Near-shoring is gaining traction in the Western Balkans, driven by geopolitical shifts and regulatory pressures to reduce carbon emissions. Relocating factories from Asia to Eastern Europe remains unlikely, owing to high costs, but Western firms are increasingly opting for Eastern Europe over Asia for new investments. Interestingly, Asian companies are also investing in the region to position themselves closer to the EU market. The recent shift to the right in global politics is likely to influence these trends in complex ways, but the greatest challenge for the Western Balkans lies in addressing the growing risk of a shortage of skilled workers.
Introduction
The concept of near-shoring first gained attention during discussions of ‘slowbalisation’ following the global financial crisis of 2007-2008 (Bakas 2015; The Economist 2019). Its relevance grew with the supply-chain disruptions caused by the COVID-19 pandemic (McKinsey & Co. 2020) and, more recently, the war in Ukraine (Agnew 2022).
In 2021, we published a study exploring whether the Western Balkan economies could benefit from near-shoring trends in the wake of the pandemic (Jovanović et al. 2021). Our findings indicated that the region could indeed capitalise on these trends if it were to focus on upskilling its workforce, enhancing infrastructure and strengthening governance.
More recently, we conducted a follow-up study that revisits and expands on these questions (Jovanović et al. 2024). This new research evaluates whether near-shoring has actually occurred in the Western Balkans, identifies examples of companies that have near-shored to the region, examines these cases in detail and investigates the factors driving the decisions to near-shore.
Trends in FDI in the Western Balkans
Our analysis begins with a quantitative examination of recent trends in foreign direct investment (FDI) inflows across the six Western Balkan economies, aiming to determine whether macroeconomic data indicate an increase in foreign investment following the pandemic.
The approach is straightforward: we analyse pre-pandemic FDI trends, extrapolate them to simulate expected post-pandemic inflows, and compare these simulations with actual data. If actual FDI inflows exceed the simulated values, we interpret this as evidence of near-shoring. The underlying assumption is that pre-pandemic trends represent the level of investment expected under a ‘business-as-usual’ scenario. Any excess in actual FDI over these projections suggests new factors driving increased investment, which we attribute to near-shoring.
To conduct this analysis, we use two complementary simulation methods. The first applies a simple logarithmic trend to total FDI inflows for each economy. The second employs econometric modelling to analyse macroeconomic factors influencing FDI, using four different models with different combinations of the following explanatory variables: sovereign credit ratings, rule of law, nominal GDP, and general government revenues. The analysis is performed separately for each Western Balkan economy, with the pre-pandemic period defined as 2012-2019 and the post-pandemic period as 2020-2023.
Figure 1 illustrates FDI inflows derived from both simulation methods alongside actual recorded inflows. Simulated values are represented as an orange range (spanning the lowest to highest estimates), while actual FDI inflows are shown as dark grey lines. The post-pandemic period is shaded in light grey for context.
The data reveal contrasting trends across the region. In Albania and Serbia, actual FDI inflows from 2020 to 2023 consistently fall below the simulated range, indicating no signs of near-shoring. Conversely, Bosnia and Herzegovina, Kosovo, and North Macedonia show actual FDI inflows exceeding the simulated range over the last two to four years, which we interpret as evidence of near-shoring in the post-pandemic period.
Montenegro represents a borderline case. Although FDI inflows exceeded the simulated range from 2020 to 2022, they fell below it in 2023. This makes it challenging to determine whether Montenegro is experiencing near-shoring or simply reflecting typical cyclical fluctuations in FDI.
Insights from case studies and interviews with companies
We identified examples of near-shoring to the Western Balkans, with such cases found in all economies except Montenegro. Notably, many of these investments come from Asian companies strategically positioning themselves in the region to be closer to EU business partners or to facilitate exports to the European market. In contrast, Western European companies that have near-shored to the Western Balkans have typically done so in preference to investing in Asia, drawn by the region’s low production costs and proximity to the EU. However, we found no evidence of companies closing operations in Asia to relocate to the Western Balkans, probably because of the high costs associated with such moves.
Interviews with foreign investors and other stakeholders underscore that multinational companies are actively discussing and implementing near-shoring strategies. Geopolitical developments, such as the war in Ukraine and growing global polarisation, are accelerating this trend. One prominent strategy gaining traction is the ‘local-for-local’ approach, in which companies locate production and other activities closer to their final markets.
The interviews also highlight the increasing importance of environmental sustainability and decarbonisation in shaping investment decisions. Regulatory pressures and consumer expectations are driving companies to reduce carbon emissions and shorten supply chains, further reinforcing the case for near-shoring.
Some tentative lessons for Europe and the world as a whole
Companies are actively considering and implementing near-shoring strategies, driven by two main factors. First, geopolitical tensions and rising global uncertainty are prompting firms to de-risk their operations and reduce costs. Second, there is increasing pressure to shorten supply chains and lower carbon emissions, arising both from regulatory demands and from expectations from partners seeking to minimise their own environmental impact.
Traditional near-shoring (for example, closing factories in Asia and relocating them to Eastern Europe) remains unlikely, as the costs involved are prohibitively high. Instead, Western companies already operating in Eastern Europe are likely to expand their activities there rather than investing in Asia. Similarly, new Western firms are expected to choose Eastern Europe over Asia for future investments.
Another significant trend involves Asian companies investing in Eastern Europe to be closer to the EU market. This allows them to sell directly within the EU and/or support EU-based companies more efficiently.
Recent geopolitical developments, such as the rise of far-right movements in Europe and Donald Trump’s return to power in the US, are likely to influence near-shoring dynamics in complex ways. On one hand, rising geopolitical uncertainty and global polarisation may accelerate near-shoring. Trade wars and the imposition of tariffs could incentivise Chinese and other Asian companies to establish operations in Eastern Europe to bypass EU tariffs. On the other hand, the anticipated rollback of environmental policies could reduce the regulatory and partner-driven incentives to near-shore.
The greatest challenge for near-shoring and FDI in Eastern Europe lies in the region’s growing shortage of skilled workers. This issue risks deterring foreign companies from investing. Governments must address this by expanding the pool of skilled workers through upskilling and reskilling initiatives, attracting foreign talent, and embracing greater automation. Additionally, there should be a stronger focus on high-tech industries that are less labour-intensive.
References:
Agnew, H. (2022). ‘Ukraine, supply chains and the end of globalisation’. Financial Times, 28 March. www.ft.com/content/bec75c62-a0e6-4ad1-8365-2671d40ef48e
Bakas, A. (2015). Capitalism & Slowbalization: The Market, the State and the Crowd in the 21st Century. Dexter.
Jovanović, B., Ghodsi, M., van Zijverden, O., Kluge, S., Gaber, M., Mima, R., et al. (2021). ‘Getting stronger after COVID-19: Near-shoring potential in the Western Balkans’. wiiw Research Report No. 453, May, wiiw, Vienna. https://wiiw.ac.at/getting-stronger-after-covid-19-near-shoring-potential-in-the-western-balkans-dlp-5814.pdf
Jovanović, B., Zlatanović, A., Kluge, S., Zec, A., Ibrahimi, M., Brašanac M. et al. (2024). Transforming the Western Balkans through near-shoring and decarbonisation. wiiw and Western Balkans 6 Chamber Investment Forum. Available at: https://wiiw.ac.at/transforming-the-western-balkans-through-near-shoring-and-decarbonisation-p-6999.html
McKinsey & Co. (2020). ‘Risk, resilience, and rebalancing in global value chains’. www.mckinsey.com/capabilities/operations/our-insights/risk-resilience-and-rebalancing-in-global-value-chains
The Economist (2019). ‘Slowbalisation: The steam has gone out of globalisation’, 24 January. www.economist.com/leaders/2019/01/24/the-steam-has-gone-out-of-globalisation
Authors:
Branimir Jovanović is Economist at wiiw and country expert for North Macedonia and Serbia. His current research interests lie mainly around economic inequality, poverty, fiscal policy, taxation, social policies, labour rights, as well as financial crises and post-crises recoveries. Previously, he has done research on monetary policy, credit activity, exchange rates, trade, FDI, remittances, current account sustainability, forecasting, house prices.
The interactive graphics were created by Alireza Sabouniha. He is university assistant and a PhD candidate at the Leopold-Franzens University Innsbruck
This article is based on a forthcoming research paper of the TWIN SEEDS Horizon Europe project, which explores the distribution of rents across business functions that are linked to (greenfield and brownfield) projects undertaken by subsidiaries of multinational enterprises (MNEs). We contrast the traditionally tested ‘Smile Curve’ that associates value added generation with different stages along global value chains (GVCs) with analysis of a wider set of distributional variables (mark-up rates as proxies of profit margins, wage rates, labour shares in value added and in turnover).
Introduction: The Significance of Rent Distribution in GVCs
The distribution of rents in global value chains (GVCs) has long fascinated economists and policy makers. The Smile Curve reveals that the highest value is generated at the pre-production and post-production stages, leaving the manufacturing segment with lower value-added activities. GVCs are undergoing a period of transformation, driven by technological advancements, geopolitical tensions and the transition to greener economies. These changes, coupled with the need for resilient supply chains, have reignited interest in understanding how value and rents are distributed across the different stages of production. ‘Rents’, in this context, refers to the economic gains from profit margins, wage levels and value-added shares.
The Smile Curve, a conceptual framework introduced by Mudambi (2008),[i] captures this distribution by illustrating that value creation is highest in upstream (R&D, design, headquarters and financing) and downstream (marketing, sales and logistics) activities; the production stage generates less value. By analysing the activities of the subsidiaries of multinational enterprises (MNEs), we can uncover the factors driving rent distribution across locations and functions. In this research, we contrast the traditionally tested Smile Curve that associates value added generation across the different stages along GVCs against a wider set of distributional variables (mark-up rates as proxies of profit margins, wage rates and labour shares in value added and in turnover). This article draws on a detailed analysis of Orbis data spanning over a decade to investigate the specialisation structures of MNE subsidiaries in their global operations and their distributional implications.
Understanding Functional Specialisation
MNEs play a pivotal role in shaping GVCs through their functional specialisation. They strategically allocate activities to locations that maximise efficiency and profitability. Our study categorises MNE business functions into five broad groups:
1. Headquarters – central decision-making and management.
2. R&D and ICT – innovation, technology development and digital infrastructure.
3. Finance and Business Services (FBS) – administrative and financial activities.
4. Production – core manufacturing activities.
5. Sales/Marketing/Logistics (SML) – distribution, marketing and customer engagement.
These categories allow us to explore how value and rents are distributed not only across functions but also across regions, distinguishing between global and European patterns.
Key Findings on Rent Distribution
1. The Smile Curve Holds for Value Added
Our analysis confirms the Smile Curve’s relevance. Value-added ratios (value added as a share of turnover) are consistently higher in headquarters, R&D and ICT, FBS, and SML than in production (Figure 1). This finding underscores the importance of high-skilled, knowledge-intensive activities in driving value creation.
2. Mark-ups (profits) are Lower in High-Value Functions
Contrary to traditional interpretations of the Smile Curve, which focus on value-added ratios, we find that profit margins tend to be lower in pre- and post-production functions than in production itself (Figure 1). This is partly a consequence of higher operating costs and greater competition in knowledge-intensive sectors. However, the broader economic gains in these segments often manifest through elevated wage rates and labour shares rather than through profits.
3. Labour Outcomes Reflect Functional Specialisation
Wage rates are significantly higher in pre- and post-production functions, reflecting a reliance on skilled labour. Labour shares in turnover and value added are also elevated, indicating stronger bargaining power and higher remuneration for skilled employees in these segments (Figure 2). In contrast, production functions are characterised by lower wages and labour shares, often relying on automation and cost-efficient practices.
Regional Patterns of Functional Specialisation
Our findings also reveal notable regional variations (Figure 3) in rent distribution across GVCs:
1. Global vs European Dynamics
At the global level, MNE subsidiaries exploit a wide range of wage differentials and market conditions, such as lower wage rates in lower-income countries and increased scope to achieve higher profit margins through the market power of MNEs. Within Europe, however, wage structures are less differentiated, owing to a generally more evenly distributed skilled labour force, and more harmonised labour market policies and regulations. European subsidiaries exhibit a smaller wage gap between production and non-production functions than their global counterparts.
2. The EU-CEE Advantage in R&D, ICT and SML
MNE operations (through their subsidiaries) in Central and Eastern European (CEE) member states show strong profit margins in R&D, ICT and SML functions. Value-added ratios in these functions surpass those in production, driven by relatively lower costs and a growing pool of skilled labour. These trends suggest that, from a cost perspective, EU-CEE economies are emerging as competitive hubs for innovation and logistics within GVCs.
Policy Implications
Policy makers must prioritise attracting high-value activities such as R&D, ICT and headquarters. This can be achieved through targeted incentives, investments in education, and infrastructure development to support functional upgrading.
Efforts to employ skilled labour forces across different business functions reduce disparities in rent distribution across functions. Such policies promote equitable wage structures, which would be supported by collective bargaining, and upskilling opportunities.
Ensuring transparency in how rents are allocated across GVCs is critical. Tax policies and reporting standards should discourage practices that concentrate profits in low-tax jurisdictions while neglecting the contribution of other functions and regions.
Outlook: The Future of Rent Distribution in GVCs
As global economies transition towards sustainability and digitalisation, the distribution of rents in GVCs is likely to evolve. Future research should investigate how these trends reshape functional specialisation and rent allocation. Additionally, granular data on intra-MNE transactions could provide deeper insights into the interplay between pricing strategies, wage bargaining, upgrading of skills and rent distribution.
Conclusion
The Smile Curve remains a powerful framework for understanding the distribution of rents in GVCs. Our findings highlight the crucial role of functional specialisation in shaping value creation and rent allocation. Policy makers must leverage these insights to enhance labour market outcomes, and position their economies as attractive hubs for high-value activities that also promote equitable growth.
[i] Mudambi, R. (2008). Location, control and innovation in knowledge-intensive industries. Journal of Economic Geography, 8(5), 699-725.
Authors:
Mahdi Ghodsi is an economist at the Vienna Institute of International Economic Studies, a lecturer at the Vienna University of Economics and Business, and Senior Fellow and Head of the Economy Unit at the Center for Middle East and Global Order.
Michael Landesmann is Senior Research Associate at wiiw and Professor of Economics at the Johannes Kepler University Linz.
The interactive graphics were created by Alireza Sabouniha. He is research assistant at wiiw and a PhD candidate at the Leopold-Franzens University Innsbruck.
The EU Carbon Border Adjustment Mechanism (CBAM) is now in its transitional phase and will fully enter into force from 1 January 2026. We assess the impacts of such tariffs on CO2-intensive imports on welfare, income and emissions, employing a general equilibrium framework. For the EU, we find an increase in the terms of trade and consequently small positive welfare effects, whereas there are tiny negative effects on real wages. Although global CO2 emissions have been reduced, specialisation effects have led to a slight increase in emissions in the EU.
Introduction
The EU Carbon Border Adjustment Mechanism (CBAM), which is now in its transitional phase, aims to establish a comparable carbon pricing level between goods of different origins, regardless of whether production takes place inside or outside the EU. The CBAM has two main goals. The first is to reduce the risk of carbon leakage, i.e. the relocation of production facilities to non-EU countries with less stringent climate regulations. The second is to create an incentive for producers in non-EU countries to reduce emissions in the manufacturing process. The CBAM has been applied since 1 October 2023; its transitional phase spans the period to the end of 2025. It should be fully implemented from 1 January 2026. The first reporting period ended on 31 January 2024. From 1 January 2025, each importer or their representative is obliged to apply for authorisation as a CBAM declarant before importing CBAM goods. In the first phase of the CBAM, the sectors covered are cement, iron and steel, aluminium, fertilisers, electricity, and hydrogen. From 2026, CBAM certificates must be purchased when importing certain goods whose production in third countries has resulted in greenhouse gas (GHG) emissions. The quantity of CBAM certificates to be purchased depends on the quantity of GHG emissions generated during production; the price of CBAM certificates is based on the price of EU emissions trading system (ETS) certificates at the time the goods are imported. The costs imposed by CBAM on imports therefore correspond to those that would have been incurred by the emission of GHGs and the associated purchase of EU ETS allowances in the case of production within the EU.
From an economic modelling point of view, the CBAM constitutes a tariff on imports in certain industries, focusing on CO2 emissions. In Flórez Mendoza et al. (2024), we assess the implications of such tariffs, employing a general equilibrium model following the approach of Caliendo and Parro (2015), using novel data OECD-ICIO 2023 multi-country input-output tables, which provide data for 76 countries and 45 industries combined with information on CO2 emissions at the same industry classification for the most recent available year (2020).
Welfare effects of the EU CBAM
The tariffs depend on the price of the EU ETS certificates, which we assume to be EUR 100 for CO2 emissions in our base scenario. Of the 45 industries in our data, nine are affected by such tariffs. The most important are energy (NACE D), petroleum (NACE C19), minerals (NACE C23) and metals (NACE C24), with tariff equivalents up to 10%, assuming a carbon price of EUR 100.
The economic implications of such tariffs imposed by the EU and EFTA countries are presented in Figure 1. First, the terms of trade are improving for the EU as the products are inelastically supplied and hence EU import prices net of tariffs are decreasing, whereas export prices are rising. Consequently, the EU experiences an increase in welfare, which according to the model amounts to 0.016% in the base scenario of a carbon price of EUR 100, whereas terms of trade and welfare decline by 0.005% in the other countries. Global welfare hence declines only marginally. Owing to overall lower demand, real wages decline in all country groups, but most strongly in the EU (by 0.025%). As shown in Figure 1, the higher the underlying carbon price, the larger these effects are.
Effects on global CO2 emissions
The change in CO2 emissions in this framework is solely driven by changes in specialisation patterns. Because of the tariffs, EU specialisation in CO2-intensive industries increases, and thus CO2 emissions rise by 0.72% in the EU in the base scenario of a carbon price of EUR 100, as indicated in Figure 2. The opposite occurs for the other countries, in which CO2 emissions decline by 0.143%. The global effect is ambiguous, depending on overall CO2 intensities in both country groups. However, as production in EU countries is in general less CO2-intensive than in the other countries and as production of CO2-intensive industries shifts towards the EU, global CO2 emissions are reduced by 0.08%. The higher the carbon price, the stronger the specialisation effects towards the EU, and therefore CO2 emissions in the EU increase more strongly and consequently decline more strongly globally (see Figure 2).
Conclusions
These results first indicate a small positive environmental impact at the global level, as the introduction of the EU CBAM reduces overall CO2 emissions by reducing production of goods in countries with high CO2 intensities and increasing production in countries with low CO2 intensities. The effect on global emissions is, however, relatively small. Second, our simulations show that welfare is increasing in those countries that are participating in the CBAM (EU and EFTA countries). Conversely, the other countries see their welfare decrease. As with the findings for CO2 emissions, the magnitude of these changes is relatively small. Third, the higher the underlying carbon price, the greater the impacts on all variables presented. Again, this is to be expected as a higher carbon price implies a higher applied tariff rate.
The CBAM, however, leads to an increase of CO2 emissions in the EU, owing to the resulting specialisation effects. It should be emphasised that this approach does not consider the effect that higher import costs (and eventually rising CO2 prices) are incentives for firms to use less CO2-intensive technologies. On top of that, sector-specific strategies within the EU’s broader climate policy framework could enhance such a technological shift (see Draghi, 2024, Chapter 3). Policy makers should focus on high-emitting sectors, such as energy and heavy industry, and provide incentives for climate-friendly technologies. Meanwhile, lower-emitting industries could benefit from policies that maintain progress and encourage further green innovation. Such an approach aligns with the EU’s climate agenda and ensures an effective transition to a low-carbon economy while strengthening the EU’s competitive position.
References:
Caliendo, L. & F. Parro (2015), Estimates of the trade and welfare effects of NAFTA, The Review of Economic Studies, Vol. 82(1), pp. 1-44.
Draghi, M. (2024), The future of European competitiveness – Part A: A competitiveness strategy for Europe, European Commission.
Flórez Mendoza, J., O. Reiter & R. Stehrer (2024), EU carbon border tax: General equilibrium effects on income and emissions, wiiw Working Paper, The Vienna Institute for International Economic Studies (wiiw), forthcoming.
Korpar, N., M. Larch & R. Stöllinger (2023), The European carbon border adjustment mechanism: a small step in the right direction, International Economics and Economic Policy, Vol. 20(1), pp. 95-138.
Robert Stehrer is Scientific Director at wiiw. His expertise covers a broad area of economic research, ranging from issues of international integration, trade and technological development to labour markets and applied econometrics. His most recent work focuses on the analysis and effects of the internationalisation of production and value-added trade. Other contributions relate to the connection between digitalisation, demographics, productivity and labour markets. He studied economics at the Johannes Kepler University Linz, Austria, and sociology at the Institute for Advanced Studies (IHS) in Vienna and is lecturer of economics at the University of Vienna.
Javier Flórez Mendoza is an economist at the Vienna Institute for International Economic Studies (wiiw). His research focuses on international trade, trade policy, European integration, environmental economics and regional economics. He is a PhD candidate at the Vienna University of Economics and Business.
The interactive graphics were created by Alireza Sabouniha. He is research assistant at wiiw and a PhD candidate at the Leopold-Franzens University Innsbruck.
The US presidential candidate has announced massive tariff increases on US imports in general and against Chinese imports in particular in the event of his re-election. Such measures would further destabilise the global trading system and would also have a direct negative impact on incomes in export markets such as the EU and China. However, the consequences would be even greater for the US itself, as our calculations using a multi-sectoral equilibrium model show.
Introduction
As unpredictable as the outcome of the US presidential election on 5 November is, the possible consequences for international economic policy and the global trading system are just as uncertain. However, the latter depend not only on whether Kamala Harris or Donald Trump wins, but also on the but also on the post-election composition of the US Congress and the ideologies of its members. Harris and Trump pursue some of the same goals, such as protecting domestic industry, securing jobs, relocating lost industries back to the US, maintaining the country’s technological leadership and reducing US dependence on international supply chains. Nevertheless, their approaches differ considerably in terms of the radical nature of the planned measures, and the speed and method of their implementation. One major substantive difference concerns climate and environmental policy, where only Harris can be expected to take a constructive approach (see Stehrer, 2024).
The proposed tariff increases
One of Trump’s most important threats is the announced tariff increases to 10% for all US imports and possibly to 60% (or more) for imports from China; Trump has floated even higher tariffs at his campaign rallies. To assess the impact of such rises, it is first necessary to examine the current tariff rates (see Figure 1). On average, the EU imposes tariffs of 5.2% on the US and China; the US imposes tariffs of 3.5% on the EU and 3.6% on China. China imposes higher average tariffs of 7.5% on the EU and 7.6% on the US. The announced increase in US import tariffs to 10% under Trump would therefore mean a near-threefold increase.
Effects of these tariffs in a general equilibrium model
The effects of such tariff increases can be estimated using general equilibrium models. Calculations based on the model using the approach taken by Caliendo and Parro (2015) – for details, see Flórez Mendoza et al. (2024) – show that if US import tariffs were to rise to at least 10% (assuming that higher tariffs remain unchanged), total income in the US, including tariff revenue, would rise by 0.08%. However, real income excluding tariff revenue would fall by around 0.14%, mainly because imports would become more expensive. Incomes in China would fall by around 0.02%, while EU countries would be slightly more affected, with a decline of 0.05%. If tariffs on imports from China were increased to 60%, US income (including customs revenue) would rise by 0.12%, but real income would fall even more sharply, by 0.33%. In China, income losses in this scenario would be slightly higher, at 0.15%. For the EU27, the fall in income would be roughly unchanged. Overall, the global trade volume would fall slightly.
Conclusions
Our estimates show that the announced tariff increases on US imports would hit real incomes in the US itself the hardest; Clausing and Lovely (2024) and Baldwin (2024) argue similarly. The planned tariff increases would also have a (relatively) minor negative impact on the incomes of US trading partners.
Overall, it should be emphasised that our calculations build on the assumption of full employment and do not take any other factors into account. Relevant factors would include retaliatory measures and thus tariff increases by other countries against US imports, or further negative growth effects due to uncertainties and a decline in global trade flows. Such developments would result in stronger negative overall effects.
Although the announced tariff increases would have manageable overall effects on incomes and global trade, it can be assumed that such unilateral measures would further destabilise the international trading system under a Trump presidency.
References
Baldwin, R. (2024), Will Trump’s tariffs on China harm US manufacturing?, Factful Friday (via LinkedIn).
Caliendo, L. & F. Parro (2015), Estimates of the trade and welfare effects of NAFTA, The Review of Economic Studies, Vol. 82(1), pp. 1-44.
Clausing, K.A. & M.E. Lovely (2024), Why Trump’s tariff proposals would harm working Americans, PIIE Policy Brief 24-1, Peterson Institute for International Economics, May.
Flórez Mendoza, J., O. Reiter & R. Stehrer (2024), EU carbon border tax: General equilibrium effects on income and emissions, wiiw Working Paper, The Vienna Institute for International Economic Studies (wiiw), forthcoming.
Stehrer, R. (2024), Mögliche Auswirkungen der US-Präsidentschaftswahl auf den Welthandel, FIW-Jahresgutachten – Update Oktober 2024, Kapitel 2. Abrufbar unter: https://www.fiw.ac.at/publications/fiw-jahresgutachten-update-oktober-2024
Authors:
Robert Stehrer is Scientific Director at wiiw. His expertise covers a broad area of economic research, ranging from issues of international integration, trade and technological development to labour markets and applied econometrics. His most recent work focuses on the analysis and effects of the internationalisation of production and value-added trade. Other contributions relate to the connection between digitalisation, demographics, productivity and labour markets. He studied economics at the Johannes Kepler University Linz, Austria, and sociology at the Institute for Advanced Studies (IHS) in Vienna and is lecturer of economics at the University of Vienna.
Oliver Reiter is an economist and data scientist at the Vienna Institute for International Economic Studies (wiiw). His research focuses on international trade, non-tariff measures in trade, the creation/updating of a multi-regional input-output database (such as WIOD) and agent-based macroeconomic models. He holds a Bachelor’s and a Master’s degree in Economics, a Bachelor’s degree in Statistics and a Master’s degree in Computer Science, all from the University of Vienna. He is currently pursuing his doctorate at the Vienna University of Economics and Business.
The interactive graphics were created by Alireza Sabouniha. He is research assistant at wiiw and a PhD candidate at the Leopold-Franzens University Innsbruck.”
A few countries account for the bulk of global trade flows. Recently emerging geopolitical country groups, such as BRICS, account for about one fifth of global exports, although this share is mostly due to China. Grouping countries into a Western group (including the US and European economies) and a group oriented towards China shows that the former accounts for almost two thirds of world trade and the latter for less than one third. As some recent literature shows, increasing geopolitical fragmentation could have strong negative impacts.
In addition to the traditionally considered forces shaping bilateral trade (e.g. the size of the trading partners, distance in geographic or cultural terms, language barriers or bilateral trade policy measures), geopolitical developments are prone to increasingly determine global trade flows (see Bosone et al. 2024). Specifically, since Russia launched its illegal, full-scale war of aggression on Ukraine in 2022, geopolitical alliances have been growing more important and the trend towards a bi- or multi-polar geopolitical and economic world order seems more and more irreversible. In this spotlight, we provide selected evidence on the patterns of bilateral trade flows between country groups defined from a recent geopolitical perspective.
Just a few countries account for the lion’s share of global trade flows
About half of global export flows are generated by only 10 countries, including China (with 16%), the United States (9%) and Germany (8%). The same applies to imports, with the United States also leading (with almost 15%), followed by China (10%) and Germany (7%). In addition, 75% of exports can be attributed to 21 countries and 90% of exports to 38 countries (out of more than 230 countries in total). The same applies to imports, with 20 countries accounting for 75% and 41 countries accounting for around 90% of global imports. In comparison, Austria accounts for roughly 1% of global trade in goods.
Global trade by geopolitical country groups
From a geopolitical perspective, it is more informative to consider world trade patterns by looking at groups of countries. For example, the Group of Seven (G7) is an intergovernmental political and economic forum consisting of Canada, France, Germany, Italy, Japan, the United Kingdom and the United States, with the European Union (EU) being a ‘non-enumerated member’. According to our data, the G7 countries account for around a third of global exports, or roughly twice as much as China.
One country group that is gaining in terms of geopolitical relevance is the one known as BRICS[1] (comprising Brazil, Russia, India, China and South Africa), which aims at breaking the dominance of the Western economies and changing the geopolitical and economic orders (see also Holzner 2024). But how important is BRICS trade compared to that of other large groups or economies? In Figure 2, which shows the shares of bilateral trade flows in global trade, BRICS accounts for about one fifth of global exports and 15% of global imports. One should note, however, that these shares are dominated by China, which is responsible for three quarters of BRICS exports (remainder: India 9%, Brazil 7.5%, Russia 6.3%, and South Africa 3%). The EU27 still accounts for almost one third of global exports and imports, with about 20% being intra-EU27 trade flows. The United States accounts for about 10% of global exports (which is roughly equivalent to the share of the EU27 excluding intra-EU27 trade) and 15% of global imports. For the remaining countries (which including some of the top 10 exporters mentioned above, such as Canada, Japan, South Korea and Mexico), the share is about 38%.
However, the BRICS group is itself a rather heterogenous group of countries (which is even more the case for BRICS+). Given these circumstances, one might group the countries differently into the following groups[2]: ‘US allies’ (in addition to the United States, these would be: Canada; the EU27 countries; other European economies, including Switzerland, Norway and the United Kingdom; Japan; Australia; and New Zealand); ‘US leans’ (e.g. Colombia, Mexico, Morocco, Turkey and South Korea); ‘China leans’ (including many countries in Africa and Asia); and ‘China allies’ (e.g. in addition to China, these would be Iran, North Korea, Pakistan and Russia). The non-allied countries would be Brazil, India, Indonesia and Nigeria.
In the following, we combine the ‘US leans’ and ‘US allies’ to form a ‘Western bloc’ as well as the ‘China leans’ and ‘China allies’ to form a ‘China bloc’. The global trade shares according to these blocs are presented in Figure 3. Although these allocations are blurred to a certain extent, the broad patterns are visible: while almost two thirds of global exports originate from the Western bloc, slightly less than 30% originate from the China bloc. The remaining countries account for about 10% of global exports. It is also interesting to note that trade within the Western bloc makes up about half of world exports, whereas trade within the China bloc is only responsible for around 9% of global trade. Another important fact is that more than half of the China bloc exports (or 16% of world exports) are shipped to the Western bloc, whereas only around 16% of Western bloc exports (10% of world exports) are shipped from these countries to countries in the China bloc.
From an import perspective, one finds that the Western bloc accounts for 69% of global imports, which is higher than the share in global exports (62%) and therefore indicates a trade deficit. The opposite is the case for the China bloc, which accounts for 22% of imports (compared to the share of 28% in world exports).
The costs of increasing geopolitical fragmentation
This note shows some stylised facts about the geometry of trade within and between country groups defined along geopolitical dimensions. These bilateral patterns also hint at the existence of strong mutual relationships from both an import-dependency and a foreign-market-reliance point of view for all trading partners involved, as has been documented in some recent literature. Continuing and increasing geopolitical distance will therefore likely backfire for all countries, as indicated by some literature. For example, Góes and Bekkers (2022) find that a potential decoupling of the global trading system into two blocs – namely, a US-centric and a China-centric bloc – would significantly reduce global welfare. Results pointing in the same direction are documented in Campos et al. (2023a, 2023b). Finally, results summarised in Aiyar et al. (2023) indicate that the costs from trade fragmentation will be equivalent to between 0.2% and 7% of GDP, depending on the specific scenario, modelling assumptions and country blocs considered. With the addition of technological decoupling, the loss in output could reach 8% to 12% in some countries. Given these strong negative impacts, it would be of mutual interest to all countries to maintain and secure the rules-based multilateral trading system currently in place.
[1] The term ‘BRIC’ was coined in 2001 by Jim O’Neill, then chief economist at Goldman Sachs. The organisation was officially launched in 2006 and expanded to include South Africa in 2010. Since 2024, the organisation has also included Egypt, Ethiopia, Iran, Saudi Arabia and the United Arab Emirates, leading its name to be changed to ‘BRICS+’. Argentina rejected membership in the group after Javier Milei became its president in late 2023.
[2] This is inspired by www.ft.com/content/28f0f57a-df50-442c-9f8e-75672d012742, which is itself based on www.capitaleconomics.com/key-issues/fracturing-global-economy.
Author:
Robert Stehrer is Scientific Director at wiiw. His expertise covers a broad area of economic research, ranging from issues of international integration, trade and technological development to labour markets and applied econometrics. His most recent work focuses on the analysis and effects of the internationalisation of production and value-added trade. Other contributions relate to the connection between digitalisation, demographics, productivity and labour markets. He studied economics at the Johannes Kepler University Linz, Austria, and sociology at the Institute for Advanced Studies (IHS) in Vienna and is lecturer of economics at the University of Vienna.
The interactive graphics were created by Alireza Sabouniha. He is research assistant at wiiw and recently completed his master’s degree in Economics at the WU (Vienna University of Economics and Business).
This spotlight analyses the impact of new technologies on the employment of migrant and native workers in the EU. First, the level of labour migration in selected EU member states (including Austria) and how it has developed in recent years is presented. It then summarises how new technologies are affecting domestic and migrant labour while focusing on the influence of innovations and robotisation.
Technological Advancements and Migrant Employment: An EU Perspective
The impact of technological advancement, such as robotisation and digitalisation, on migrant employment will almost certainly reshape the labour market dynamics within the European Union (EU). The transformation brought about by these novel technologies has been profound, particularly in industries like manufacturing, where the potential substitution of workers and migrant workers, in particular, by robots could lead migrants to seek an alternative. Analysing such a scenario requires a deeper knowledge of the specific migrant jobs affected by these technologies, which is investigated in detail in Ghodsi et al. (2024).
Migrants are often employed in specific tasks that may be particularly vulnerable to automation or necessitate digital skills. Identifying the migrant jobs linked to technological adoption offers insights into the potential risks and opportunities for this segment of the workforce in an economy increasingly characterised by automation and digitalisation. This is particularly important for the EU labour market, as the share of migrant workers in the EU has increased from less than 9% in 2005 to about 14% in 2019 (see Figure 1 below), according to the EU Labour Force Survey (EU-LFS).
The Role Of Migrant Workers In Selected EU Countries
Figure 2 reveals significant variations in the shares of migrant worker across EU countries, with Luxembourg leading at 52%. This is significantly higher than Austria (19%) and Sweden (18%), while Slovakia, Czechia and Lithuania had the lowest shares, which ranged from 1% to 4%. Austria thereby has the second-largest share of migrant workers in the EU in terms of total workforce. Luxembourg, uniquely, had more EU than non-EU migrant workers, largely due to its attractive location, high wages and the presence of EU institutions, all of which naturally make it a prime destination for skilled workers. In contrast, the Baltic states and Slovakia have the lowest shares of EU migrant workers, at less than 1%. Non-EU migrant workers predominated in Sweden, Germany, Spain and Austria, with shares of up to 13%, with the reasons often having to do with geographical and historical connections with non-EU countries.
The distribution of migrant workers across occupations and countries from 2015 to 2019 shows heterogeneous employment patterns. As documented in Figure 3, migrant workers were predominantly found in service and sales occupations (ISCO 5), with shares ranging from above 30% in countries such as Greece and Spain to just over 10% in Lithuania and Slovenia. The lowest employment level of migrant workers was in skilled agricultural, forestry and fishery sectors (ISCO 6). A significant number also held high-skill professional roles (ISCO 2), especially in Luxembourg, which had the highest proportion (46%), as well as in Lithuania and Denmark (both 28%).
In terms of overall employment, as Figure 4 shows, migrants were mostly employed in lower-skilled roles, such as service and sales positions (ISCO 5) and elementary occupations (ISCO 9). While having migrants make up 75% of the total workforce for the latter category, Luxembourg also had an unusually high percentage (83%) of migrant workers in high-skill managerial positions (ISCO 1), vastly outstripping other nations.
As Figure 5 and Figure 6 show, migrant distribution also varied by the migrants’ education levels. While most countries showed a prevalence of migrants with medium education levels, Italy, Greece and Spain had higher proportions of low-educated migrants, which has to do with these countries’ geographical proximity to countries with lower average education levels. In contrast, Luxembourg had a notably high percentage (55%) of highly educated migrants, which suggests a mismatch, as this exceeds the proportion in high-skill occupations, which in turn indicates potential overeducation.
The Dual Impact of the Technological Revolution on Native and Migrant Workers
Given these differences in employment patterns, the technological revolution is expected to impact employment opportunities for both native and migrant workers in different ways. Analysing this relationship allows for an assessment of potential labour market outcomes and the identification of disparities, thereby informing policy decisions aimed at mitigating negative impacts while fostering inclusive growth. This is important, as the integration of migrant workers into the labour market and society at large is closely linked with their employment prospects. Thus, understanding how technological adoption affects migrant employment patterns is crucial for addressing challenges related to social integration, economic well-being and societal cohesion. In this respect, the findings in Ghodsi et al. (2024) can be summarised as follows:
First, innovations boost migrant employment. The study reveals that technological innovations, quantified by the number of granted patents, tend to increase both the absolute number and the proportion of migrant workers within the workforce. This indicates a positive correlation between novel technologies and migrant employment opportunities.
Second, robots replace jobs, but less so for migrants. While robot adoption does lead to job displacement, the impact is more pronounced for native workers than for migrant workers. This results in a relative increase in the share of migrant workers, suggesting that migrant jobs and tasks may be less vulnerable to automation-related displacements.
Third, digitalisation shows mixed effects. The adoption of digital assets shows heterogeneous effects on migrant employment; while some digital technologies positively influencing migrant employment, others do not have any significant impact.
The research highlights the diverse effects of technological change on migrant employment, providing crucial insights for policies aiming to foster economic inclusivity and social cohesion. To support skill development, it is imperative for policy makers to promote lifelong learning and skills enhancement among both native and migrant workers, thereby enhancing their ability to adapt to technological shifts. Support needs to be directed towards groups most vulnerable to the impacts of automation and digitalisation, particularly in the most affected sectors and occupations. Re-training and up-skilling are also needed to help both native and migrant workers to adopt new technologies.
Authors:
Mahdi Ghodsi is an economist at the Vienna Institute of International Economic Studies, a lecturer at the Vienna University of Economics and Business, and Senior Fellow and Head of the Economy Unit at the Center for Middle East and Global Order.
Robert Stehrer is Scientific Director at the Vienna Institute of International Economic Studies.
The interactive graphics were created by Alireza Sabouniha. He is research assistant at wiiw and recently completed his master’s degree in Economics at the WU (Vienna University of Economics and Business).
Austria’s exports depend to a large extent on foreign inputs, which amounted to 40% of the value of gross exports in 2021 (though many industries had an even larger share). If we include intermediate imports in the picture, exports accounted for about 30% of Austrian GDP; services also contributed significantly via inter-industry linkages.
How much do Austrian exports contribute to Austria’s GDP? This question is important, since for small open economies like Austria’s, foreign markets are important for products ‘Made in Austria’. To answer it, one must consider the fact that many of the goods produced in Austria directly and indirectly embody intermediate products imported from abroad, like raw materials and energy, semi-finished products, or high-tech components like computer chips. So-called Multi-Country Input-Output Tables (MC IOTs) allow us to calculate such indicators and the contribution of exports to Austria’s GDP. In this note we highlight some selected patterns and trends, taking a ‘value-added perspective’ of trade. In the first place, this allows inter-country and inter-industry linkages to be taken into account. Secondly, using such data also enables us to simultaneously consider the role of services and their contribution to the production of exports.
The import content of exports
The first question is the extent to which the production of exports relies on intermediate imports, expressed in value-added terms. This is presented in Figure 1, which shows the so-called ‘import content of exports’, based on the FIGARO data released by Eurostat/JRC (for further technical detail and an overview of the indicators, see Stehrer, 2022) from 2010 to 2021 (the latest year available). Whereas in 2010, the share of foreign value added in Austrian total gross exports (including all industries) was about 36%, by 2021 that figure had increased to over 40%. The numbers conceal a large variation across industries, however. Figure 2 therefore shows the foreign import content of each industry’s gross exports for 2010C and 2021. This direct and indirect reliance on imports is highest in manufacturing industries, with almost 73% in C19 (Manufacture of coke and refined petroleum products) and 65% in C29 (Manufacture of motor vehicles, trailers and semi-trailers). In eight industries, the share is over 50%.
Austria’s value-added exports
Given this (in part) heavy reliance on imports to produce exports, the second question is the extent to which exports contribute to a country’s GDP. Put differently: how much value added produced in Austria is absorbed in other countries due to final consumption abroad? The answer – as presented in Figure 3 – is that Austria’s value-added exports amount to about 30% of total value added. This is lower than the usual measure of a country’s openness, defined as a country’s gross exports as a percentage of total value added, which amounts to over 50%. The difference is due to the imported intermediate inputs to produce a country’s exports.[1]
This value-added perspective of trade also leads to an alternative view concerning the relative importance of industries for Austria’s exports. Specifically, due to strong inter-industry linkages, some service industries contribute significantly to Austria’s value-added exports. Figure 4 compares the share of each industry in Austria’s gross exports with its share in Austria’s value-added exports in 2021. For example, the industry G46 (Wholesale trade, except of motor vehicles and motorcycles) contributes more than 10% to Austria’s value-added exports, whereas the share in terms of gross exports is much less, at about 7%. One finds similar patterns (with the contribution to value-added exports being larger than the contribution to gross exports) for industries like M69_70 (Legal and accounting activities), K64 (Financial service activities, except insurance and pension funding) and H49 and H52 (Transport activities), to name but a few. Such business services are thus very relevant for the production of other industries’ exports which rely on their inputs.
Conversely, whereas C28 (Manufacture of machinery and equipment n.e.c.) contributes more than 10% of Austria’s gross exports, its share in terms of value-added exports is 6.3%, as it also relies on value added created in other industries (and foreign inputs, as discussed above). This also applies to other (mostly manufacturing) industries like C10T12 (Manufacture of food products), C24 (Manufacture of basic metals), C29 (Manufacture of motor vehicles, trailers and semi-trailers) or C20 (Manufacture of chemicals and chemical products).
Concluding remarks
In this note, we have highlighted some important aspects when considering Austria’s trade patterns from a value-added perspective. This, first, allows us to account for the importance of imported intermediate inputs in producing gross exports. Second, it indicates that when taking these intermediate imports into account the share of value-added exports in GDP is about 30% – lower than the usual measure of openness, defined as gross exports over GDP. Finally, third, this perspective allows us to consider the important role of (business) services and the way in which these contribute to other industries’ production of exports.
[1] We disregard some subtle differences between these two measures (e.g. taking re-imports of value added into account, etc.). Further, the openness measure can vary due to differences in the respective data sources.
Author:
Robert Stehrer is Scientific Director at wiiw. His expertise covers a broad area of economic research, ranging from issues of international integration, trade and technological development to labour markets and applied econometrics. His most recent work focuses on the analysis and effects of the internationalisation of production and value-added trade. Other contributions relate to the connection between digitalisation, demographics, productivity and labour markets. He studied economics at the Johannes Kepler University Linz, Austria, and sociology at the Institute for Advanced Studies (IHS) in Vienna and is lecturer of economics at the University of Vienna.
The interactive graphics were created by Alireza Sabouniha. He is research assistant at wiiw and recently completed his master’s degree in Economics at the WU (Vienna University of Economics and Business).
The political and economic interests of the heterogeneous group of countries under China’s leadership are too diverse to seriously challenge Western supremacy. However, as a bloc, the BRICS Plus members would be in a position to pressure the West in terms of global reserves of raw materials.
Not everyone is happy with the current balance of power in the world. The BRICS states of Brazil, Russia, India, China and South Africa want to change the geopolitical and geoeconomic order and form a collective counterweight to the United States and the West. At the beginning of 2024, the alliance was expanded by five countries and is now called BRICS Plus, although Argentina rejected its invitation at the last minute at the instigation of its new president, Javier Milei.
At this point, let’s have a brief digression on the history of its creation. The post-Cold War era has been dominated by the so-called Pax Americana, which – until recently – has provided a relatively stable order in which the US and its allies have largely set the geopolitical and geoeconomic tone. The vast majority of world trade is conducted in US dollars, and in international bodies and organisations such as the International Monetary Fund and the World Bank the US is the dominant heavyweight alongside the other G7 states. In 2009, Brazil, Russia, India and China founded the BRIC group of states in the hopes of changing this. When South Africa joined in 2010, BRIC became BRICS. At the beginning of 2024, Saudi Arabia, Iran, the United Arab Emirates (UAE), Egypt and Ethiopia joined on the initiative of Beijing, turning BRICS into BRICS Plus. Chinese President Xi Jinping particularly hopes that this will open up new opportunities in his efforts to end America’s global dominance.
End of American dominance and protection against sanctions
While three of the new BRICS Plus members – Saudi Arabia, Iran and the UAE – are important oil and gas producers, Egypt and Ethiopia are key players in Africa with large populations. With its economy suffering massively under US economic sanctions, Iran is urgently looking for new trading partners. All these middle powers have a common interest, which the well-known political scientist Ivan Krastev formulated as follows: they want to be at the table and not on the menu. In other words, they want to trade as little as possible via the US-dominated international financial system, they want to be less dependent on the West and, above all, they want to take the bite out of any Western economic sanctions. These aims are precisely why bringing some major fossil fuel producers into the bloc has a particular appeal to China, the leading BRICS power. Beijing could be preparing for war against Taiwan – at least as an option. In the various war scenarios that China’s leadership is probably playing through, possible sanctions by the West are likely to play a prominent role, especially given the harsh punitive measures taken against Russia following its full-scale invasion of Ukraine. Having Saudi Arabia, Iran and the UAE on its side in the event of a conflict would be economically vital for the supply of oil and natural gas as well as politically helpful.
Heterogeneous alliance
But how realistic is the prospect of establishing a new world order and dislodging the US dollar as the global reserve currency? Apart from their scepticism towards the US-dominated international economic and financial system, the BRICS Plus members do not share much in common. On the contrary, India and China have been engaged in a bloody border conflict in the Himalayas for decades. New Delhi has clearly taken Washington’s side in the geopolitical struggle between the US and China while also being politically and militarily supported by the latter. Moreover, while India’s economy is still relatively closed and primarily focused on the domestic market, China’s is closely intertwined with those of the US and the EU, even if there are tendencies towards decoupling. On the other hand, Saudi Arabia and Iran are arch-enemies who only resumed diplomatic relations in May 2023 under Chinese mediation and remain hostile to each other in the Middle East. While Saudi Arabia maintains a strategic security and energy partnership with the US, Iran is repeatedly on the brink of war with Washington and its ally Israel.
Apart from wanting to play a bigger role on the global stage, the five founding members of BRICS have never really been like-minded. While Russia and China have increasingly positioned themselves as antipoles to the US, India has gradually drawn closer to the US to counter a more aggressive China. Although they occasionally toy with the anti-American option, South Africa and Brazil continue to foster close ties with the US in both economic and political terms. It is no coincidence that India, Brazil and South Africa are democracies, while Russia and China are autocracies – and ones that get along very well with the authoritarian rulers of Iran and Saudi Arabia.
In addition to having diverging political and economic interests, the BRICS Plus countries also differ strongly in terms of their respective economic and demographic weight. Collectively, the five BRICS countries account for around 41 per cent of the world’s population, approximately 32 per cent of global economic output (adjusted for purchasing power), and roughly 20 per cent of all goods exported worldwide. If we add the five countries that make up the “Plus” part, the combined bloc only accounts for slightly more – around 45 per cent of the world’s population, 36 per cent of global GDP, and 25 per cent of global goods exports. Thus, the expansion is likely to fundamentally alter the character of the previously exclusive club of leading regional economies. It will be replaced by a curious mixture of very large, large, medium-sized and small countries, some of which are pursuing very different interests. What’s more, the BRICS Plus group is already clearly dominated by China, which accounts for almost two-thirds of the bloc’s economic output and 39 per cent of its population. As understandable as Beijing’s claim to leadership may be against this backdrop, these imbalances are problematic for ensuring joint action on an equal footing. The balance between the interests of the junior partners and dominant China is therefore likely to remain delicate. And it is unlikely that forming an internationally relevant bloc capable of cohesive action out of such a heterogeneous group of countries will represent a genuine success for Beijing.
BRICS Plus as a potential raw-materials superpower
As the figure above shows, even if their political interests were more aligned, the combined economic weight of the BRICS Plus countries would not be enough – at least in the short to medium term – to turn the US-dominated world order on its head. However, there is one exception, as the BRICS Plus countries would collectively be in a dominant position when it comes to raw material deposits. With the inclusion of Saudi Arabia, Iran and the UAE, the bloc would account for 43 per cent of global oil production and a very large share of global oil reserves. Almost 40 per cent of the rare earth deposits required to manufacture batteries for electric vehicles, power storage systems and microelectronics are in the hands of China, which also has a near monopoly on their processing. Thus, when it comes to the supply of raw materials, the BRICS Plus bloc could potentially put the West under considerable pressure – in a scenario with echoes of the OPEC oil embargo of 1973.
G7 and US dollar still dominant
From an overall economic perspective, however, a reorganisation of the world and an end to the US dollar as the reserve currency is a pipe dream of Beijing, Moscow and Tehran, which will not come true in the foreseeable future. As the most important industrialised countries of the West, the G7 nations still jointly account for around 30 per cent of global GDP, just under 10 per cent of the world’s population, and roughly 27 per cent of all exported goods. As still the largest economy and the only military superpower, the US continues to dominate not only the G7 but also the world. Around 62 per cent of global currency reserves are invested in US dollars, compared to just 2 per cent in Chinese yuan. The BRICS group’s track record to date also speaks against a rapid end to the Pax Americana. The bloc’s greatest success so far has been founding the New Development Bank in 2014, which is modelled on the World Bank. To date, the bank has issued loans with a total value of just over 30 billion US dollars. Tellingly, most of the loans have been granted in US dollars.
From China’s point of view, however, the meagre balance sheet of the previous BRICS format and the uncertain prospects for BRICS Plus are acceptable. The old BRICS format did not really advance the interests of the rulers in Beijing. So, their thinking goes, why not try a new start that could at least irritate the US and its partners while possibly strengthening some bilateral relations, especially in the Middle East, where China is keen to gain more influence? At the same time, the BRICS Plus initiative allows some smaller powers to position themselves as players in the geopolitical competition of the incipient Cold War 2.0 between China and the US so that they can avoid becoming mere pawns or a theatre of war in this conflict.
Author:
Mario Holzner is Director of the Vienna Institute for International Economic Studies (wiiw) and was a Fellow of the European Commission’s Directorate-General for Internal Market, Industry, Entrepreneurship and SMEs (DG GROW) in 2023.
The interactive graphics were created by Alireza Sabouniha. He is research assistant at wiiw and recently completed his master’s degree in Economics at the WU (Vienna University of Economics and Business).
The value added generated by export activities in Austria amounts to around 30% of GDP. On average, slightly more than two thirds of firms in the manufacturing industry are internationally active. These export activities are designed for the long term. Larger companies are significantly more active internationally and contribute the largest share of exports. Exporting companies are larger on average, generate more surpluses and invest more compared to companies that do not export. They also pay higher wages, but rather than being driven by the export activities as such, they result from the higher firm-level productivity. Finally, there is a close and reciprocal link between exports, R&D activities and productivity.
Austria’s prosperity depends to a large extent on exports, which account for more than half of the country’s economic output. If the imports necessary for the production of exports are deducted, around a third of domestic value added still comes from exports (see Figure 1).
Despite the export industry’s great importance to Austria, little was previously known about the characteristics of exporting companies. How large is the proportion of Austrian companies that export? Are they primarily large or small companies? Are exporters more productive and more successful?
Access to microdata via Statistics Austria’s Austria Micro Data Center (AMDC) makes it possible to provide detailed answers to these questions for the first time (Stehrer et al. 2022; Stehrer, 2023).
How many companies export? And how much?
Not all companies export. On average, in the 2013-2020 period, the share of Austrian manufacturing companies active in foreign trade was around 70%. Just over 55% were both exporters and importers. Around 6% were pure exporters, and just under 10% were only internationally active as pure importers. The remaining 28% were neither exporters nor importers (see Figure 2). [1]
The export activities of Austrian companies are designed for the long term. Around 90-95% of exporting companies in a given year also export in the following year, and only 1-2% of all companies cease their export activities each year. A further 5% of companies in any given year leave the market due to insolvency or closure.
Conversely, only a few non-exporting companies (around 5% per year) start exporting. As a result, the proportion of exporters among all companies is slowly but steadily increasing (see Figure 2). While 33% of companies were still not internationally active in 2013, this proportion had fallen to around 26% by 2020. Even the economic crisis and the disruption to supply chains triggered by COVID-19 were unable to halt this trend.
Non-exporters also have a higher probability (roughly 5-10%) of exiting the market. On average, around 5% of companies (as a percentage of existing companies) enter the market each year. Of these, the proportion of companies that export immediately accounts for around two thirds of all market entrants.
Smaller companies export significantly less often than large companies. While exporters are in the minority among companies with fewer than 10 employees, around half of companies with 10 to 49 employees export. In addition, more than 80% of companies with more than 49 employees are exporters, and it is very rare for large companies (meaning those with 250 or more employees) to not be exporters (see Figure 3).
Although Germany is the most important export market for Austrian companies, this does not mean that Austrian exporters limit themselves to this market. The proportion of ‘marginal exporters’ (i.e. companies that only export to one country) is only 15% of exporting companies. If marginal exporters are defined somewhat more strictly as companies that only export one product to a specific country, their share drops to only around 7%. The shares of marginal importers are only half as high according to these two definitions, at 7% and 3.5%, respectively. Unsurprisingly, these shares are significantly higher among smaller companies.
Overall, a small number of companies account for a large proportion of export sales. Around two thirds of exports are accounted for by 5% of exporting companies, 75% by around 10% of exporting companies, and 90% by a quarter of exporting companies. The situation is similar for imports, as only 25% of importing companies are responsible for 90% of all imports. If a distinction is made according to the different sizes (i.e. employee numbers) of companies, this concentration is somewhat lower, but still very pronounced.
From an economic policy perspective, this concentration is a clear sign of the success of some Austrian companies on international markets. However, it also means that there is a group of companies in the Austrian economy that may be significantly more susceptible to international demand shocks or disruptions to international supply networks.
The strengths of exporting companies
Exporting companies are larger, generate more surpluses, and invest more compared to companies that do not export. In absolute terms, this ‘export premium’ is a factor of around two to three. Per hour worked, turnover, wages and operating surpluses are a factor of 1.2 to 1.6 higher for exporters. However, taking into account both the size and productivity of the exporting companies and the socioeconomic characteristics (e.g. education, age and gender) of their employees, it is clear that export activity only has a very small positive effect on employees’ wages and salaries, which means that the productivity and performance of the companies are more important factors.
These correlations are also evident in relation to their import activity. Companies belonging to an international group of companies are also very often larger and more productive than companies that are only domestically active. This pattern is consistent with both the empirical results for other countries and the current theoretical literature on the performance of heterogeneous companies. Companies that only export to one country or only export one product (i.e. are ‘marginal exporters’) also tend to be larger and more productive than companies without export activities, albeit to a lesser extent than companies with a diversified export portfolio.
One explanation for the positive export premium is the reciprocal, close link between exports and productivity, as exporters are more productive than non-exporters, and higher productivity in the past goes hand in hand with significantly higher export intensity. Exporters also conduct R&D more frequently and invest in digitalization more often than non-exporters. In fact, there are hardly any companies active in R&D that do not export, and the more they invest in R&D, the higher the export share of turnover. In addition, the causality between exports and R&D runs in both directions. In other words, exports create incentives to develop new products, just as R&D creates the basis for products that can be marketed internationally.
Conclusion
Exports are of crucial importance to Austria’s prosperity. New data shows that export activities are very widespread in Austrian manufacturing, as half of companies with 10 or more employees export. However, only 5% of exporting companies account for two thirds of export sales.
Exporting companies are larger and economically more successful; sales, wages and operating surpluses per hour worked are significantly higher for exporters than for companies that do not export. The decisive factor here is the higher productivity of exporting companies: the more productive a company is, the better it can hold its own on export markets. Conversely, international competition forces exporting companies to continuously boost their productivity.
In terms of economic policy, this means that measures to promote the productivity of companies lead to better export performance and, conversely, that measures to promote export activities may lead to better company performance. In particular, the close relationship between R&D and exports is very important in terms of economic policy, as it shows a way to increase export intensity by promoting R&D and innovation.
If, as in the past, it is possible to increase the number of companies conducting R&D in Austria, the proportion of exporters will also continue to rise. The same applies to the correlation between productivity and exports: measures that increase productivity, such as research funding, should also increase the export activities of Austrian companies in the long term. In the best-case scenario, exports and productivity will reinforce each other over time.
[1] These figures relate to the primary survey of the structural business statistics (SBS).
Authors:
Dr. Bernhard Dachs and Univ.-Doz. Dr. Robert Stehrer (wiiw)
Bernhard Dachs is Senior Scientist at the Innovation Systems Department of AIT Austrian Institute of Technology, Vienna. He graduated in Economics from the University of Business Administration and Economics, Vienna, and holds a doctorate in Economics from the University of Bremen. Over the past years, his research focus has been the economics of innovation and technological change, in particular the internationalisation of R&D, innovation in services, and the analysis of national and international technology policy. His work has been mostly empirical and applied. Papers based on this research has been published a number of international peer-reviewed journals.
Robert Stehrer is Scientific Director at wiiw. His expertise covers a broad area of economic research, ranging from issues of international integration, trade and technological development to labour markets and applied econometrics. His most recent work focuses on the analysis and effects of the internationalisation of production and value-added trade. Other contributions relate to the connection between digitalisation, demographics, productivity and labour markets. He studied economics at the Johannes Kepler University Linz, Austria, and sociology at the Institute for Advanced Studies (IHS) in Vienna and is lecturer of economics at the University of Vienna.
The interactive graphics were created by Alireza Sabouniha. He is research assistant at wiiw and recently completed his master’s degree in Economics at the WU (Vienna University of Economics and Business).