Blog|  Piero Cipollone, Member of the Executive Board of the ECB
As payments and financial markets go digital, central bank money must evolve too. Through initiatives such as Pontes and Appia, the Eurosystem is working with market participants to ensure that tokenised finance can settle safely in central bank money, supporting innovation, integration and Europe’s financial sovereignty.
Technology is transforming how we communicate, travel, work and pay. The way that central banks issue money also needs to change, to meet the evolving needs of the societies we serve.
Issuing money is at the very core of what central banks do. Yet most of the money we use in our day-to-day transactions is created by the private sector – for example, when a bank finances a mortgage. Ultimately, people accept this private form of money as payment because they have the option to convert it, on a one-to-one basis, into central bank money – the safest of assets and the reference point that anchors the entire system. This interplay helps build and maintain trust.
Central bank money comes in two forms. For our everyday payment needs we have cash. And as our lives increasingly move online, the Eurosystem is developing the digital euro – a digital form of cash to complement banknotes and coins.
Meanwhile, in wholesale financial markets, central bank money takes the form of the deposits banks hold at their central bank, recorded as entries on its books. Banks can use these deposits for large-volume transactions and to settle payments among themselves. This central bank money provides the bedrock of today’s wholesale financial market infrastructures.
But wholesale financial markets are not immune to change. Thanks to tokenisation and distributed ledger technologies (DLTs), it will be possible to represent financial assets such as bonds as digital tokens – or, put simply, files – that can be transferred and updated more efficiently than is currently the case. These new technologies hold the promise of greater innovation, efficiency and integration across financial markets.
With tokenised assets and DLTs, transactions will be settled faster and more efficiently, lowering processing costs and risks. The entire lifecycle of an asset – from trading to settlement to custody – will run on the same platform, available 24/7. Cross‑border activity will become simpler and cheaper, with lower costs across the board. Smart contracts will enable further innovative solutions. More efficient and integrated financial markets will also mean cheaper funding for the real economy.
To reap the benefits of these technologies, investors will need a safe asset to settle transactions – central bank money. And this is exactly what we are working towards.
Thanks to the Eurosystem’s Pontes initiative, we will already be able to offer a way to settle DLT‑based wholesale transactions in central bank money in the third quarter of 2026. We will do so initially by connecting our financial backbone – the TARGET Services – to these new DLT platforms. This will provide the safety and institutional credibility that is needed if tokenised finance is to flourish in Europe. And this is just the beginning.
To fully realise the potential of tokenisation and DLTs, investors will need central bank money to be more directly integrated on these platforms. With this goal in mind, this week we published the roadmap for our Appia initiative.
The aim of Appia is to design – together with market participants – the next generation of Europe’s financial infrastructure. This process will guide our own gradual, continuous enhancements of Pontes to ensure that it evolves in line with Appia. But it will also steer the market towards building its own solutions and infrastructures in a way that ensures competition, integration and innovation for European financial markets.
Underpinning all this will be safe, tokenised euro central bank money, giving the market the settlement anchor it needs to grow safely. Market participants have been clear that this is essential. Appia will be developed through a broad public‑private partnership, and the final design will reflect extensive collaboration through experiments, proofs of concept and common standards.
There is one more dimension to consider. In today’s world, financial infrastructure can have geopolitical implications. If Europe does not build its own digital roads, it risks having to rely exclusively on those built by others. To avoid sleepwalking into such a situation, we must not succumb to complacency or fall behind. Europe has both the technology and the means to avoid this dependency.
With Appia, an integrated European ecosystem will replace today’s fragmented infrastructures. It will support efforts to develop a savings and investments union, while ensuring that the euro remains the trusted anchor of Europe’s digital economy.
Change is inevitable – but how we respond to it is up to us. Through Appia, Europe is choosing to shape its own digital financial space.
 
 
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Secure transparency, remuneration and the possibility for rightsholders to prevent the use of their protected content in AI training

Protect the news media sector to ensure media pluralism and diversity of information

Introduce new licensing rules to address potential infringements of copyright law

To protect the creative sector in the EU, the use of copyrighted work by artificial intelligence requires transparency and fair remuneration, Parliament says.

On Tuesday, MEPs adopted a series of recommendations to protect copyrighted creative work from use by artificial intelligence (AI), by 460 votes to 71, and with 88 abstentions. They believe that EU copyright law should apply to all systems of generative artificial intelligence (genAI) on the EU market, regardless of the place of training.
Remuneration and transparency
MEPs insist that use of copyrighted material by genAI must be fairly remunerated in order to protect the EU’s creative sector, which generates 6.9% of the EU’s gross domestic product. They also want the Commission to examine how remuneration for past use can be ensured, but not through a global licence for providers to train their genAI systems in exchange for a flat-rate payment.
MEPs also stress the importance of full transparency for the use of protected content by genAI. They want AI providers and deployers to provide an itemised list of all copyrighted works used to train AI and detailed records of crawling activities for inference and retrieval-augmented generation. Lack of these could be perceived as copyright infringement, triggering legal consequences for AI providers and deployers. If such a court case is then decided in favour of the rightsholder, AI providers or deployers will have to bear all legal costs and related expenses.
Licensing market and opt-out from training
MEPs want the Commission to create a new licensing market for copyrighted material, including voluntary collective licensing agreements per sector, which would include individual creators and small and medium-sized enterprises. They want to make sure rightsholders can exclude their work from being used in AI training and they suggest that the European Union Intellectual Property Office (EUIPO) could manage such an opt-out list.
Protection for news media sector
MEPs urge the Commission to protect the press and news media sector whose work is regularly exploited by AI systems. News media outlets whose traffic and revenues are diverted by AI systems should be fully compensated and they should also have the right to refuse use of their content for training AI systems. MEPs insist that the aggregation of news content must ensure media pluralism and diversity of information, avoiding the selective processing of information or self-preferencing practices by gatekeepers benefiting their AI services.
Content created by AI and individual protection
Content fully generated by AI should not be protected by copyright, MEPs say. They also want to make sure individuals are protected from dissemination of manipulated and AI-generated content and stress the obligation of digital service providers to act against such illegal use.
Quote
Rapporteur Axel Voss (EPP, DE) said after vote: “We need clear rules for the use of copyright-protected content for AI training. Legal certainty would let AI developers know which content can be used and how licences can be obtained. On the other hand, rightsholders would be protected against unauthorised use of their content and receive remuneration. If we want to promote and develop AI in Europe while also protecting our creators, then these provisions are absolutely indispensable.”

 
 
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Blog | AI can lift global growth but lasting productivity benefits depend on how fast we learn to measure, finance, and govern it.

Artificial intelligence is the defining driver of global economic conversation—and, increasingly, of economic growth itself. In the United States, AI-related investment now accounts for a large share of GDP growth, fueling new demand for servers, data centers, software, and power infrastructure. Policymakers are scrambling to understand what this means: Is the world witnessing a short-lived investment bubble or a lasting productivity boom comparable to the IT revolution of the 1990s?
The US economy, the world’s largest and still at the center of the global business cycle, has entered a two-speed expansion. AI-intensive sectors are racing ahead, while construction, manufacturing, and industries that are sensitive to interest rates are falling behind. According to the Bureau of Economic Analysis, investment in information-processing equipment and software grew by 16.5 percent from a year earlier in the third quarter of 2025. Stripped of AI, GDP would have been markedly weaker.
This pattern has global echoes. Growth in Europe and Japan has stabilized but remains dependent on loose monetary policy. Emerging markets have benefited from lower yields and a weaker dollar, but their growth impulses increasingly depend on technology-related investment and capital inflows. Global growth has not collapsed—but it’s increasingly concentrated in narrow sectors and regions.
What makes the current AI wave unusual is its capital intensity. Training large language models and deploying generative systems require vast computing power and physical infrastructure. AI is more like electricity—an enabling technology that requires continuous investment in grids, hardware, and complementary assets—than other recent innovations such as social media or digital commerce, which grew on preexisting networks. To match global demand, data centers worldwide may require $6.7 trillion in capital expenditure by 2030, estimates suggest.
Measuring immeasurables
This investment boom is transforming the structure of the economy—but also revealing how poorly our measurement systems capture intangible capital. National accounts were designed for an industrial age when factories and machinery dominated. Today, value increasingly resides in data, algorithms, proprietary models, and cloud infrastructure.
Official statistics record part of this shift—software and R&D, for example—but miss much of what drives productivity. The costs of training large models, refining datasets, and creating new applications are often expensed rather than capitalized. Even semiconductors, central to the AI ecosystem, are treated as intermediate goods rather than as carriers of embedded intellectual property.
As a result, GDP data simultaneously overstate the immediate contribution of AI (by counting massive capital outlays) and understate its broader economic impact (by missing the productivity spillovers). This is the same statistical paradox that masked the early productivity gains of the IT revolution. When measurement lags reality, policymakers risk misreading the economy—tightening too much because apparent slack seems small or easing too soon because inflation looks demand-driven, when it may reflect structural change.
The Federal Reserve, for example, now faces a more complex policy landscape. If AI adoption quietly raises potential output, the economy may be running less hot than headline data imply. Conversely, the surge in electricity demand and infrastructure bottlenecks could set a new floor for inflation. Misjudging either side could mean policy errors in both directions.

New geographies
AI’s rise is also redrawing trade and capital-flow patterns. Imports and exports of computers, servers, and semiconductors have surged, signaling a global reallocation of supply chains. Manufacturing and assembly are shifting toward Southeast Asia, India, and specialized US hubs such as Texas and the Gulf Coast.
This re-regionalization is not de-globalization; it’s a new geography of interdependence. The US and China remain dominant players, with Europe seeking to catch up through industrial policy and investment incentives. For many emerging markets, AI demand is already translating into exports and foreign direct investment—particularly in energy and component manufacturing—but also into vulnerability to technological and geopolitical shocks.
Capital flows increasingly follow the map of AI infrastructure. Equity markets have rewarded hyperscalers—the handful of firms building and financing the global computing backbone—with valuations and cash flows unseen since the dot-com era. As a result, a small group of tech giants now accounts for a disproportionate share of global AI-related capital expenditure and productivity expectations.
Research by the Institute of International Finance reveals a distinction between digital participation (the use of imported digital tools) and digital depth (the ability to produce and export digital goods and services and embed them in domestic value chains). Emerging markets with digital depth—China, India, Korea, and a smaller group of specialized hubs—are attracting more stable foreign direct investment linked to AI-era production. Their export profiles show rising shares of information and communications technology services, royalties, and digital content. Others remain primarily consumers of imported technologies and therefore rely more heavily on volatile portfolio flows driven by global liquidity cycles.
As AI becomes central to economic activity, digital depth may play a role in capital flow dynamics comparable to fiscal credibility or exchange-rate regimes—an underappreciated channel that global policymakers will need to monitor closely.
The scale of computing power required for AI training and inference has made electricity generation and grid capacity critical macroeconomic variables.
The macroeconomic implications are profound. Energy bottlenecks could delay AI diffusion, anchor a higher level of core inflation, and generate localized overheating even as other sectors remain weak. Grid investment is becoming a central supply-side constraint, blurring the line between industrial and macroeconomic policy.
Diffusion or concentration?
The deeper question is whether the AI boom will translate into broad-based productivity growth or remain confined to a narrow set of businesses and industries. History suggests that the payoff from general purpose technologies comes only after years of complementary investment—in skills, management practices, and institutional adaptation. Electricity and IT took decades to diffuse widely enough to raise aggregate productivity.
If AI adoption remains concentrated among hyperscalers and specialized service providers, the returns may plateau quickly, leaving the economy vulnerable once the investment cycle peaks. But if AI applications spread across industries, the potential for a sustained lift in potential output becomes real. Corporate surveys suggest diffusion is underway but uneven. While many firms are experimenting with AI, only a smaller group is implementing it at scale.
The risk is that diffusion will collide with inadequate infrastructure and outdated statistics. The mismatch between rapid technological change and slow policy adaptation could make the next few years unusually volatile. Growth could oscillate between bursts of investment and pauses for adjustment while policymakers struggle to interpret what the numbers mean.
Behind the numbers
The AI boom is unfolding against a backdrop of global uncertainty. Tariff wars, immigration restrictions, and fiscal imbalances have left the world economy more fragmented and less predictable. In this environment, AI stands out not just as a technological story but as a macroeconomic stabilizer—one of the few genuine sources of incremental demand and optimism.
Yet this narrow engine cannot carry the entire global economy indefinitely. The US expansion remains capital-heavy and employment-light. Europe risks missing out unless it retools its industrial and digital policy. Emerging markets must balance opportunity with prudence, ensuring that cheap energy or favorable regulation does not substitute for long-term competitiveness.
Policymakers and statisticians must move faster. Measurement frameworks must evolve to capture intangible capital; fiscal and monetary tools must account for sectoral divergence and new supply constraints; and international cooperation must ensure that the benefits of AI diffusion are not confined to a few economies.

 
 
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Yesterday in Toronto, Commissioner for Trade and Economic Security, Maroš Šefčovič, and Canada’s Minister for International Trade Maninder Sidhu launched negotiations for an EU-Canada Digital Trade Agreement (DTA). Building on nine years of successful implementation of the EU-Canada Comprehensive Economic and Trade Agreement (CETA), this new deal will upgrade EU-Canada trade by making it easier and safer for businesses to trade digitally across borders and providing stronger protections for consumers online.
The launch of DTA negotiations reflects the mutual commitment to secure, open and rules-based trade, and to strengthening and diversifying trade with like-minded partners. Through this agreement, the EU and Canada aim to play a leading role in shaping high-standard international rules for digital trade.
Focus on trust and predictability
The agreement is expected to set clear, predictable rules for businesses and consumers engaged in digital trade, while ensuring that both the EU and Canada retain the right to develop and implement policies addressing new digital economy challenges. More specifically, the DTA will aim to:

Create a safe online environment with binding, high-standard consumer protections for personal data and privacy, and protect against unsolicited commercial messages. This will boost consumer confidence and assurance in digital transactions.
Enhance legal certainty for businesses by promoting paperless trade; ensure the validity of electronic signatures, contracts and invoices; and prohibit customs duties on electronic transmissions for more efficient and predictable digital transactions.
Promote fair digital trade by prohibiting unjustified data localisation requirements and forced transfers of software source code, thereby protecting businesses from protectionist practices and fostering confidence in digital markets.

Background
Discussions at the EU-Canada Summit in June 2025 prepared the ground for the launch of the DTA negotiations, with both partners reaffirming their commitment to reinforcing their economic partnership and diversifying markets. A successful scoping exercise took place in September 2025, with preliminary discussions starting in February 2026.
CETA provides a framework for trade in goods and services, as well as for cross-border investment and public procurement. Since it entered into force nine years ago, trade in goods has jumped 76 percent – to over €81 billion. Trade in services has surged 97 percent – to nearly €51 billion. The DTA will complement CETA by addressing emerging needs in the digital economy.
The DTA will also build on the EU-Canada Digital Partnership, signed in December 2023. While the Digital Partnership sets a non-binding framework for regulatory and research cooperation, the DTA will provide binding commitments that businesses and consumers can rely on.
Digital trade is growing in size and importance, with over 60% of global GDP linked to digital transactions. The EU is the world’s leading exporter and importer of digitally deliverable services. As of 2023, 54 % of the EU’s service trade was conducted digitally, amounting to €670 billion in imports and €661 billion in exports from outside the EU. This includes, for example, telecommunication services, computer and information services, and other services that are typically delivered digitally (financial services, insurance and pension services, etc).
 
 
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Global debt markets remained resilient in 2025 amidst geopolitical tensions, trade disputes and risks for growth prospects, with governments and companies borrowing a record USD 27 trillion, according to a new OECD report.
Sovereign bond issuance in OECD countries is projected to reach a record USD 18 trillion in 2026, up from USD 12 trillion in 2022. Outstanding debt is estimated to have risen from USD 55 trillion in 2024 to USD 61 trillion in 2025. Debt relative to GDP remained stable, at 83% in the OECD countries, but is projected to rise to 85% in 2026.
In emerging markets and developing economies, sovereign borrowing from debt markets hit USD 4 trillion in 2025, bringing the total debt stock to USD 14 trillion, or 30% of GDP, the highest level since 2007.
Corporate borrowing from markets reached its highest level ever in real terms in 2025, with total debt raised across corporate bond and syndicated loan markets hitting USD 13.7 trillion, surpassing the 2021 peak of USD 13.5 trillion. Outstanding debt reached USD 59.5 trillion at year-end 2025, of which USD 36.4 trillion in bonds and USD 23.1 trillion in syndicated loans. Given the scale of capital expenditure required to finance the expansion of AI technology, corporate borrowing needs are expected to increase substantially going forward.
Borrowing costs remain a concern – sovereign real yields are elevated, especially at longer maturities, and higher interest rates are beginning to flow through to the corporate debt stock. Sovereign borrowers have responded by shifting their issuance towards shorter maturities, in an effort to mitigate interest expenditures. The share of issuance in 2025 with a maturity over 10 years reached its lowest point since 2009 for sovereign borrowers, and the lowest on record for corporates.
Corporates, whose borrowing predominantly carries fixed-rate interest structures, have not seen their interest expenditure increase as much as sovereigns, but the shift towards higher interest spending is also clearly visible. Securities with an interest rate above 4% made up half of outstanding investment grade bonds at the end of 2025, while 15% of outstanding non-investment grade bonds cost 8% or more, up from 10% of outstanding bonds in 2021. As near-term refinancing needs disproportionately consist of low-cost debt, this trend is expected to continue.
Central banks remain the largest domestic holders of government debt in many OECD countries, but, as they have reduced their balance sheets, the market is increasingly dependent on price-sensitive investors, such as hedge funds, households and certain institutional investors. This transition in the sovereign debt market – from price-insensitive demand of central banks to price-sensitive demand from other investors – has the potential to increase market volatility and can be expected to reverberate in the corporate market as well.
This year’s report assesses how technology companies are set to become ever-larger issuers in debt markets as they shift their funding model from internally generated cash to external funding to finance the capital-intensive AI expansion, notably data centres. In 2025, nine major players commonly known as “hyperscalers” raised an aggregate of USD 122 billion from bond markets, accounting for nearly half of all technology firm issuance globally.
The report suggests that the AI transformation is set to become a major financing event in global markets for years to come, possibly setting debt markets on a course towards greater concentration, similar to developments in equity markets in recent years. The nine hyperscaler firms alone have projected cumulative capital expenditure of USD 4.1 trillion from 2026 to 2030, about 35% more than total capital expenditure by all US non-financial companies in 2025. If half of these investments were financed by bond markets, these nine firms would represent 15% of global historical average issuance by non-financial issuers annually.
Go here for further information on the report with key findings and charts.
 
 
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Blog | Artificial intelligence is everywhere, and the workplace is no exception. But will it empower workers, or is it set to replace them? This blog post looks at the impact of AI use and investment on firms’ current and future hiring and firing decisions.
Artificial intelligence (AI) has the potential to significantly influence firms’ production processes. It could also profoundly reshape employment and the labour market. But how exactly? On the one hand, AI could replace workers, leading to a decline in employment. On the other hand, it could boost corporate profits and create entirely new types of jobs, complementing the new technology. Meanwhile, reports from the other side of the Atlantic point to thousands of job cuts at companies like Amazon and Target, citing AI as a contributing factor. Have firms already started to replace humans with AI? This blog post examines hiring patterns at European firms, comparing companies that use and invest in AI with companies that don’t. To do so, we draw on the results of the ECB’s survey on the access to finance of enterprises (SAFE) for the second and fourth quarters of 2025.
Widespread use, limited investment
While most firms use AI, few actually invest in it. Two-thirds of the 5,000 firms that took part in the survey reported that their employees use AI, with significant disparities across firm size (Chart 1). Almost 90% of businesses with 250 or more employees use AI, compared with 60% of those with fewer than ten employees. By contrast, a mere quarter of Europe’s companies invest in AI technology. This points to a crucial insight: firms do not necessarily need to invest in AI in order to use AI technology. Thanks to accessible online tools, the entry barrier for using AI is low, enabling broad adoption even among smaller firms.

Chart 1
AI use and investment by firm size

(percentage of firms; by firm size (number of employees))

Source: SAFE.
Notes: Firms that did not respond were excluded. Observations for AI investment: second quarter of 2025. Observations for AI use: fourth quarter of 2025.

Are firms already replacing their workers?
We compare firms that use AI with those that don’t. We factor in a range of variables generally understood to drive employment growth. These include: firm size and age, current change in investment, turnover, profitability, the economic outlook of the firm, expected change in investment, sector and country.[1] Overall, in terms of job creation and destruction, we find no significant difference between businesses that report using AI and those that don’t (Chart 2). However, the picture changes when we separate firms that frequently use AI from those that rarely use it. Companies that make significant use of AI are about 4% more likely to take on additional staff. In other words, AI-intensive firms tend, on average, to hire rather than fire. Much the same can be said of investment in AI: firms that invest in AI are nearly 2% more likely to hire additional staff than those that don’t.
This suggests that investment in AI often entails a higher level of AI use, as well as a need to take on new workers to operationalise and support the technology. The effect is driven by small firms, while AI is neutral for large firms’ employment.[2] Some firms may see investment as a way of scaling up their output. This hypothesis would appear to be borne out when we look at why firms use AI. The overall growth in employment is driven by firms that use AI to promote research and development (R&D) and innovation – key determinants of business growth. Although it is not possible to ascertain the type of workers hired from the survey alone, many are likely to be highly skilled employees able to use and develop AI technology, since firms are looking to use AI for R&D. Conversely, firms using AI to cut their labour costs experience negative effects on hiring and positive effects on layoffs. However, only 15% of firms that use AI cite reducing labour costs as a factor, and this is insufficient to offset the overall positive effects observed to date.

Chart 2
Impact of AI use and investment on current hiring and firing

(percentage marginal probability of an increase in the workforce)

Source: SAFE.
Notes: Chart 2 shows the marginal effect of the b coefficient from an ordered probit of the outcome “increase” in employment (see footnote 1 for more details on the regression). Columns 4 and 5 are the coefficients of dummies taking the value 1 if the firm declared the reason for using AI. Cross-sectional dataset of around 5,300 euro area firms. Observations for current AI investment: second quarter of 2025. Observations for current AI use: fourth quarter of 2025.

Hiring expectations: does AI matter?
So far, we have looked at firms’ current hiring and firing decisions. But what if we ask firms that are currently using or investing in AI about their plans one year from now? In short, we see no marked difference in overall hiring intentions (Chart 3). But when we look specifically at future AI investment, it’s a different story. Firms planning to invest in AI are more likely to have positive expectations for future employment growth, even when their overall investment expectations (in addition to investment in AI) are accounted for. This is true regardless of the level of planned AI investment and suggests that a pause in hiring due to investment in AI technology is also unlikely over the next year. However, these findings could change over a different time horizon. Indeed, a survey from the ifo Institute finds that many German companies expect AI to lead to some job cuts, albeit over a longer horizon of five years.

Chart 3
Impact of AI use and investment on hiring and firing expectations

(percentage marginal probability of an increase in the workforce one year ahead)

Source: SAFE.
Notes: Chart 3 shows the marginal effect of the b coefficient from an ordered probit of the outcome “increase” in employment expectations. The control variables are the same as in Chart 2, with planned AI investment included in addition to AI usage. Expectations refer to the next year. Cross-sectional dataset of around 5,300 euro area firms. Observations for current AI investment: second quarter of 2025. Observations for AI use and future AI investment: fourth quarter of 2025.

Conclusions
As things stand, based on firms’ overall hiring plans, investment in and the intensive use of AI are not yet replacing jobs. In fact, some firms are hiring additional employees – perhaps because they are looking to develop and implement AI technologies while maintaining their existing production processes, or because AI is a way to help them scale up more quickly. Looking one year ahead, the firms that plan to invest in AI are still planning to take on more people than firms that have no such plans. On balance, these findings hold. While some firms may use AI to replace workers, the average firm is more likely to take on additional staff to enable it to use and invest in AI.
So how can we square our findings with some of the gloomier studies? The literature on AI and employment yields mixed results, owing to variations in the time horizons over which the effects are likely to be felt, the geographical areas covered and the research topics explored. Notably, it is difficult to compare studies on Europe (the focus of this blog post) with those on the United States, since the scale of investment in AI, the extent and timing of AI adoption all differ significantly. Our results are in line with the findings of most of the existing studies in the small body of European research focusing on the current and near-term effects.[3]
Overall, the survey data explored in this blog post suggest that the effects of AI on employment are currently still positive. This is certainly the case as AI has not yet significantly transformed production processes. Given that this is set to change, the longer-term impact of AI on employment remains less clear.
The views expressed in each blog entry are those of the author(s) and do not necessarily represent the views of the European Central Bank and the Eurosystem.
 
 
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What is the Industrial Accelerator Act and why is the Commission proposing it?
The Industrial Accelerator Act (IAA) is a legislative proposal designed to strengthen Europe’s industrial base by boosting manufacturing, growing businesses, and creating jobs in the EU. It delivers on the recommendations of the Draghi report on EU competitiveness, the political guidelines of the Commission, and the mission entrusted to the Executive Vice-President for Prosperity and Industrial Strategy.
The IAA mobilises public procurement and public incentives to boost demand for low-carbon and European-made products and net-zero technologies, speeds up investment through faster and simpler permitting, and introduces targeted conditions to ensure major foreign direct investments generate added value for the EU. In so doing, it will create lead markets for clean and strategically important industrial products. In 2024, manufacturing represented 14.3% of EU GDP. The objective is to increase the manufacturing’s share of EU GDP to 20% by 2035 and reinforce Europe’s resilience, competitiveness, and economic security.
The Act complements the Automotive Package adopted on 16 December 2025, defining the ‘Made in EU’ conditions to benefit from the flexibilities under the CO2 standards for cars and vans and the super-credit for small affordable electric cars, as well as the conditions to benefit from financial support for greening corporate fleets.
What are the expected benefits?
The IAA is expected to create substantial value added and high-quality jobs for the EU. Low-carbon demand measures alone could generate more than €600 million of additional value in the steel, aluminium, and cement industries by 2030, and up to €10.5 billion across the automotive value chain. It will also create tens of thousands of jobs, including 85,000 in battery projects and 58,000 in solar manufacturing, while safeguarding existing jobs in steel, aluminium and cement as these sectors transition to cleaner production. The foreign investments conditionalities will also create local employment opportunities, as well as boost overall EU manufacturing capacity.
Digitalised permitting will lead to administrative savings of up to €240 million for all manufacturing industries in the EU.
In total, the Act is expected to save 30.58 million tonnes of carbon dioxide in the energy intensive industries (steel, cement and aluminium), batteries, and vehicle components. Streamlining permitting procedures will accelerate the implementation of decarbonisation projects, therefore leading to an accelerated pace of GHG savings of a sector that represents 22.5% of total EU GHG emissions.
To what sectors does the Industrial Accelerator Act apply?
The IAA covers the manufacturing industry, with a focus on energy intensive industries, the automotive value chain, and net-zero technologies needed to enable the clean industrial transformation and ensure supply-chain resilience. For instance, low-carbon requirements are introduced for the steel used in automotive and construction, while ‘Made in EU’ and low-carbon requirements apply to the cement used in construction and the aluminium used in automotive and construction, when subject to public procurement and other forms of public intervention. For net-zero technologies, the Act introduces ‘Made in EU’ requirements for batteries, battery energy storage systems (BESS), solar PV, heat pumps, wind, electrolysers, and nuclear technologies, when subject to certain public procurement procedures, auctions, and support schemes. It also introduces ‘Made in EU’ provisions for electric vehicles (EVs) and their components.
Why has the Commission chosen these sectors?
The IAA focuses on sectors that are strategically important for the EU economy, and which currently face strong competitive and structural pressures: energy-intensive industries (steel, cement, aluminium, chemicals), net-zero technologies, and automotive components manufacturing. These sectors are essential enablers of the clean transition and vital to downstream industries such as construction, mobility, energy systems, and defence. At the same time, they face declining production in Europe, slower decarbonisation investments and growing global competition and market distortions, such as unfair subsidies, in markets that are increasingly concentrated outside the EU. The value chain of each sector/technology was subject to an in-depth analysis to determine where the EU faced strategic dependencies and structural challenges. Lead markets measures were proposed for steel, cement and aluminium, to start with, and chemicals, at a later stage. These are the most energy and emissions-intensive sectors, as well as sectors for which demand will increase, driven by the green transition needs. Rather than applying a single uniform “European content” threshold across all net-zero technologies, the IAA tailors requirements to the specific structure, maturity, and dependencies of each sector. This approach allows the EU to gradually increase the share of European-made components where it is most impactful and realistic. The targeted design ensures that intervention is proportionate and focused where it can deliver the greatest resilience and economic return.
What does ‘Made in EU’ mean for third countries?
The European Union remains one of the world’s most open markets and is committed to maintaining that openness as a key source of economic strength and resilience. The proposal encourages greater reciprocity by providing equal treatment for public procurement as well as other forms of public intervention to countries that offer EU companies access to their markets through trade agreements. Companies from these countries will therefore benefit from treatment equivalent to Union-origin content. Therefore, ‘Made in EU’ requirements do not restrict market access or consumer choice in an unwarranted manner, but ensure taxpayers’ money benefits European companies and workers. They are designed in a targeted and proportionate manner to create demand in European strategic value chains, giving investor certainty, avoiding critical dependencies, while at the same time ensuring that the EU honours its commitments towards international partners and continues to be open to international trade and investment on fair terms.
What does the Act propose in terms of permitting? What are Industrial Accelerator Areas and what benefits will they bring?
The IAA proposes to fully digitalise permitting processes for industrial manufacturing projects, introduce clear time limits and, for certain projects such as energy-intensive industry decarbonisation or projects located in Industrial Acceleration Areas, allow for faster approval of intermediary steps where authorities do not respond within set deadlines. Dedicated single points of contact and maximum timelines of 18 months for specific projects will speed up energy intensive industries’ decarbonisation investment in the EU.
These measures are designed to provide greater clarity, predictability, and legal certainty for investors. By reducing administrative delays and ensuring transparent, trackable processes, the IAA lowers investment risk and accelerates project deployment.
Member States shall designate Industrial Acceleration Areas to encourage the creation of strategic manufacturing clusters. Projects located in these areas benefit from faster permitting, improved coordination, and better access to infrastructure, financing, and skills ecosystems. The objective is to create competitive industrial hubs that attract investment, facilitate decarbonisation, and strengthen supply chain resilience.
What are the implications for non-EU investors/companies that want to invest in the EU?
The EU remains open to foreign direct investment (FDI). The IAA sets conditions, however, for foreign investments above €100 million by companies originating in countries that hold more than 40% of global production capacities in EVs, batteries, solar, and critical raw materials. Conditions include EU shareholding majority, technology transfer, integration into EU value chains, and job creation.
These measures complement the EU’s existing foreign direct investment (FDI) screening framework. While FDI screening focuses on national security risks, the IAA addresses the economic impact of major investments on the functioning of the Single Market, such as supply security and added value to the Union. By applying common conditions across Member States, the IAA will strike a carefully calibrated balance by ensuring that strategic foreign investments contribute to Europe’s competitiveness, resilience, and industrial transformation, while preventing fragmentation
How does the Industrial Accelerator Act deliver on the Draghi report?
The IAA puts the Draghi report into action by proposing targeted EU-made and low-carbon content requirements to create demand for EU net-zero tech and low-carbon industrial products using public procurement money, public schemes and auction funding. In doing so, it operates as an ‘insurance policy’ to make sure the EU becomes more independent in those strategic economic areas where significant investments are needed.
 
 
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Countries must shift toward fiscal discipline and reforms that raise long-term growth.

Many highly indebted advanced economies face a grim fiscal outlook. Under current policies, the public debt ratios of countries including Belgium, France, the United Kingdom, and the United States are set to deteriorate over the next two decades. They still have room to borrow, but there are limits.
So far, financial markets have been forgiving. But recent tremors suggest that they may become more sensitive to negative news about the fiscal or economic outlook. They may demand higher interest rates even from countries with highly liquid government bond markets, making the job of reducing debt that much harder.
AI-driven productivity growth may slow the increase in debt ratios and reduce the needed adjustment. But the magnitude and timing of this effect are unclear. Population aging and growth declines linked to trade fragmentation and political uncertainty pull in the opposite direction.
What will it take to stabilize debt ratios? In a recent paper with Gonzalo Huertas and Lennard Welslau, we assessed the fiscal adjustment needed in EU countries, the UK, and the US. Using official growth forecasts and market-based projections for interest rates, exchange rates, and inflation, combined with simulated shocks, we generated probability distributions for future debt ratios under different scenarios for the primary balance, which excludes interest payments on the debt.
We considered a 20-year horizon starting in 2024 and divided it into two periods. In the first, a seven-year period, governments raise the primary balance to a level that ensures debt sustainability. In the following, 13-year, period, governments keep the primary balance constant, excluding spending changes driven by an aging society. We aimed to ensure a 70 percent probability that the fiscal adjustment in the first period was large enough to stabilize the debt ratio over the final five years of the 20-year horizon.
Mixed findings
On the positive side, the required long-term primary balance does not look dramatically high in many cases. For example, it is 1.3 percent of GDP for France and the US, 1.8 percent for Belgium and the UK, and 2.5 percent for Italy. On the negative side, however, given large deficits in 2024, substantial adjustments are likely to be needed. About a dozen countries require adjustments of more than 3 percent of GDP; five of those–France, Poland, Romania, the Slovak Republic, and the US–need adjustments of 5 percent relative to 2024.
On paper, almost all EU countries plan adjustments to stabilize the debt ratio. However, several use macroeconomic assumptions that are more optimistic than the EU’s common methodology. Germany’s plan, for example, assumes higher inflation and growth than expert forecasts. If actual growth and inflation turn out lower, Germany’s deficit and debt will end up much higher than it projects.
Moreover, forecasts by the European Commission and the IMF suggest that countries with the biggest adjustment needs are unlikely to deliver the measures needed to stabilize their debt levels. This reinforces doubts about the likelihood of these adjustments.

Historical precedents
While the US and several other advanced economies are unlikely to make fiscal adjustments needed to stabilize debt in the medium term, they may try later. To see how likely this is, we looked at historical precedents: how often countries achieved the required primary balance, the longest period balance was maintained, and how often they made the needed adjustment within seven years.
Our results show that primary balances at the level needed to stabilize debt in several high‑debt advanced economies—and the large adjustments needed to get there from current fiscal positions—are rare. France, for example, would need a primary surplus of 1.3 percent of GDP to stabilize its debt, which has happened only six times in five decades. This does not mean such adjustments are impossible, but history suggests it will be difficult and likely to take longer than the seven years EU fiscal rules envisage.
Policymakers in these economies can take heart from the transformation of what were once considered the euro area’s weakest links. In 2024, Greece posted a primary balance of 4.0 percent, adjusted for swings in the business cycle—well above what is needed to stabilize debt. Portugal needs only a minor adjustment of 0.5 percent of GDP; Ireland’s required adjustment of 1.9 percent is modest, and the country’s debt ratio is exceptionally low, at 39 percent of GDP, far below 122 percent in the US and the UK’s 101 percent.
How did countries that faced severe fiscal crises 15 years ago become examples of discipline today? After the 2008 global financial crisis, financial markets drove them to the edge of collapse, forcing them to accept EU/IMF lending programs. Despite design flaws, these programs’essential fiscal tightening and structural reforms put their economies back on track for sustainable growth. The adjustment was painful and, in the case of Greece, very long-lasting, but it was eventually effective.
The results speak for themselves. With average annual growth between 3.1 percent and 4.2 percent in 2022–25, all three countries exceeded the US pace of 2.6 percent.
The lesson: Fiscal discipline and structural reforms—along with public and private debt restructuring when debt is unsustainable—pay off eventually. Not surprisingly, these reforms and restructurings did not stem from domestic political momentum but were forced on them by market pressure.
Recognize the risks
The question is, How will countries adjust this time? We see several possibilities.
The best outcome would combine growth-enhancing reform—including by implementing the Draghi report’s single-market agenda in the EU—with deep reforms to social security and pension systems. It could also include overhaul of tax systems to raise revenue without discouraging growth. The latter is particularly true for the US—the only Organisation for Economic Co-operation and Development country without a value-added tax.
Unfortunately, this outcome is also politically the most difficult. A more likely path to fiscal consolidation involves a shift in domestic political leadership that prioritize fiscal discipline but not necessarily deep reform. Italy offers an example. Scarred by near disaster in the early 2010s, Italian governments across the political spectrum have kept budgets broadly under control. Italy’s debt ratio of roughly 135 percent of GDP is still high, but its cyclically adjusted primary balance of 0.3 percent of GDP looks far healthier than those of Belgium, France, or the UK.
A hard‑landing scenario could be triggered by a sudden spike in borrowing costs, leading to debt distress. As debt rises, interest rates could also climb, and markets might become more sensitive to news that calls fiscal sustainability into question. Governments might attempt forms of financial repression—for example, encouraging domestic banks or institutions to absorb additional government debt—but such measures have limits. Surprise inflation could temporarily ease fiscal pressures, but persistently higher inflation would eventually drive up nominal interest rates.
Let’s hope that policymakers recognize these risks and act early enough to prevent such an outcome.

 
 
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Blog | Connections to global markets and supplies are a precondition for trade driven development, investments, and jobs. Here, we analyze how the global shipping network has evolved and the impact on countries position in the network over the last two decades.  

Two snapshots of the global liner shipping network: Moving towards more hub-and-spoke connections
The data reviewed here describe scheduled container shipping services between pairs of countries, capturing both the presence of a direct connection and the number of shipping lines operating on each bilateral link. We benefit from a unique dataset, the MDST Container Data Bank1, which comprehensively captures all regular container shipping services, globally, for two full decades. The period has been characterized by a process of consolidation among shipping lines, while also seeing a continued growth of containerized trade.
The analysis compares two snapshots of the network, one from early 2006 and one from early 2026, redrawn using identical methods to permit visual comparison.2 The third chart displays the distribution of the number of direct partners per country in each year
The dataset enables an examination of the number of bilateral connections, and the intensity of those connections, expressed through shipping line counts. It also allows a comparison of how direct connectivity is distributed, and how the network’s structure has shifted.
 
Figure 1. Q1 2006 Liner Shipping Network
(Click on image for full resolution)

Source: Authors, based on data provided by MDST

 
Figure 2. Q1 2026 Liner Shipping Network
(Click on image for full resolution)

Source: Authors, based on data provided by MDST

Network characteristics: What has changed over the last 20 years
The total number of countries included in the global liner shipping network rises from 174 in 2006 to 178 in 2026. Yet the number of direct bilateral connections falls from 2,444 to 2,243. A larger network with fewer direct links results in a lower density: the percentage of country pairs with a direct link decreased from 16.2% to 14.2%.
The  main consequence is that trade between more than four out of five pairs of countries depends on transshipment, and this reliance becomes more pronounced over the two decades, as direct links thin out. For many smaller developing economies and small island states, which already sit at the lower end of the connectivity distribution, this shift heightens their dependence on intermediary hubs for access to global markets.
The average number of direct partners per country falls from 28.1 to 25.2, and the median declines from 22 to 17. These shifts are also visible in the histogram of degree distributions, where the 2026 curve sits to the left of the 2006 curve. More countries have fewer direct partners than they did twenty years earlier.
 
Figure 3. Number of direct connections per country, 2006 and 2026

Source: Authors, based on data provided by MDST

 
The long tail of highly connected countries also shortens. In 2006, the United Kingdom had 117 direct partners, followed by Belgium and the United States. By 2026, the top position is held by Spain with 97, followed closely by the United States, China, and the Netherlands. The underlying cause for these trends is the process of consolidation in liner shipping, including mergers and acquisitions, which, combined with larger vessel sizes, encourages hub-and-spoke operations.
The range between the best and worst connected countries remains high. In both years the least connected countries have only one or two direct partners—these are mostly small island states. For these economies, direct maritime access is limited, and the decline in average connectivity globally is particular concern, as investments and new jobs require access to markets and to supplies.
Competing and connecting: Countries served by the shipping lines
Two different metrics are useful to describe service intensity in the network.
First, at the global level (across all bilateral links), the number of shipping lines per edge captures how intensively each country pair is served. The median remains unchanged at four liner companies, while the global average declines from 9.76 to 8.32 between 2006 and 2026. This combination indicates that the “typical” link is stable, but heavily served routes have lost choice over time, making the overall distribution more uneven.
Second, at the country level, we look at the average number of lines per direct connection for each country. In 2006, a typical country had 6.7 companies per link, with a median of five, but the range was wide: from countries averaging only two operators per route to a few with averages approaching twenty‑four. This reflected large differences in competitive conditions across countries, particularly disadvantaging many small developing economies and small island states. By 2026, this country‑level pattern largely persists, though with lower averages across much of the distribution. Some countries continue to enjoy routes served by many companies, while many others remain reliant on a small number of operators. The persistence of low per‑country averages for less connected economies underscores the continued unevenness of service availability in the global network.
Improving connectivity
A country’s position in the global liner shipping network depends on three key determinants3.

Its domestic cargo base and hinterland: Carriers are more likely to call in a port if there is demand for import and export cargo.
Its geographical position: The closer a country is to the main shipping routes, the less costly it is for the shipping line to deviate and call in an additional port.
Port performance: The time ships and their cargo spend in port is a key consideration for shipping lines to choose a port. Shippers, i.e. the carriers’ clients, have also an interest in short cargo dwell times.

Shipping lines may not only choose to call in a port, but also potentially invest through vertically integrated terminal operators. Once a terminal is operated by a shipping line-associated operator, it is more likely that its sister shipping line or alliance chooses this port – with the collateral that competitors my prefer not to call elsewhere.
The World Bank Group is supporting its clients to improve their position in the global shipping network to ensure that trade-driven development creates the necessary jobs. Performance indicators such as the Container Port Performance Index (CPPI) or the Logistics Performance Indicators (LPI) help identify potential improvements in the time ships and containers spend in port. The Global Supply Chain Stress Index (GSCSI) tracks supply chain stress, including port congestion. And the Port Reform Toolkit (PRT) helps governments and private investors identify options for public-private-partnerships and potential investments in partnership with the World Bank Group.
 

1 The “Containership Databank” provided by MDS Transmodal covers the world’s container carrying fleet of over 6,000 vessels based on known service deployment. Every vessel in service has multiple fields of information including operator, service, route, TEU capacity, service frequency, port rotation and much more. The Containership Databank also includes information about vessels on order and vessels removed from the commissioned fleet. Service deployment of individual vessels in the fleet frequently changes – the Containership Databank tracks these changes and is continually updated. Analyses that are regularly produced to provide advice for clients include: Capacity by operator, route and trade lane; Trends on a consistent quarterly basis since 2006; and Fleet analysis by operator, size, configuration of ships and fuel type.
The Containership Databank is among the sources for global indicators such as the Logistics Performance Indicators (LPI) developed by the World Bank; the Liner Shipping Connectivity Index (LSCI) developed in partnership with UNCTAD; and the Maritime Trade Connectivity Indicator (MTCI) developed in partnership with OECD/ITF.
The data reviewed here describe scheduled container shipping services between pairs of countries, capturing both the presence of a direct connection and the number of shipping lines operating on each bilateral link.
2 The liner shipping network is modelled as a weighted, undirected graph. Nodes represent countries (ISO‑3 codes). An edge exists between two countries if at least one liner shipping company operates a direct bilateral service; edge weight reflects the number of distinct shipping lines serving that pair.
Layout is generated using a force‑directed spring layout (NetworkX spring_layout) with parameters: k = 4.0, iterations = 500, random seed = 42,  node_size = log(degree+1) × 75, weighted_degree = ∑ companies on all adjacent edges. Distances are weighted inversely to edge weights, so country pairs connected by many shipping lines are drawn closer together.
Images generated with Microsoft Copilot Analyst World Bank Group license.
3 Wang and Cullinane 2016; Fugazza and Hoffmann 2017; UNCTAD 2017; Jouili 2019; Ducruet 2020; Hoffmann and Hoffmann 2020; Guerrero et al. 2021; Mishra et al. 2021; Hoffmann and Hoffmann 2021; Wang, Dou, and Haralambides 2022; Hoffmann et al. 2024; Faure and Ducruet 2025; Canbay et al. 2026; Tsantis et al. 2026. 

 
 
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Blog | Tariff hikes are putting European companies under strain at a time when productivity growth is already sluggish. Short-term business sentiment is not the only thing at stake. Tariffs could also dampen business dynamism, a key channel for innovation and long-term growth.

Business dynamism – the constant churn of firms entering the market, growing, contracting and then exiting – is crucial for productivity. Through “creative destruction”, new firms with better technologies and business models take the place of their older, less efficient counterparts. Meanwhile, competition compels incumbent firms to innovate, invest and stay sharp if they want to remain competitive. When this process weakens, productivity slows. This blog post focuses on how the current trade tensions are threatening incumbents in the euro area. Specifically, it looks at their risk of exit and their decisions to scale up or down. It also examines why tariffs matter for productivity and long-term economic growth and what this means for monetary policy.
Do trade tensions pose a risk to the euro area outlook?
Before we delve into the details, let’s take a step back and set the scene.
Last year’s tariff increases are already weighing on the euro area economic outlook.[1] However, beyond the immediate impact on exports lies a deeper concern: if export-oriented firms – which are typically more efficient and innovative – scale back their activity or shut down entirely due to higher tariffs, the economy will lose some of its strongest producers. This will make resource allocation less efficient. It will slow the spread of new technologies. And overall productivity will decline over time.
Uncertainty amplifies these effects. When firms cannot reliably predict conditions of trade, and hence future revenues, they tend to adopt “wait-and-see” strategies. They delay investment. They postpone their expansion plans. And they often shift innovation away from risky frontier research towards safer, more incremental projects. While these strategies may protect firms in the short term, they also slow the pace of technological progress across the economy. A prolonged period of high uncertainty and pressure on profits can therefore weigh on growth for years.
What can the firm-level data tell us?
To understand how firms respond to trade tensions, we need detailed data. Firm-level administrative records – though sometimes delayed and with larger firms over-represented – offer a window into the mechanisms that drive business creation, expansion and exit.
We draw on detailed data for Germany, Spain, France and Italy from 2008 to 2023 to examine how trade tensions affect incumbent businesses based on their exposure to international markets.[2] Exposure is identified by taking sectors whose share of sales to the United States stands above the median within each country. These are industries whose exports to the United States are greater than those of at least half of the other industries in the same country.
Our dataset combines information from Orbis and BACH, covering more than three million firms and around 27 million observations. This robust information allows us to track firm growth and exit patterns. It also enables us to control for firm characteristics, as well as country and sector-specific factors – for instance, the exceptional disruption caused by the COVID-19 pandemic.
To capture swings in global trade tensions, we use a text-based index that counts newspaper mentions of tariffs, trade disputes, retaliation and related topics.[3] Only sharp spikes – significant deviations from historical patterns – are classified as trade shocks. Unsurprisingly, the most notable episode in our sample coincides with the first Trump Administration.
Our results show that trade shocks lowered the chances of firms expanding (Chart 1, panel a) and raised the risk of firms exiting (Chart 1, panel b). These effects were strongest for firms that were heavily exposed to the United States, although the differences between highly export-oriented firms and the rest were moderate, albeit statistically significant.
This matters because the firms that are most exposed to trade with the United States are also, on average, the most productive (Chart 1, panel c): they generate more value added per worker and are often more innovative. When these firms shrink or exit altogether, the economy loses not only jobs, but also some of its most productive capacity and dynamic elements.

Chart 1
Trade shocks and firm performance by exposure to the United States

a) Percentage change in likelihood of job creation

b) Percentage change in likelihood of firm exit

c) Productivity ratio by exposure to trade with the United States

(percentage)

(percentage)

(ratio)

Sources: BvD Electronic Publishing GmbH – a Moody’s Analytics company, Banque de France, European Commission, Durrani (forthcoming) and ECB staff calculations.
Notes: Trade shock residuals with +1 standard deviation from an AR(1) regression for the trade tensions index by Durrani (forthcoming). Low (high) exposure firms in sectors and countries with a share of sales to the United States below (above) the median. Cox proportional hazards estimates controlling for firms’ balance sheets, size, performance, and country and sector effects. Estimates statistically significant at 99%. In panel c, ratio of productivity (value added per employee) between low and high-exposure firms.

Beyond the obvious: supply chains and fragmentation
And yet, the overall impact of trade tensions on productivity may be even larger than might be suggested by firm-level churn alone. Other transmission channels include:

supply chain disruptions and costly reorganisations that prioritise resilience over efficiency;
trade fragmentation, which can reduce the size of export markets and impair economies of scale;
loss of access to key inputs, undermining production efficiency;
reduced technology diffusion, which is particularly harmful for catching-up economies.

All of these channels can slow innovation, erode competitiveness and weaken potential growth.
Why does this matter for monetary policy?
Slower productivity growth can reduce an economy’s potential output and increase inflationary pressures. This is because weaker productivity growth limits how fast an economy can expand without pushing up costs and prices. It also lowers the natural rate of interest consistent with stable inflation. This limits the room for central banks to cut interest rates during downturns. As explained in an earlier ECB Blog, weaker productivity growth can also make an economy more sensitive to financing conditions. Even small rate increases can significantly slow investment and hiring.
In short, rising tariffs and persistent trade tensions affect much more than individual firms. They reshape the macroeconomic landscape in which monetary policy operates – narrowing the room for manoeuvre and making the economy as a whole more vulnerable.
The views expressed in each blog entry are those of the author(s) and do not necessarily represent the views of the European Central Bank and the Eurosystem.

See, for example, European Central Bank (2025), “US trade policies and the activity of US multinational enterprises in the euro area”, Economic Bulletin, Issue 4
Our dataset includes annual values of firm-level characteristics such as age, number of employees and industry, as well as financial variables (e.g. leverage – the ratio of total liabilities to assets), performance indicators (e.g. revenue growth) and the status of the firms (e.g. new entrant or exit). However, firm entry is substantially underreported in the data, which prevents a rigorous analysis of business creation. This limitation is unlikely to materially affect our analysis, as newly established firms tend to be smaller and less export-oriented. In our sample, the share of new firms exposed to US trade is around 2%, while the share of firms with 10+ years is about 60%.
To capture swings in trade tensions, we use a Durrani (forthcoming) text-based indicator constructed from local newspapers in Germany, Spain France and Italy. Each month, articles related to tariffs and trade tensions are identified using a supervised text classification model. The index is computed as the share of identified articles in total articles for a given month.

 
 
Compliments of the European Central Bank The post ECB | How Tariffs Threaten Business Dynamism, Productivity and Growth first appeared on European American Chamber of Commerce New York [EACCNY] | Your Partner for Transatlantic Business Resources.