (UM) 3036– 9385 3116– 9645 3126– 9655 3031– 9360 2996– 9265 2996– 9265 2976– 9205 2936– 9075 3036– 9385 3256– 10,065 3466– 10,725 3596– 11,115 3706– 11,455 3856– 11,905 3946– 12,195 High income (H) >9385 >9645 >9655 >9360 >9265 >9265 >9205 >9075 >9385 >10,065 >10,725 >11,115 >11,455 >11,905 >12,195 Australia H H H H H H H H H H H H H H H Austria H H H H H H H H H H H H H H H Belgium H H H H H H H H H H H H H H H Brazila UM UM UM UM UM UM UM LM LM LM LM UM UM UM UM Bulgariaa LM LM LM LM LM LM LM LM LM LM LM UM UM UM UM Canada H H H H H H H H H H H H H H H Chinaa L L LM L LM LM LM LM LM LM LM LM LM LM LM Cyprus H H H H H H H H H H H H H H H Czech Republic UM UM UM UM UM UM UM UM UM UM UM H H H H Denmark H H H H H H H H H H H H H H H Estoniaa LM LM UM UM UM UM UM UM UM UM UM H H H H Finland H H H H H H H H H H H H H H H France H H H H H H H H H H H H H H H Germany H H H H H H H H H H H H H H H Greece UM H H H H H H H H H H H H H H Hungarya UM UM UM UM UM UM UM UM UM UM UM UM H H H Indiaa L L L L L L L L L L L L LM LM LM Indonesiaa LM LM LM L L L L L LM LM LM LM LM LM LM Ireland H H H H H H H H H H H H H H H Italy H H H H H H H H H H H H H H H Japan H H H H H H H H H H H H H H H Korea, Rep. H H H UM UM UM H H H H H H H H H Latviaa LM LM LM LM LM LM UM UM UM UM UM UM UM UM H Lithuaniaa LM LM LM LM LM LM UM UM UM UM UM UM UM UM UM Luxembourg H H H H H H H H H H H H H H H Malta UM UM UM H UM H UM H H H H H H H H Mexicoa UM UM UM UM UM UM UM UM UM UM UM UM UM UM UM Netherlands H H H H H H H H H H H H H H H Polanda LM UM UM UM UM UM UM UM UM UM UM UM UM UM H Portugal H H H H H H H H H H H H H H H Romaniaa LM LM LM LM LM LM LM LM LM LM UM UM UM UM UM Russian Federationa LM LM LM LM LM LM LM LM LM UM UM UM UM UM UM Slovak Republic LM UM UM UM UM UM UM UM UM UM UM UM H H H Slovenia UM UM H H H H H H H H H H H H H Spain H H H H H H H H H H H H H H H Sweden H H H H H H H H H H H H H H H Taiwan, China H H H H H H H H H H H H H H H Turkeya LM LM UM UM LM UM LM LM LM UM UM UM UM UM UM United Kingdom H H H H H H H H H H H H H H H United States H H H H H H H H H H H H H H H 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Low income (L) ≤765 ≤785 ≤785 ≤760 ≤755 ≤755 ≤745 ≤735 ≤765 ≤825 ≤875 ≤905 ≤935 ≤975 ≤995 Lower-middle income (LM) 766–3035 786–3115 786–3125 761–3030 756–2995 756–2995 746–2975 736–2935 766–3035 826–3255 876–3465 906–3595 936–3705 976–3855 996–3945 Upper-middle income (UM) 3036– 9385 3116– 9645 3126– 9655 3031– 9360 2996– 9265 2996– 9265 2976– 9205 2936– 9075 3036– 9385 3256– 10,065 3466– 10,725 3596– 11,115 3706– 11,455 3856– 11,905 3946– 12,195 High income (H) >9385 >9645 >9655 >9360 >9265 >9265 >9205 >9075 >9385 >10,065 >10,725 >11,115 >11,455 >11,905 >12,195 Australia H H H H H H H H H H H H H H H Austria H H H H H H H H H H H H H H H Belgium H H H H H H H H H H H H H H H Brazila UM UM UM UM UM UM UM LM LM LM LM UM UM UM UM Bulgariaa LM LM LM LM LM LM LM LM LM LM LM UM UM UM UM Canada H H H H H H H H H H H H H H H Chinaa L L LM L LM LM LM LM LM LM LM LM LM LM LM Cyprus H H H H H H H H H H H H H H H Czech Republic UM UM UM UM UM UM UM UM UM UM UM H H H H Denmark H H H H H H H H H H H H H H H Estoniaa LM LM UM UM UM UM UM UM UM UM UM H H H H Finland H H H H H H H H H H H H H H H France H H H H H H H H H H H H H H H Germany H H H H H H H H H H H H H H H Greece UM H H H H H H H H H H H H H H Hungarya UM UM UM UM UM UM UM UM UM UM UM UM H H H Indiaa L L L L L L L L L L L L LM LM LM Indonesiaa LM LM LM L L L L L LM LM LM LM LM LM LM Ireland H H H H H H H H H H H H H H H Italy H H H H H H H H H H H H H H H Japan H H H H H H H H H H H H H H H Korea, Rep. H H H UM UM UM H H H H H H H H H Latviaa LM LM LM LM LM LM UM UM UM UM UM UM UM UM H Lithuaniaa LM LM LM LM LM LM UM UM UM UM UM UM UM UM UM Luxembourg H H H H H H H H H H H H H H H Malta UM UM UM H UM H UM H H H H H H H H Mexicoa UM UM UM UM UM UM UM UM UM UM UM UM UM UM UM Netherlands H H H H H H H H H H H H H H H Polanda LM UM UM UM UM UM UM UM UM UM UM UM UM UM H Portugal H H H H H H H H H H H H H H H Romaniaa LM LM LM LM LM LM LM LM LM LM UM UM UM UM UM Russian Federationa LM LM LM LM LM LM LM LM LM UM UM UM UM UM UM Slovak Republic LM UM UM UM UM UM UM UM UM UM UM UM H H H Slovenia UM UM H H H H H H H H H H H H H Spain H H H H H H H H H H H H H H H Sweden H H H H H H H H H H H H H H H Taiwan, China H H H H H H H H H H H H H H H Turkeya LM LM UM UM LM UM LM LM LM UM UM UM UM UM UM United Kingdom H H H H H H H H H H H H H H H United States H H H H H H H H H H H H H H H a Denotes emerging economies identified according to the IMF classification in 2009 (https://www.imf.org/external/pubs/ft/weo/2009/02/weodata/groups.htm). Open in new tab Table A5. WIOD country coverage and countries’ classification 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Low income (L) ≤765 ≤785 ≤785 ≤760 ≤755 ≤755 ≤745 ≤735 ≤765 ≤825 ≤875 ≤905 ≤935 ≤975 ≤995 Lower-middle income (LM) 766–3035 786–3115 786–3125 761–3030 756–2995 756–2995 746–2975 736–2935 766–3035 826–3255 876–3465 906–3595 936–3705 976–3855 996–3945 Upper-middle income (UM) 3036– 9385 3116– 9645 3126– 9655 3031– 9360 2996– 9265 2996– 9265 2976– 9205 2936– 9075 3036– 9385 3256– 10,065 3466– 10,725 3596– 11,115 3706– 11,455 3856– 11,905 3946– 12,195 High income (H) >9385 >9645 >9655 >9360 >9265 >9265 >9205 >9075 >9385 >10,065 >10,725 >11,115 >11,455 >11,905 >12,195 Australia H H H H H H H H H H H H H H H Austria H H H H H H H H H H H H H H H Belgium H H H H H H H H H H H H H H H Brazila UM UM UM UM UM UM UM LM LM LM LM UM UM UM UM Bulgariaa LM LM LM LM LM LM LM LM LM LM LM UM UM UM UM Canada H H H H H H H H H H H H H H H Chinaa L L LM L LM LM LM LM LM LM LM LM LM LM LM Cyprus H H H H H H H H H H H H H H H Czech Republic UM UM UM UM UM UM UM UM UM UM UM H H H H Denmark H H H H H H H H H H H H H H H Estoniaa LM LM UM UM UM UM UM UM UM UM UM H H H H Finland H H H H H H H H H H H H H H H France H H H H H H H H H H H H H H H Germany H H H H H H H H H H H H H H H Greece UM H H H H H H H H H H H H H H Hungarya UM UM UM UM UM UM UM UM UM UM UM UM H H H Indiaa L L L L L L L L L L L L LM LM LM Indonesiaa LM LM LM L L L L L LM LM LM LM LM LM LM Ireland H H H H H H H H H H H H H H H Italy H H H H H H H H H H H H H H H Japan H H H H H H H H H H H H H H H Korea, Rep. H H H UM UM UM H H H H H H H H H Latviaa LM LM LM LM LM LM UM UM UM UM UM UM UM UM H Lithuaniaa LM LM LM LM LM LM UM UM UM UM UM UM UM UM UM Luxembourg H H H H H H H H H H H H H H H Malta UM UM UM H UM H UM H H H H H H H H Mexicoa UM UM UM UM UM UM UM UM UM UM UM UM UM UM UM Netherlands H H H H H H H H H H H H H H H Polanda LM UM UM UM UM UM UM UM UM UM UM UM UM UM H Portugal H H H H H H H H H H H H H H H Romaniaa LM LM LM LM LM LM LM LM LM LM UM UM UM UM UM Russian Federationa LM LM LM LM LM LM LM LM LM UM UM UM UM UM UM Slovak Republic LM UM UM UM UM UM UM UM UM UM UM UM H H H Slovenia UM UM H H H H H H H H H H H H H Spain H H H H H H H H H H H H H H H Sweden H H H H H H H H H H H H H H H Taiwan, China H H H H H H H H H H H H H H H Turkeya LM LM UM UM LM UM LM LM LM UM UM UM UM UM UM United Kingdom H H H H H H H H H H H H H H H United States H H H H H H H H H H H H H H H 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Low income (L) ≤765 ≤785 ≤785 ≤760 ≤755 ≤755 ≤745 ≤735 ≤765 ≤825 ≤875 ≤905 ≤935 ≤975 ≤995 Lower-middle income (LM) 766–3035 786–3115 786–3125 761–3030 756–2995 756–2995 746–2975 736–2935 766–3035 826–3255 876–3465 906–3595 936–3705 976–3855 996–3945 Upper-middle income (UM) 3036– 9385 3116– 9645 3126– 9655 3031– 9360 2996– 9265 2996– 9265 2976– 9205 2936– 9075 3036– 9385 3256– 10,065 3466– 10,725 3596– 11,115 3706– 11,455 3856– 11,905 3946– 12,195 High income (H) >9385 >9645 >9655 >9360 >9265 >9265 >9205 >9075 >9385 >10,065 >10,725 >11,115 >11,455 >11,905 >12,195 Australia H H H H H H H H H H H H H H H Austria H H H H H H H H H H H H H H H Belgium H H H H H H H H H H H H H H H Brazila UM UM UM UM UM UM UM LM LM LM LM UM UM UM UM Bulgariaa LM LM LM LM LM LM LM LM LM LM LM UM UM UM UM Canada H H H H H H H H H H H H H H H Chinaa L L LM L LM LM LM LM LM LM LM LM LM LM LM Cyprus H H H H H H H H H H H H H H H Czech Republic UM UM UM UM UM UM UM UM UM UM UM H H H H Denmark H H H H H H H H H H H H H H H Estoniaa LM LM UM UM UM UM UM UM UM UM UM H H H H Finland H H H H H H H H H H H H H H H France H H H H H H H H H H H H H H H Germany H H H H H H H H H H H H H H H Greece UM H H H H H H H H H H H H H H Hungarya UM UM UM UM UM UM UM UM UM UM UM UM H H H Indiaa L L L L L L L L L L L L LM LM LM Indonesiaa LM LM LM L L L L L LM LM LM LM LM LM LM Ireland H H H H H H H H H H H H H H H Italy H H H H H H H H H H H H H H H Japan H H H H H H H H H H H H H H H Korea, Rep. H H H UM UM UM H H H H H H H H H Latviaa LM LM LM LM LM LM UM UM UM UM UM UM UM UM H Lithuaniaa LM LM LM LM LM LM UM UM UM UM UM UM UM UM UM Luxembourg H H H H H H H H H H H H H H H Malta UM UM UM H UM H UM H H H H H H H H Mexicoa UM UM UM UM UM UM UM UM UM UM UM UM UM UM UM Netherlands H H H H H H H H H H H H H H H Polanda LM UM UM UM UM UM UM UM UM UM UM UM UM UM H Portugal H H H H H H H H H H H H H H H Romaniaa LM LM LM LM LM LM LM LM LM LM UM UM UM UM UM Russian Federationa LM LM LM LM LM LM LM LM LM UM UM UM UM UM UM Slovak Republic LM UM UM UM UM UM UM UM UM UM UM UM H H H Slovenia UM UM H H H H H H H H H H H H H Spain H H H H H H H H H H H H H H H Sweden H H H H H H H H H H H H H H H Taiwan, China H H H H H H H H H H H H H H H Turkeya LM LM UM UM LM UM LM LM LM UM UM UM UM UM UM United Kingdom H H H H H H H H H H H H H H H United States H H H H H H H H H H H H H H H a Denotes emerging economies identified according to the IMF classification in 2009 (https://www.imf.org/external/pubs/ft/weo/2009/02/weodata/groups.htm). Open in new tab Table A6. Arellano–Bond estimations of BS value added in foreign exports (1a) (2a) (3a) (1b) (2b) (3b) BS value added in foreign exports lag 1 0.468 0.396 0.402 0.449 0.33 0.348 (13.77)*** (12.04)*** (11.76)*** (12.60)*** (9.72)*** (10.04)*** BS value added in total final demand 0.166 0.156 0.229 (2.15)** (2.21)** (3.01)*** BS value added in manufacturing final demand 0.106 0.136 0.137 (5.96)*** (8.38)*** (8.29)*** BS VA in foreign exports of partners 1.781 1.939 2.238 2.110 (6.50)*** (5.25)*** (8.45)*** (6.05)*** BS VA in final demand of partners −0.74 −0.464 −1.147 −0.824 (−3.85)*** (−1.86)* (−6.00)*** (−3.47)*** Manufacturing VA in foreign exports of partners 0.038 0.255 (0.13) (0.98) Manufacturing VA in final demand of partners −0.656 −0.546 (−2.09)** (−1.99)** Public expenditure on education over GDP −0.058 −0.084 −0.076 0.002 0.012 0.018 (−0.76) (−1.19) (−1.06) (0.02) (0.17) (0.25) R&D over GDP −0.019 −0.03 −0.025 0.066 0.057 0.065 (−0.50) (−0.85) (−0.70) (1.75)* (1.68)* (1.88)* Hourly wage of high-skilled workers −0.121 −0.235 −0.26 −0.168 −0.307 −0.296 (−2.12)** (−3.94)*** (−4.24)*** (−3.05)*** (−5.75)*** (−5.46)*** Internet users per 100 people 0.077 0.097 0.104 0.089 0.113 0.101 (3.06)*** (4.13)*** (3.75)*** (3.57)*** (5.04)*** (3.97)*** Count of provisions stimulating the liberalization of trade in services 0.001 0.001 0.000 0.001 0.003 0.001 (0.44) (0.67) (0.2) (0.59) (1.53) (0.78) Share of direct VA attributed to high-skilled labor returns 0.247 0.109 0.149 0.346 0.302 0.31 (2.45)** (1.15) (1.53) (3.16)*** (3.10)*** (3.13)*** Capital labor ratio 0.351 0.419 0.357 0.485 0.554 0.546 (3.83)*** (5.04)*** (4.12)*** (9.25)*** (11.79)*** (11.57)*** Constant 1.364 −2.486 0.92 2.059 −1.005 1.648 (2.57)** (−1.36) (0.53) (4.81)*** (−0.60) (1.03) Observations 414 414 414 414 414 414 (1a) (2a) (3a) (1b) (2b) (3b) BS value added in foreign exports lag 1 0.468 0.396 0.402 0.449 0.33 0.348 (13.77)*** (12.04)*** (11.76)*** (12.60)*** (9.72)*** (10.04)*** BS value added in total final demand 0.166 0.156 0.229 (2.15)** (2.21)** (3.01)*** BS value added in manufacturing final demand 0.106 0.136 0.137 (5.96)*** (8.38)*** (8.29)*** BS VA in foreign exports of partners 1.781 1.939 2.238 2.110 (6.50)*** (5.25)*** (8.45)*** (6.05)*** BS VA in final demand of partners −0.74 −0.464 −1.147 −0.824 (−3.85)*** (−1.86)* (−6.00)*** (−3.47)*** Manufacturing VA in foreign exports of partners 0.038 0.255 (0.13) (0.98) Manufacturing VA in final demand of partners −0.656 −0.546 (−2.09)** (−1.99)** Public expenditure on education over GDP −0.058 −0.084 −0.076 0.002 0.012 0.018 (−0.76) (−1.19) (−1.06) (0.02) (0.17) (0.25) R&D over GDP −0.019 −0.03 −0.025 0.066 0.057 0.065 (−0.50) (−0.85) (−0.70) (1.75)* (1.68)* (1.88)* Hourly wage of high-skilled workers −0.121 −0.235 −0.26 −0.168 −0.307 −0.296 (−2.12)** (−3.94)*** (−4.24)*** (−3.05)*** (−5.75)*** (−5.46)*** Internet users per 100 people 0.077 0.097 0.104 0.089 0.113 0.101 (3.06)*** (4.13)*** (3.75)*** (3.57)*** (5.04)*** (3.97)*** Count of provisions stimulating the liberalization of trade in services 0.001 0.001 0.000 0.001 0.003 0.001 (0.44) (0.67) (0.2) (0.59) (1.53) (0.78) Share of direct VA attributed to high-skilled labor returns 0.247 0.109 0.149 0.346 0.302 0.31 (2.45)** (1.15) (1.53) (3.16)*** (3.10)*** (3.13)*** Capital labor ratio 0.351 0.419 0.357 0.485 0.554 0.546 (3.83)*** (5.04)*** (4.12)*** (9.25)*** (11.79)*** (11.57)*** Constant 1.364 −2.486 0.92 2.059 −1.005 1.648 (2.57)** (−1.36) (0.53) (4.81)*** (−0.60) (1.03) Observations 414 414 414 414 414 414 Note: Year dummies included but not reported. Standard errors are heteroscedasticity robust. *, **, and *** indicate statistical significance at 10%, 5%, and 1%, respectively. Open in new tab Table A6. Arellano–Bond estimations of BS value added in foreign exports (1a) (2a) (3a) (1b) (2b) (3b) BS value added in foreign exports lag 1 0.468 0.396 0.402 0.449 0.33 0.348 (13.77)*** (12.04)*** (11.76)*** (12.60)*** (9.72)*** (10.04)*** BS value added in total final demand 0.166 0.156 0.229 (2.15)** (2.21)** (3.01)*** BS value added in manufacturing final demand 0.106 0.136 0.137 (5.96)*** (8.38)*** (8.29)*** BS VA in foreign exports of partners 1.781 1.939 2.238 2.110 (6.50)*** (5.25)*** (8.45)*** (6.05)*** BS VA in final demand of partners −0.74 −0.464 −1.147 −0.824 (−3.85)*** (−1.86)* (−6.00)*** (−3.47)*** Manufacturing VA in foreign exports of partners 0.038 0.255 (0.13) (0.98) Manufacturing VA in final demand of partners −0.656 −0.546 (−2.09)** (−1.99)** Public expenditure on education over GDP −0.058 −0.084 −0.076 0.002 0.012 0.018 (−0.76) (−1.19) (−1.06) (0.02) (0.17) (0.25) R&D over GDP −0.019 −0.03 −0.025 0.066 0.057 0.065 (−0.50) (−0.85) (−0.70) (1.75)* (1.68)* (1.88)* Hourly wage of high-skilled workers −0.121 −0.235 −0.26 −0.168 −0.307 −0.296 (−2.12)** (−3.94)*** (−4.24)*** (−3.05)*** (−5.75)*** (−5.46)*** Internet users per 100 people 0.077 0.097 0.104 0.089 0.113 0.101 (3.06)*** (4.13)*** (3.75)*** (3.57)*** (5.04)*** (3.97)*** Count of provisions stimulating the liberalization of trade in services 0.001 0.001 0.000 0.001 0.003 0.001 (0.44) (0.67) (0.2) (0.59) (1.53) (0.78) Share of direct VA attributed to high-skilled labor returns 0.247 0.109 0.149 0.346 0.302 0.31 (2.45)** (1.15) (1.53) (3.16)*** (3.10)*** (3.13)*** Capital labor ratio 0.351 0.419 0.357 0.485 0.554 0.546 (3.83)*** (5.04)*** (4.12)*** (9.25)*** (11.79)*** (11.57)*** Constant 1.364 −2.486 0.92 2.059 −1.005 1.648 (2.57)** (−1.36) (0.53) (4.81)*** (−0.60) (1.03) Observations 414 414 414 414 414 414 (1a) (2a) (3a) (1b) (2b) (3b) BS value added in foreign exports lag 1 0.468 0.396 0.402 0.449 0.33 0.348 (13.77)*** (12.04)*** (11.76)*** (12.60)*** (9.72)*** (10.04)*** BS value added in total final demand 0.166 0.156 0.229 (2.15)** (2.21)** (3.01)*** BS value added in manufacturing final demand 0.106 0.136 0.137 (5.96)*** (8.38)*** (8.29)*** BS VA in foreign exports of partners 1.781 1.939 2.238 2.110 (6.50)*** (5.25)*** (8.45)*** (6.05)*** BS VA in final demand of partners −0.74 −0.464 −1.147 −0.824 (−3.85)*** (−1.86)* (−6.00)*** (−3.47)*** Manufacturing VA in foreign exports of partners 0.038 0.255 (0.13) (0.98) Manufacturing VA in final demand of partners −0.656 −0.546 (−2.09)** (−1.99)** Public expenditure on education over GDP −0.058 −0.084 −0.076 0.002 0.012 0.018 (−0.76) (−1.19) (−1.06) (0.02) (0.17) (0.25) R&D over GDP −0.019 −0.03 −0.025 0.066 0.057 0.065 (−0.50) (−0.85) (−0.70) (1.75)* (1.68)* (1.88)* Hourly wage of high-skilled workers −0.121 −0.235 −0.26 −0.168 −0.307 −0.296 (−2.12)** (−3.94)*** (−4.24)*** (−3.05)*** (−5.75)*** (−5.46)*** Internet users per 100 people 0.077 0.097 0.104 0.089 0.113 0.101 (3.06)*** (4.13)*** (3.75)*** (3.57)*** (5.04)*** (3.97)*** Count of provisions stimulating the liberalization of trade in services 0.001 0.001 0.000 0.001 0.003 0.001 (0.44) (0.67) (0.2) (0.59) (1.53) (0.78) Share of direct VA attributed to high-skilled labor returns 0.247 0.109 0.149 0.346 0.302 0.31 (2.45)** (1.15) (1.53) (3.16)*** (3.10)*** (3.13)*** Capital labor ratio 0.351 0.419 0.357 0.485 0.554 0.546 (3.83)*** (5.04)*** (4.12)*** (9.25)*** (11.79)*** (11.57)*** Constant 1.364 −2.486 0.92 2.059 −1.005 1.648 (2.57)** (−1.36) (0.53) (4.81)*** (−0.60) (1.03) Observations 414 414 414 414 414 414 Note: Year dummies included but not reported. Standard errors are heteroscedasticity robust. *, **, and *** indicate statistical significance at 10%, 5%, and 1%, respectively. Open in new tab Table A7. Estimations of BS value added in total exports Business services VA in exports Manufacturing VA in exports Emerging Advanced Emerging Advanced BS value added in exports lag 1 0.470 0.561 0.414 0.822 (2.29)** (8.34)*** (2.62)*** (6.41)*** BS value added in exports lag 2 0.037 0.078 −0.073 −0.052 (0.57) (1.99)** (1.99)** (0.63) BS (or manufacturing) value added in total final demand 0.344 0.152 0.579 0.074 (2.75)*** (2.99)*** (5.15)*** (2.29)** BS VA in exports of partners 1.828 0.954 −1.194 −0.496 (1.62) (3.01)*** (−1.27) (−2.50)** Manufacturing VA in exports of partners −1.070 0.303 4.194 1.308 (−0.98) (1.22) (3.01)*** (5.71)*** BS VA in final demand of partners −2.425 −0.255 0.704 0.441 (−2.99)*** (−0.94) (1.14) (2.52)** Manufacturing VA in final demand of partners 2.138 −0.065 −2.818 −0.789 (2.05)** (−0.22) (2.82)*** (3.31)*** Public expenditure on education over GDP −0.032 0.124 0.108 0.071 (−0.16) (1.19) (0.75) (1.61) R&D over GDP −0.032 0.031 −0.103 −0.084 (−0.51) (0.55) (−1.90)* (−1.85)* Hourly wage of high-skilled −0.317 −0.261 −0.217 −0.062 (2.02)** (3.08)*** (3.85)*** (−1.08) Internet users per 100 people −0.045 −0.007 −0.017 0.056 (−0.61) (−0.3) (−0.19) (2.92)*** Count of provisions stipulating the liberalization of trade in services 0.010 0.004 0.012 0.000 (2.47)** (1.69)* (3.09)*** (−0.140) Share of direct VA attributed to high-skilled labor returns 0.201 0.054 0.023 0.118 (0.98) (0.58) (0.13) (1.33) Capital labor ratio 0.162 0.294 0.028 0.105 (2.75)*** (2.34)** (0.67) (1.42) Constant −0.379 −5.474 −7.748 −2.446 (−0.11) (6.41)*** (2.83)*** (3.21)*** Arellano–Bond test for AR(1) −1.115 −1.999** −2.122** −3.475*** Arellano–Bond test for AR(2) −1.172 −0.519 −1.426 −0.827 Observations 165 252 165 252 Business services VA in exports Manufacturing VA in exports Emerging Advanced Emerging Advanced BS value added in exports lag 1 0.470 0.561 0.414 0.822 (2.29)** (8.34)*** (2.62)*** (6.41)*** BS value added in exports lag 2 0.037 0.078 −0.073 −0.052 (0.57) (1.99)** (1.99)** (0.63) BS (or manufacturing) value added in total final demand 0.344 0.152 0.579 0.074 (2.75)*** (2.99)*** (5.15)*** (2.29)** BS VA in exports of partners 1.828 0.954 −1.194 −0.496 (1.62) (3.01)*** (−1.27) (−2.50)** Manufacturing VA in exports of partners −1.070 0.303 4.194 1.308 (−0.98) (1.22) (3.01)*** (5.71)*** BS VA in final demand of partners −2.425 −0.255 0.704 0.441 (−2.99)*** (−0.94) (1.14) (2.52)** Manufacturing VA in final demand of partners 2.138 −0.065 −2.818 −0.789 (2.05)** (−0.22) (2.82)*** (3.31)*** Public expenditure on education over GDP −0.032 0.124 0.108 0.071 (−0.16) (1.19) (0.75) (1.61) R&D over GDP −0.032 0.031 −0.103 −0.084 (−0.51) (0.55) (−1.90)* (−1.85)* Hourly wage of high-skilled −0.317 −0.261 −0.217 −0.062 (2.02)** (3.08)*** (3.85)*** (−1.08) Internet users per 100 people −0.045 −0.007 −0.017 0.056 (−0.61) (−0.3) (−0.19) (2.92)*** Count of provisions stipulating the liberalization of trade in services 0.010 0.004 0.012 0.000 (2.47)** (1.69)* (3.09)*** (−0.140) Share of direct VA attributed to high-skilled labor returns 0.201 0.054 0.023 0.118 (0.98) (0.58) (0.13) (1.33) Capital labor ratio 0.162 0.294 0.028 0.105 (2.75)*** (2.34)** (0.67) (1.42) Constant −0.379 −5.474 −7.748 −2.446 (−0.11) (6.41)*** (2.83)*** (3.21)*** Arellano–Bond test for AR(1) −1.115 −1.999** −2.122** −3.475*** Arellano–Bond test for AR(2) −1.172 −0.519 −1.426 −0.827 Observations 165 252 165 252 Robust z statistics in parentheses. Note: Year dummies included but not reported. Standard errors are heteroscedasticity robust. *, **, and *** indicate statistical significance at 10%, 5%, and 1%, respectively. Open in new tab Table A7. Estimations of BS value added in total exports Business services VA in exports Manufacturing VA in exports Emerging Advanced Emerging Advanced BS value added in exports lag 1 0.470 0.561 0.414 0.822 (2.29)** (8.34)*** (2.62)*** (6.41)*** BS value added in exports lag 2 0.037 0.078 −0.073 −0.052 (0.57) (1.99)** (1.99)** (0.63) BS (or manufacturing) value added in total final demand 0.344 0.152 0.579 0.074 (2.75)*** (2.99)*** (5.15)*** (2.29)** BS VA in exports of partners 1.828 0.954 −1.194 −0.496 (1.62) (3.01)*** (−1.27) (−2.50)** Manufacturing VA in exports of partners −1.070 0.303 4.194 1.308 (−0.98) (1.22) (3.01)*** (5.71)*** BS VA in final demand of partners −2.425 −0.255 0.704 0.441 (−2.99)*** (−0.94) (1.14) (2.52)** Manufacturing VA in final demand of partners 2.138 −0.065 −2.818 −0.789 (2.05)** (−0.22) (2.82)*** (3.31)*** Public expenditure on education over GDP −0.032 0.124 0.108 0.071 (−0.16) (1.19) (0.75) (1.61) R&D over GDP −0.032 0.031 −0.103 −0.084 (−0.51) (0.55) (−1.90)* (−1.85)* Hourly wage of high-skilled −0.317 −0.261 −0.217 −0.062 (2.02)** (3.08)*** (3.85)*** (−1.08) Internet users per 100 people −0.045 −0.007 −0.017 0.056 (−0.61) (−0.3) (−0.19) (2.92)*** Count of provisions stipulating the liberalization of trade in services 0.010 0.004 0.012 0.000 (2.47)** (1.69)* (3.09)*** (−0.140) Share of direct VA attributed to high-skilled labor returns 0.201 0.054 0.023 0.118 (0.98) (0.58) (0.13) (1.33) Capital labor ratio 0.162 0.294 0.028 0.105 (2.75)*** (2.34)** (0.67) (1.42) Constant −0.379 −5.474 −7.748 −2.446 (−0.11) (6.41)*** (2.83)*** (3.21)*** Arellano–Bond test for AR(1) −1.115 −1.999** −2.122** −3.475*** Arellano–Bond test for AR(2) −1.172 −0.519 −1.426 −0.827 Observations 165 252 165 252 Business services VA in exports Manufacturing VA in exports Emerging Advanced Emerging Advanced BS value added in exports lag 1 0.470 0.561 0.414 0.822 (2.29)** (8.34)*** (2.62)*** (6.41)*** BS value added in exports lag 2 0.037 0.078 −0.073 −0.052 (0.57) (1.99)** (1.99)** (0.63) BS (or manufacturing) value added in total final demand 0.344 0.152 0.579 0.074 (2.75)*** (2.99)*** (5.15)*** (2.29)** BS VA in exports of partners 1.828 0.954 −1.194 −0.496 (1.62) (3.01)*** (−1.27) (−2.50)** Manufacturing VA in exports of partners −1.070 0.303 4.194 1.308 (−0.98) (1.22) (3.01)*** (5.71)*** BS VA in final demand of partners −2.425 −0.255 0.704 0.441 (−2.99)*** (−0.94) (1.14) (2.52)** Manufacturing VA in final demand of partners 2.138 −0.065 −2.818 −0.789 (2.05)** (−0.22) (2.82)*** (3.31)*** Public expenditure on education over GDP −0.032 0.124 0.108 0.071 (−0.16) (1.19) (0.75) (1.61) R&D over GDP −0.032 0.031 −0.103 −0.084 (−0.51) (0.55) (−1.90)* (−1.85)* Hourly wage of high-skilled −0.317 −0.261 −0.217 −0.062 (2.02)** (3.08)*** (3.85)*** (−1.08) Internet users per 100 people −0.045 −0.007 −0.017 0.056 (−0.61) (−0.3) (−0.19) (2.92)*** Count of provisions stipulating the liberalization of trade in services 0.010 0.004 0.012 0.000 (2.47)** (1.69)* (3.09)*** (−0.140) Share of direct VA attributed to high-skilled labor returns 0.201 0.054 0.023 0.118 (0.98) (0.58) (0.13) (1.33) Capital labor ratio 0.162 0.294 0.028 0.105 (2.75)*** (2.34)** (0.67) (1.42) Constant −0.379 −5.474 −7.748 −2.446 (−0.11) (6.41)*** (2.83)*** (3.21)*** Arellano–Bond test for AR(1) −1.115 −1.999** −2.122** −3.475*** Arellano–Bond test for AR(2) −1.172 −0.519 −1.426 −0.827 Observations 165 252 165 252 Robust z statistics in parentheses. Note: Year dummies included but not reported. Standard errors are heteroscedasticity robust. *, **, and *** indicate statistical significance at 10%, 5%, and 1%, respectively. Open in new tab Table A8. System GMM estimations of BS value added in foreign exports for upper-middle and low and lower-middle income countries Upper-middle income Low and lower-middle income BS value added in foreign exports lag 1 0.453 0.361 (4.53)*** (3.44)*** BS value added in foreign exports lag 2 0.137 0.096 (1.72)* (1.98)** BS value added in total final demand 0.24 0.442 (2.43)** (2.88)*** BS VA in foreign exports of partners 0.772 6.331 (1.22) (4.61)*** Manufacturing VA in foreign exports of partners 1.139 −4.094 (1.94)* (−7.06)*** BS VA in final demand of partners −0.419 −4.556 (−0.58) (5.90)*** Manufacturing VA in final demand of partners −0.455 3.775 (−0.83) (11.60)*** Public expenditure on education over GDP 0.097 −0.277 (0.85) (−1.80)* R&D over GDP 0.374 −0.058 (4.93)*** (−0.91) Hourly wage of high-skilled workers −0.293 −0.159 (−2.68)*** (−0.51) Internet users per 100 people 0.084 −0.005 (1.31) (−0.05) Count of provisions stimulating the liberalization of trade in services 0.003 0.035 (0.8) (2.97)*** Share of direct VA attributed to high-skilled labor returns 0.017 0.347 (0.14) (1.99)** Capital labor ratio 0.109 0.082 (1.83)* (2.03)** Constant −4.834 0.069 (−3.19)*** (0.02) Observations 110 71 Number of countries 13 9 Upper-middle income Low and lower-middle income BS value added in foreign exports lag 1 0.453 0.361 (4.53)*** (3.44)*** BS value added in foreign exports lag 2 0.137 0.096 (1.72)* (1.98)** BS value added in total final demand 0.24 0.442 (2.43)** (2.88)*** BS VA in foreign exports of partners 0.772 6.331 (1.22) (4.61)*** Manufacturing VA in foreign exports of partners 1.139 −4.094 (1.94)* (−7.06)*** BS VA in final demand of partners −0.419 −4.556 (−0.58) (5.90)*** Manufacturing VA in final demand of partners −0.455 3.775 (−0.83) (11.60)*** Public expenditure on education over GDP 0.097 −0.277 (0.85) (−1.80)* R&D over GDP 0.374 −0.058 (4.93)*** (−0.91) Hourly wage of high-skilled workers −0.293 −0.159 (−2.68)*** (−0.51) Internet users per 100 people 0.084 −0.005 (1.31) (−0.05) Count of provisions stimulating the liberalization of trade in services 0.003 0.035 (0.8) (2.97)*** Share of direct VA attributed to high-skilled labor returns 0.017 0.347 (0.14) (1.99)** Capital labor ratio 0.109 0.082 (1.83)* (2.03)** Constant −4.834 0.069 (−3.19)*** (0.02) Observations 110 71 Number of countries 13 9 Robust z statistics in parentheses. *, **, and *** indicate statistical significance at 10%, 5%, and 1%, respectively. Open in new tab Table A8. System GMM estimations of BS value added in foreign exports for upper-middle and low and lower-middle income countries Upper-middle income Low and lower-middle income BS value added in foreign exports lag 1 0.453 0.361 (4.53)*** (3.44)*** BS value added in foreign exports lag 2 0.137 0.096 (1.72)* (1.98)** BS value added in total final demand 0.24 0.442 (2.43)** (2.88)*** BS VA in foreign exports of partners 0.772 6.331 (1.22) (4.61)*** Manufacturing VA in foreign exports of partners 1.139 −4.094 (1.94)* (−7.06)*** BS VA in final demand of partners −0.419 −4.556 (−0.58) (5.90)*** Manufacturing VA in final demand of partners −0.455 3.775 (−0.83) (11.60)*** Public expenditure on education over GDP 0.097 −0.277 (0.85) (−1.80)* R&D over GDP 0.374 −0.058 (4.93)*** (−0.91) Hourly wage of high-skilled workers −0.293 −0.159 (−2.68)*** (−0.51) Internet users per 100 people 0.084 −0.005 (1.31) (−0.05) Count of provisions stimulating the liberalization of trade in services 0.003 0.035 (0.8) (2.97)*** Share of direct VA attributed to high-skilled labor returns 0.017 0.347 (0.14) (1.99)** Capital labor ratio 0.109 0.082 (1.83)* (2.03)** Constant −4.834 0.069 (−3.19)*** (0.02) Observations 110 71 Number of countries 13 9 Upper-middle income Low and lower-middle income BS value added in foreign exports lag 1 0.453 0.361 (4.53)*** (3.44)*** BS value added in foreign exports lag 2 0.137 0.096 (1.72)* (1.98)** BS value added in total final demand 0.24 0.442 (2.43)** (2.88)*** BS VA in foreign exports of partners 0.772 6.331 (1.22) (4.61)*** Manufacturing VA in foreign exports of partners 1.139 −4.094 (1.94)* (−7.06)*** BS VA in final demand of partners −0.419 −4.556 (−0.58) (5.90)*** Manufacturing VA in final demand of partners −0.455 3.775 (−0.83) (11.60)*** Public expenditure on education over GDP 0.097 −0.277 (0.85) (−1.80)* R&D over GDP 0.374 −0.058 (4.93)*** (−0.91) Hourly wage of high-skilled workers −0.293 −0.159 (−2.68)*** (−0.51) Internet users per 100 people 0.084 −0.005 (1.31) (−0.05) Count of provisions stimulating the liberalization of trade in services 0.003 0.035 (0.8) (2.97)*** Share of direct VA attributed to high-skilled labor returns 0.017 0.347 (0.14) (1.99)** Capital labor ratio 0.109 0.082 (1.83)* (2.03)** Constant −4.834 0.069 (−3.19)*** (0.02) Observations 110 71 Number of countries 13 9 Robust z statistics in parentheses. *, **, and *** indicate statistical significance at 10%, 5%, and 1%, respectively. Open in new tab © The Author(s) 2019. Published by Oxford University Press on behalf of Associazione ICC. All rights reserved. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)
TI - When Linder meets Hirschman: inter-industry linkages and global value chains in business services
JF - Industrial and Corporate Change
DO - 10.1093/icc/dtz023
DA - 2019-12-01
UR - https://www.deepdyve.com/lp/oxford-university-press/when-linder-meets-hirschman-inter-industry-linkages-and-global-value-AYDamPziEQ
SP - 1555
VL - 28
IS - 6
DP - DeepDyve
ER -