Keynote speech by Piero Cipollone, Member of the Executive Board of the European Central Bank, at the National Conference of Statistics on official statistics at the time of artificial intelligence

It is a pleasure to be here today to discuss the implications of artificial intelligence (AI) from a central bank’s perspective.[1]
The world is witnessing extraordinary advances in the field of AI.[2] We are moving from analytical AI models designed to perform specific tasks[3] to generative AI models capable of creating human-like content.
The burgeoning interest in generative AI has boosted AI adoption.[4] A recent international survey revealed that almost three-quarters of organisations had adopted AI for one or more business functions, and around two-thirds of them are using generative AI. Nevertheless, just 8% reported using AI for five or more business functions – suggesting that we are still in the initial stages of AI integration.[5]
AI can be applied to a wide spectrum of activities, from routine and repetitive tasks to knowledge-based and creative work. It has been argued that AI is a general-purpose technology – akin to the steam engine, electricity or the computer – with the potential to transform our economies in the long run.[6]
But, like the computer before it, AI may involve a paradox similar to the one made famous by the economist Robert Solow: “You can see the computer age everywhere but in the productivity statistics.”[7]
The dawn of the computer era saw information and communication technology (ICT) profoundly alter our personal lives and the economy. Today, our workplaces, homes and social lives are interwoven with digitalisation.
At the European Central Bank (ECB), our Information Systems department has become the largest business area within the institution. ICT has become key to our core tasks, from the economic models that underpin our forecasts to monetary policy implementation and the operation of market infrastructures.
Yet technology has not fundamentally changed the way we think about monetary policy. Moreover, just as Solow observed, the macroeconomic impact of ICT on productivity has not been as large as might have been expected – at least outside of the tech sector.
Indeed, the transformative potential of AI may not always be productivity-enhancing. Consider, for example, a recent AI-generated deepfake video of the actor Tom Cruise dressed in a bathrobe and singing Elton John’s “Tiny Dancer” to Paris Hilton that went viral on TikTok.[8]
Might we see another Solow paradox emerge in the context of AI? In other words, what is the potential of AI to boost the productive capacity of the economy, as well as that of central banks?
Today I will take stock of what we know about the impact of AI on the economy and discuss its possible implications for our monetary policy. I will then share the ECB’s perspective on how we can best use AI in our central banking tasks, while putting in place the necessary safeguards for its responsible use.
 
The macroeconomic impact of AI and its implications for monetary policy
 
The macroeconomic impact of AI
AI could affect the economy in several areas that are particularly relevant for the conduct of monetary policy. Today I will highlight just three of them.

AI and productivity
The first area relates to productivity.
The potential of AI to raise productivity is undeniable – from acting as a powerful coding assistant to running autonomous “smart factories”. AI could increase productivity through various channels – for example, via direct productivity effects that boost total factor productivity or through individual production factors.
Indeed, several studies already point to sizeable AI-induced productivity gains at firm level.[9] But estimates of aggregate effects over the coming decade differ markedly across studies – from an increase in annual total factor productivity growth of less than 0.1 percentage points to annual labour productivity growth of up to 1.5 percentage points.[10]
The eventual outcome will depend on whether we see a rapid and broad-based adoption and diffusion of AI across all sectors of the economy. Up until now, the sheer speed of diffusion across sectors and firms has little historical precedent.[11] And survey evidence suggests that adoption by European firms nearly matches that of North America.[12]
But a key risk stems from the possibility that most of the value created by AI is extracted by a few companies that end up dominating the AI ecosystem.[13] This is a key reason why productivity gains from AI at firm level may not translate into sustained value-added gains at the aggregate level, as market power increases costs. We saw this happen already with the rise of IT[14], which resulted in productivity gains being concentrated in the IT sector and primarily benefiting countries with large, successful tech firms. This is also reflected in the unprecedented concentration of market value in the “Magnificent Seven” firms in the United States.[15] These are currently benefiting from the AI boom and making higher yearly profits than all the listed companies of France, Germany and Italy combined.
This has important implications for Europe. As Mario Draghi recently observed, EU productivity growth over the past twenty years would have been on a par with that of the United States if it were not for the tech sector.[16] Current data point to the euro area trailing behind the United States in terms of private investment in AI[17], as well as patent applications and journal publications in the field.[18] It is therefore critical to devise a European AI strategy with a threefold aim: to preserve competition in the AI space[19]; to create an ecosystem that supports’ European AI firms’ competitiveness, generating sectoral productivity gains over time[20]; and to support the diffusion of AI across the economy, facilitating the development of AI-supported products and services.[21]

AI and the labour market
The labour market is the second area of the economy that is likely to be affected by AI.[22]
New technologies can substitute or complement labour. On the one hand, automation implies capital taking over a task previously performed by a worker. On the other, productivity tends to increase with the automation of tasks, which may contribute to increased labour demand for non-automated tasks if price reduction brought about by productivity-improving technology spurs strong demand growth.[23] And new technology can lead to the creation of new kinds of jobs.[24] Whether AI represents an opportunity or risk for employment depends on the net effect.
ECB staff analysis suggests that around 25% of jobs in European countries are in occupations that are highly exposed to AI-enabled automation, while another 30% have a medium degree of exposure.[25] Other research finds that knowledge-intensive services in particular – including finance and insurance, advertising, consultancy and IT – are most likely to be affected by AI.[26]
Initial evidence for Europe suggests that, on average, occupations more exposed to AI have seen an increase in their share in total employment – although mostly for highly skilled occupations and younger workers, and with significant heterogeneity across countries.[27] But the ultimate impact on employment remains uncertain and is likely to hinge on equipping the workforce with skills that complement AI.[28]
 
AI and financial stability
The third area of the economy that may be affected by AI is financial stability.
Certainly, AI can bring benefits to the table. The application of AI could allow banks to conduct more efficient risk assessments and capital and liquidity planning.[29] But there are also risks. If new AI tools are used widely in the financial system and AI suppliers are concentrated, operational risk, market concentration and too-big-to-fail externalities may increase. Furthermore, widespread AI adoption could heighten the potential for herd behaviour, market correlation, deception, manipulation and conflicts of interest.[30]
 
Implications for monetary policy
Central banks, including the ECB, are monitoring these developments closely.[31] Not only does AI influence the environment in which we operate, it also affects how that environment interacts with our monetary policy.
 
Inflation
First, AI could affect cost pressures in the economy in both directions.
We may see AI exerting downward pressure on prices in various ways. For instance, if the net effect of AI is that it substitutes labour and increases productivity, we could see a reduced risk of labour shortages and downward pressure on unit labour cost growth. This is especially relevant in the euro area, where unemployment is at a record low and the working age population is projected to decline by 19% by the end of the century as a result of population ageing.[32]
AI could also lead to a decline in energy prices through its impact on the supply side, for instance through enhanced grid management and more efficient energy consumption. And it could provide consumers with better tools for price comparison.
But AI could also create upward price pressures.
For instance, the uptake of AI will also have an impact on global energy demand, with the computational power required for sustaining AI’s rise doubling every 100 days.[33] This could push up energy costs. Moreover, AI may encourage discriminatory pricing by facilitating the real-time analysis of consumer demand and price elasticities. And algorithms consistently learn to charge collusive prices that are higher than competitive ones, even without communicating with one another – in part by exploiting well-known biases that deviate from rational consumer behaviour.[34]
 
Monetary policy transmission
Second, we may see AI affect monetary policy transmission.
AI is likely to create new winners and losers in the labour and capital market, with consequences for income and wealth distribution.[35] This matters for monetary policy because it can influence people’s marginal propensity to consume and their access to credit, which in turn affect how demand responds to changes in monetary policy.
Moreover, if AI leads to a change in financial structures, such as an increase in non-bank intermediation,[36] it may have further implications for monetary policy transmission. There is evidence to suggest that compared with banks, non-banks are more responsive to monetary policy measures that influence longer-term interest rates, such as asset purchases. Non-banks also exhibit higher levels of credit, liquidity and duration risk compared with the banking sector.[37]
 
The natural rate of interest
Third, AI may go on to influence the natural rate of interest.[38]
If AI boosts productivity growth and potential output, we may see upward pressure being exerted on the natural rate of interest, as demand increases for capital to invest in new technologies and expand production capabilities.
But if AI leads to higher rates of labour displacement and causes rising income inequality, we may see some downward pressure on the natural rate, owing to an increase in precautionary savings and a subsequent boost to the supply of loanable funds.
 
Using AI in central banking: AI at the ECB
These developments will play out over time outside the walls of the ECB, and we will be monitoring them closely. But within the ECB’s walls, AI also has the potential to help with multiple tasks.[39]
Let me give you a few examples.
 
Statistics
Given that we are here at the National Conference of Statistics, it is fitting to begin with statistics. The ECB needs trustworthy and high-quality statistical products, services and a wide range of data to inform its monetary policy decisions.
A key lesson from the global financial crisis was that aggregate statistics alone are insufficient to grasp the complexity of financial markets. We need more granular data.
As you can imagine, the resulting datasets are so vast in terms of the number of observations they contain that collecting and disseminating them requires the use of statistical processes and analytical methods that surpass traditional statistical approaches.
Around six years ago the ECB began exploring the application of AI to improve the efficiency and effectiveness of its statistical processes. And these efforts are reaping dividends.
We use AI to improve the quality of our datasets, from identifying and matching observations across datasets to using modern machine learning techniques for quality assurance.[40]
Moreover, large language models (LLMs) can support statistical processes in ways that were once simply not feasible. These include unlocking new and non-traditional data sources – for instance, unstructured data like text, image, video or audio. These sources can complement and enhance our existing data collections.
 
Economic analysis
AI is also increasingly being incorporated into the economic analyses we carry out to help us prepare our monetary policy decisions.
AI can identify patterns in data more effectively than traditional methods. This is particularly true for non-linearities, which have been playing a bigger role in an environment that is becoming more shock prone. AI also enables the real-time analysis of economic indicators, helping central banks to make more timely policy decisions – a particularly valuable capability in times of crisis.
What do these applications look like in practice?
ECB staff use AI to nowcast inflation. This includes web-scraping price data and using LLMs for data classification. We are currently exploring the use of Big Data and new generative AI models in close cooperation with the BIS Innovation Hub.[41]
Staff are also applying machine learning models to euro area inflation forecasting, accounting for possible non-linearities.[42] These models are already performing well compared with our conventional forecast and survey-based measures of inflation expectations. Another project is employing machine learning techniques to nowcast global trade.[43]
Staff are also exploring the possibilities opened up by innovative datasets. For instance, projects include using a combination of text data and machine learning techniques to quantify risks and tensions in the global economy and exploring the use of satellite data to track economic activity.[44]
 
Communication
Central bank communication is another area in which AI can contribute.
AI could help in areas where central bank communication is key, such as ensuring that policy decisions are well understood and keeping inflation expectations anchored. With AI, we can rapidly analyse vast volumes of media reporting and market commentary.
Moreover, AI can help us communicate with the public in all parts of the euro area. As a European institution, the ECB communicates in all 24 official languages of the EU. Even today, AI and machine translation are helping us meet a demand for translation that exceeds 6 million pages per year. Without those tools, the ECB’s language services would be limited to covering around 150,000 pages per year.
AI can also help broaden our reach by simplifying key messages and communication products for targeted audiences[45] that have less awareness or knowledge of the ECB.[46] And it could help us answer any questions the public may have.
All these innovations could ultimately make the ECB better understood, facilitate the effectiveness of our monetary policy and boost our accountability.
 
Market infrastructures and payments
AI might also bring profound changes to the field of market infrastructures and payments.
The technology could help design and develop innovative payments services customised to consumers’ needs and preferences. And it could help foster financial inclusion, for example, by facilitating voice activated payments. These potential developments are clearly relevant when it comes to the ECB’s role in promoting efficient, integrated and inclusive payments.
Moreover, AI could also help us oversee payment systems. There is an opportunity to use AI as part of early warning models that aim to identify financial stability risks related to financial market infrastructures before these risks materialise. And it could play a supporting role in the scrutiny of information provided by overseen entities, helping us ensure that their practices align with the applicable regulatory frameworks.
The ECB has developed an AI action plan to facilitate the adoption of AI wherever it is relevant to our tasks. It aims to develop and deploy the necessary AI tools and infrastructure, while fostering AI skills and ensuring the technology is used safely and responsibly.
 
The limits of AI: putting the necessary safeguards in place
Let me now turn to the limits of AI.
A key strength of human intelligence is the ability to reflect on its limits. As the philosopher Immanuel Kant once wrote, “we can cognize of things a priori only what we ourselves have put into them”.[47] But AI does not have this capacity for self-reflection. Nor does it have the ability to produce its own safeguards independently of human critical thinking. We therefore need to be aware of the limits of AI and their implications for the ECB, so that we can put the necessary guardrails in place.
First, we need to ensure confidentiality and privacy.
Given the sensitivity of central banks’ decisions, guaranteeing confidentiality is a key condition for the in-house use of AI. Likewise, when it comes to data use, AI will increase concerns about privacy, underlining the importance of applying technological and governance safeguards and complying with regulations such as the EU AI Act.
Take, for instance, the AI solutions we use for our statistics. These tools need to provide comprehensive documentation. This is a prerequisite for clarifying how AI solutions have been used to assess, improve or integrate data. Trust in these solutions comes from first understanding them.
The second risk stemming from AI is the degree to which it can be used to spread false information and data, facilitate fraud or launch cyberattacks.
Since late 2022 there has been a 53-fold increase in generative AI-related incidents and hazards reported in the media.[48] It is one thing for an AI-generated deepfake video of Tom Cruise to go viral. But it is quite another when a deepfake of a policymaker goes viral – particularly at moments of crisis, when attention levels are high and volatility and uncertainty are already pronounced.
At the same time, AI can be used to detect and address such risks. It can help prevent and detect cyberattacks by identifying anomalies in user, system and network behaviours in real time.[49]
The third risk emerges from what we might describe as an over-arching dependence on AI. And this can manifest itself in several ways.
For instance, a greater dependence on AI may inadvertently increase the risk of falling into an “echo chamber” trap.
Given that LLMs are trained using available data and information – which, over time, will increasingly be produced by AI – there is a risk of AI becoming self-referential or repeating existing biases.
To the extent that this dynamic increases the impact of central bank communication on markets, while central banks look to the markets for information, it could increase the risk of central bank echo chambers emerging.[50] This could, for instance, increase the risks of using forward guidance.[51]
An excessive reliance on AI could also reduce our own operational resilience.
As AI becomes a bigger part of our way of working, we may find ourselves growing more dependent on it for core tasks. That is why it is so important to understand the properties of the AI algorithms and models we use to reduce the risks of a potential “black box” effect.
Similarly, if it is not used responsibly, AI could also suppress the diversity and originality of thought, thereby increasing the risk of groupthink and confirmation bias. The mathematician Alan Turing once famously asked, “Can machines think?”[52] The last thing we want is for the same question to be asked about central bankers who end up being too reliant on AI.
A key feature of human cognition is the ability to question existing theories, produce new ones and identify data to test them.[53] This ability needs to be preserved. ECB Governing Council meetings are best understood as a process of comparing views on the economy, considering alternative interpretations of economic developments and assessing risks from multiple perspectives. The ongoing uncertainty in the economy shows that we need to do this more, rather than less.
The overall lesson is that humans need to remain firmly in control, not only to ensure a trustworthy use of AI systems, but also to address questions of accountability and maintain the public’s trust in the central bank.
 
Conclusion
To conclude, as we enter the AI age, we face the challenge of realising its potential while managing its risks.
Whether AI will show up in productivity statistics or create a new paradox remains uncertain. To an extent, whether we face an AI productivity paradox will partly depend on our ability to accurately measure its contribution – and statisticians have an important role to play given the complexity of measuring intangible capital.[54]
But as with other technologies, for AI to be able to produce its full effects, the right ecosystem must be in place – one that facilitates competition in the AI sphere, ensures a fair distribution of possible productivity gains, establishes robust regulatory and ethical safeguards and fosters the corresponding skills in the labour market.
For central banks, AI offers opportunities for innovation and efficiency gains, from economic analysis to communication. But there are also risks that must be considered, and we are duly building appropriate safeguards.
As we integrate AI into our processes, we must ensure that human judgement and critical thinking remain at the forefront. This balance will be essential to maintaining trust in our data, our decisions and the broader financial system.
Thank you.

I would like to thank Jean-Francois Jamet and Simon Mee for their help in preparing this speech, and Siria Angino, Katrin Arnold, Maciej Brzezinski, António Dias Da Silva, Ferdinand Dreher, Maximilian Freier, Gabriel Glöckler, Guzmán González-Torres, Alexander Hodbod, Daniel Kapp, Baptiste Meunier, Roberto Motto, Chiara Osbat, Tom Sanders, Jürgen Schaff, Hanni Schölermann, David Sondermann, Anton Van der Kraaij and Balázs Zsámboki for their input and comments.
Artificial intelligence is a collective term for machine-enabled cognitive processing. The Organisation for Economic Co-operation and Development (OECD) defines artificial intelligence as “a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments.” See OECD (2024), “OECD AI Principles”, May.
For instance, shopping recommendations or text analysis.
Within two months of its launch in late 2022, ChatGPT had already attracted 100 million users. See The Economist (2023), “ChatGPT mania may be cooling, but a serious new industry is taking shape”, 21 September.
See McKinsey (2024), “The state of AI in early 2024: Gen AI adoption spikes and starts to generate value”, 30 May.
See Crafts, N. (2021), “Artificial intelligence as a general-purpose technology: an historical perspective”, Oxford Review of Economic Policy, Vol. 37, Issue 3, Autumn 2021, pp. 521-536 and Agrawal, A. et al. (2019), “Economic Policy for Artificial Intelligence”, Innovation Policy and the Economy, Vol. 19.
Solow, R.M. (1987), “We’d Better Watch Out”, New York Times Book Review.
See TikTok, @ParisHilton and Forbes (2022), “The Story Behind Paris Hilton’s Viral TikTok With DeepTomCruise”, 22 November.
See, for example, Dell’Acqua, F. et al. (2023), “Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality”, Harvard Business School Technology & Operations Management Unit Working Paper, No 24-013.
For instance, see Acemoglu, D. (2024), “The Simple Macroeconomics of AI”, MIT, 5 April; Briggs, J. and Kodnani, D. (2023), “The Potentially Large Effects of Artificial Intelligence on Economic Growth”, Goldman Sachs, 26 March. For an overview, see Filippucci, F. et al. (2024), “Should AI stay or should AI go: The promises and perils of AI for productivity and growth”, VoxEU, 2 May.
One international survey finds that three out of every five white-collar workers are already using generative AI on a weekly basis. The survey encompasses 16 countries spanning the Americas, Europe, Asia and Oceania. See Oliver Wyman Forum (2024), “How generative AI is transforming business and society: the good, the bad, and everything in between”, p. 23.
In 2023 the proportion of European firms reporting the use of AI technologies stood at 57%, compared with 61% in North America, 58% in Asia Pacific and 48% in China. See Maslej, N. et al. (2024) “The AI Index 2024 Annual Report”, AI Index Steering Committee, Institute for Human-Centered AI, Stanford University, Stanford, CA, April.
Acemoglu, D. and Johnson, S. (2023), “Big Tech Is Bad. Big A.I. Will Be Worse”, The New York Times, 9 June.
De Ridder, M. (2024), “Market Power and Innovation in the Intangible Economy”, American Economic Review, Vol. 114, Issue 1, pp. 199-251. See also Philippon, T. (2019), The great reversal: How America gave up on free markets, Harvard University Press.
The “Magnificent Seven” comprise Microsoft, Apple, Nvidia, Alphabet, Amazon, Meta and Tesla. These companies now make up close to one-third of the market value of the S&P index.
See Draghi, M. (2024), “An Industrial Strategy For Europe”, acceptance speech at the Monastery of San Jeronimo de Yuste for the Carlos V European Award, 14 June: “If we were to exclude the tech sector, EU productivity growth over the past twenty years would be on par with that of the United States.” Empirical evidence also indicates that the ICT-intensive sector in the United States has experienced a much higher increase in labour productivity than in Europe: euro area countries have been less efficient than the United States in both adopting IT technologies and leveraging them to achieve labour productivity gains. See Bergeaud (2024), “The past, present and future of European productivity”, paper presented at the ECB Forum on Central Banking 2024.
In 2023 private investment in AI reached USD 67 billion in the United States compared with USD 11 billion in the EU and the United Kingdom combined. See Maslej, N. et al. (2024), Ibid.
Euro area firms filed on average 475 AI-related patents per year from 2002 to 2022, three times less than the United States and twice less than China. In terms of citation-adjusted AI journal publications, the United States also took the lead over the euro area and China. See Bergeaud (2024), Ibid.
See Coeuré, B. (2024), “Comments on ‘The simple macroeconomics of transformative AI’ by Daron Acemoglu”, Economic Policy Panel, Brussels, 4 April and Coeuré, B. (2024), “Artificial intelligence: making sure it’s not a walled garden”, keynote address at the Bank for International Settlements – Financial Stability Institute policy implementation meeting on big tech in insurance, 19 March.
Measures in that direction include investing in AI education, encouraging venture capital investment and an environment that supports AI startups, increasing the mobility of financial capital across EU countries, and strengthening the link between European universities and European AI firms to convert AI research into marketable innovations. See Bergeaud (2024), Ibid.
See Meyers, Z. and Springford, J. (2023), “How Europe can make the most of AI”, Centre for European Reform Policy Brief, 14 September.
See Albanesi, S. et al. (2023), “Reports of AI ending human labour may be greatly exaggerated”, Research Bulletin, No 113, ECB, 28 November.
An elastic demand may support employment even in the face of automation, as productivity growth is reflected in prices and product demand increases. See, for example, Bessen, J. (2020). “Automation and jobs: when technology boosts employment”, Economic Policy, Volume 34, Issue 100, pp. 589-626.
About 60% of employment in 2018 can be classified under job titles that did not exist back in 1940. See Autor, D. et al. (2021), “New frontiers: the origin and content of new work, 1940-2018”, MIT Working Paper, July.
Albanesi, S. et al. (2023) “New technologies and jobs in Europe” Working Paper Series, No 2831, ECB.
See Figure 8 in Organisation for Economic Co-operation and Development (2024), “The impact of Artificial Intelligence on productivity, distribution and growth: Key mechanisms, initial evidence and policy challenges”, OECD Artificial Intelligence Papers, No 15, 16 April.
Albanesi, S. et al. (2023) “New technologies and jobs in Europe”, Working Paper Series, No 2831, ECB.
See Green, A. (2024), “Artificial intelligence and the changing demand for skills in the labour market”, OECD Artificial Intelligence Papers, No 14, OECD Publishing, Paris.
See Figure B.2 in Leitner, G. et al. (2024), “The rise of artificial intelligence: benefits and risks for financial stability”, Financial Stability Review, ECB, May.
See Leitner, G. et al. (2024), “The rise of artificial intelligence: benefits and risks for financial stability”, Financial Stability Review, ECB, May; Gensler, G. (2023), “Isaac Newton to AI”, Remarks before the National Press Club, 17 July; Gensler, G. and Bailey, L. (2020), “Deep Learning and Financial Stability”, 1 November; and Gensler, G. (2024), “AI, Finance, Movies, and the Law”, Prepared Remarks before the Yale Law School.
Bank for International Settlements (2024), “Artificial intelligence and the economy: implications for central banks”, BIS Annual Economic Report 2024, Chapter III, 25 June.
As noted in Freier, M. et al. (2023), “EUROPOP2023 demographic trends and their euro area economic implications”, Economic Bulletin, Issue 3, ECB.
See Ammanath, B. (2024), “How to manage AI’s energy demand — today, tomorrow and in the future”, World Economic Forum, 25 April.
See Calvano, E. et al. (2020), “Artificial Intelligence, Algorithmic Pricing, and Collusion”, American Economic Review, Vol. 110, Issue 10, pp. 3267-97; for biases, see OECD (2024), “The impact of Artificial Intelligence on productivity, distribution and growth: Key mechanisms, initial evidence and policy challenges”, OECD Artificial Intelligence Papers, No 15, 16 April, pp. 33-34.
See Cazzaniga, M. et al. (2024), “Gen-AI: Artificial Intelligence and the Future of Work”, IMF Staff Discussion Notes, No 2024/001.
The use of artificial intelligence for credit scoring could allow big tech with access to large consumer data to rapidly expand in the area of financial services and to challenge banks’ traditional role in financing the economy and serving as the first point of contact for financial services. See Boot, A., Hoffmann, P., Laeven, L. and Ratnovski, L. (2021), “Fintech: what’s old, what’s new?”, Journal of Financial Stability, Vol. 53.
See Work stream on non-bank financial intermediation (2021), “Non-bank financial intermediation in the euro area: implications for monetary policy transmission and key vulnerabilities”, Occasional Paper Series, No 270.
The natural rate of interest is the real rate of interest that is neither expansionary nor contractionary.
See also Moufakkir, M. (2023), “Careful embrace: AI and the ECB”, The ECB Blog.
This allows us to identify and prioritise anomalous observations and outliers that require further attention, assessment and potential treatment.
Osbat, C. (2022), “What micro price data teach us about the inflation process: web-scraping in PRISMA”, SUERF Policy Brief, No 470, 17 November.
See, for instance, Lenza, M. et al. (2023), “Forecasting euro area inflation with machine learning models”, Research Bulletin, No 112, ECB, 17 October.
For example, see Menzie, C. et al. (2023), “Nowcasting world trade with machine learning: a three-step approach”, Working Paper Series, No 2836, ECB.
See, for instance, d’Aspremont, A. (2024), “Satellites turn “concrete”: tracking cement with satellite data and neural networks”, Working Paper Series, No 2900, ECB.
On layered communication, see Work stream on monetary policy communications (2021), “Clear, consistent and engaging: ECB monetary policy communication in a changing world”, Occasional Paper Series, No 274, ECB; see also Bholat, D. et al. (2018), “Enhancing central bank communications with behavioural insights”, Staff Working Paper Series, Bank of England, No 750, August.
Survey evidence suggests that there is a lack of understanding of the ECB’s tasks. Two-thirds of euro area citizens believe that it is the ECB’s task to stabilise the foreign exchange rate, while over one-third think that the ECB’s role is to finance governments. See Chart 7 in Gardt, M. et al. (2021), “ECB communication with the wider public”, Economic Bulletin, Issue 8, ECB.
Kant, I. (1781), Critique of pure reason.
OCED (2024), “OECD Digital Economy Outlook 2024 (Volume 1): Embracing The Technology Frontier”, 14 May, p. 38.
See Cipollone, P. (2024), “One step ahead: protecting the cyber resilience of financial infrastructures”, introductory remarks at the ninth meeting of the Euro Cyber Resilience Board for pan-European Financial Infrastructures, 17 January; and Bank for International Settlements, “Project Raven: using AI to assess financial system’s cyber security and resilience”.
The central bank may no longer observe independent signals about the state of the economy from financial markets, instead mainly seeing the mirror image of its own communications.
Echo chamber dynamics can create a circularity between market prices and forward guidance. See Morris, S. and Shin, H. S. (2018), “Central Bank Forward Guidance and the Signal Value of Market Prices”, AEA Papers and Proceedings, Vol. 108, May, pp. 572-577.
Turing, A. (1950), “Computing Machinery and Intelligence”, Mind, Vol. LIX, Issue 236, October, pp. 433-460.
For instance, see the role of paradigm shifts in scientific development in Kuhn, T. (1962), The structure of scientific revolutions. See also Felin, T. and Holweg, M. (2024), “Theory Is All You Need: AI, Human Cognition, and Decision Making”, 24 February.
See Brynjolfsson, E. et al. (2017), “Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics”, NBER Working Paper Series, No 24001, November.

 
 
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Today, the European Commission announced the sixth investment package under the EU’s Economic and Investment Plan for the Western Balkans that is expected to mobilise €1.2 billion in investments. This package will support eight new flagship investments in water supply and sanitation, wastewater treatment and rail transport, as well as innovation and green transformation in small and medium enterprises. The investments will be rolled out in close cooperation with the Western Balkan partners and international financial institutions.
President of the European Commission, Ursula von der Leyen, said: “Our €30 billion Investment Plan for the Western Balkans is delivering, with this new €1.2 billion package. It strengthens regional connections with quality infrastructure and brings us closer together, which is our ultimate goal. Our Western Balkan partners are building their European future. These investments, along with necessary reforms and access to our Single Market, will prepare our partners’ economies to join our Union.”
The €1.2 billion in investment package includes €300 million in EU grants from the Instrument for Pre-accession Assistance (IPA III), additional bilateral contributions from EU Member States and Norway, loans from international financing institutions and contributions from the economies of the Western Balkans. The package was endorsed by the Operational Board of the Western Balkans Investment Framework (WBIF) during the 1-2 July meeting. The new flagship investments fall under three priorities of the Economic and Investment Plan:

Environment and climate: Reconstruction and rehabilitation of water supply and sanitation infrastructure in Montenegro and Bosnia and Herzegovina.

Sustainable transport: advancing on Corridor X rail infrastructure, with the high-speed Belgrade – Velika Plana connection enabling a faster flow of passengers and freight in the region.

Support to the business sector: launch of a new facility for innovation and green transformation of enterprises in the region.

Background
As part of the Global Gateway, the EU’s Economic and Investment Plan for the Western Balkans (2021-27) aims to spur long-term recovery, accelerate a green and digital transition, and foster regional cooperation and convergence with the EU. Adopted by the European Commission in October 2020, the Plan mobilises up to €30 billion in investments, including €9 billion in EU grants through IPA III, over the seven-year period. Of this amount, €5 billion has been committed through the WBIF.
So far, the EU has approved programmes set to mobilise up to €17.5 billion in investments under the Economic and Investment Plan, including €5.4 billion in EU grants.
The WBIF is a joint financial platform launched 15 years ago, bringing together the European Commission, financial organisations, EU Member States and Norway, to enhance cooperation in public and private sector investments. It supports the region’s socio-economic development and contributes to the European integration of the Western Balkans. Alongside being the main financial vehicle for implementing the EU’s Economic and Investment Plan, the WBIF will also play an important role in the implementation of the new €6 billion Reform and Growth Facility for the Western Balkans, which has the double objective to boost socio-economic convergence with the EU and accelerate the accession process. The WBIF will channel €3 billion of grants and loans under the Facility to support priority investments in transport, energy, digital and human capital areas.
For more information, please contact:

Ana PISONERO-HERNANDEZ, Spokesperson

Piotr CICHOCKI, Press Officer

 
 
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The complex structuring and multi-step distribution chains involved in certain securitisation structures in the run-up to the 2008 global financial crisis (GFC) generated misaligned incentives between the originator of a securitisation and its investors. This led to weakened lending standards, while amplifying a rapid and largely undetected build-up of leverage and maturity mismatches. A number of regulatory reforms have since been introduced to improve transparency, address conflicts of interest, strengthen the regulatory capital treatment for banks’ securitisation exposures by improving risk sensitivity and reducing cliff effects, and align incentives associated with securitisation.
The objectives of the evaluation are twofold:

to assess the extent to which risk retention and higher bank prudential requirements implemented to date have achieved their financial stability objectives and
to examine broader effects (positive or negative) of these reforms on the functioning and structure of the securitisation markets and on the financing of the real economy.

To achieve this, the evaluation examines the mechanisms through which these reforms are expected to operate and associated metrics to assess securitisation market resilience.
The analysis thus far suggests that the reforms have contributed to the resilience of the securitisation market without strong evidence of material negative side-effects on financing to the economy, though the findings are preliminary and need to be confirmed by additional work. Looking ahead, the FSB will continue its analysis of the effects of these reforms and expects to publish the final report at the end of 2024.
The FSB invites comments on this consultation report and the questions set out below. Responses should be submitted via this secure online form by 2 September 2024.
 
Responses should be submitted via this secure online form by 2 September 2024. For questions, please contact the FSB (fsb@fsb.org).
 
 
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Dear Charles,
dear Alexander,
I want to start by thanking you, dear Alexander, for an exceptionally successful Presidency of the Council. You have managed to reach political agreement on over 45 files spanning all of our major political priorities. It goes from the European Green Deal to digitalisation, from industry and the economy to enlargement. I think two proposals were exemplary, that is the Net-Zero Industry Act and the new Economic Governance Framework.
But you also steered the first ever agreement on a mid-term revision of the Multiannual Financial Framework. This enabled, because it included, the EUR 50 billion Facility for Ukraine. You delivered another highlight that was the adoption of the Pact on Migration and Asylum, certainly one of the most challenging sets of legislation this College put forward. I also want to emphasise that it is not only legislative files that you managed, but you also chaired the Industry Summit in Antwerp, the Social Partners Summit in Val Duchesse and the Pillar of Social Rights in La Hulpe.
During your Presidency, in fact just this week, we also adopted the 14th sanctions package against Russia. And also this week, we adopted new sanctions on Belarus that will align them with our Russian sanctions regime. This is a very strong sign of our continued determination to deprive Russia of the means to continue its war of aggression against Ukraine. And of course, there was a big event: On Tuesday, we launched the accession negotiations for Ukraine and Moldova. Today, in a further step, we have paid almost EUR 1.9 billion in pre-financing under the Ukraine Facility. So it was very fitting and good that we could discuss these developments in person with President Zelenskyy at the start of our meeting. I was particularly honoured to sign the security commitments between the European Union and Ukraine, on behalf of the European Commission. We also presented to the Leaders the G7 initiative, to provide Ukraine with loans of roughly USD 50 billion. Now we will work with our Member States, with the G7 partners and Ukraine, to put the necessary legislation in place. We are looking forward to providing Ukraine with the relevant funds before the end of the year.
We had many other topics, as you heard from my colleague, Charles Michel. I want to have a second look at the security and defence element that was discussed. We all know, and it was said already this evening, that we are facing unprecedented and growing security threats. High-intensity war has returned to our continent, and Russia is an aggressive and disruptive power. It has rapidly transitioned to a war economy. Just one figure: It will spend over 7% of its GDP on defence this year. So as we agreed in the Versailles Agenda, again last March, Europe as a whole, needs to step up on defence. Let me give you three figures that show the necessity: If you look at the combined EU spending on defence from 2019 to 2021, so in 3 years, it increased by 20%. In that same time frame, China’s defence spending increased by almost 600%, and Russia’s defence spending by almost 300%. And this is even before Russia massively increased its defence spending over the last two years.
We have taken various sources, from the Strategic Compass to the European Defence Industrial Strategy, to identify the defence capabilities that are required. We have on top, in addition, some Member States that have recently called for a European air defence shield, and others that called for the reinforcement of the Union’s eastern land border. And if we take all of this into account and based on non-classified sources, we estimate that additional defence investments of around EUR 500 billion are needed over the next decade. There are some sources in the MFF, close to EUR 11 billion, that could be topped up with another EUR 11 billion off budget by the European Peace Facility. We have created already a toolbox for defence. Just a reminder: We have the European Defence Fund, the Connecting Europe Facility, or the European Defence Industry Programme, that has, for example the Eurodrone as flagship. But overall, more is needed, and therefore, as the Council had asked for, there are options if you come to the defence spending possibilities. The first is: additional national contribution. The second option is: agreement on new own resources for the European level. The proposal for that is on the table of the Council. Then, of course, there is a second question, whether Leaders call immediately on those resources, or whether they use the borrowing power of the Union budget upfront and call on these resources later. None of these options are easy. All of them have to be looked at with the political will to decide what to do together, but they have to be looked at seriously.
Finally, a brief look at the Strategic Agenda. I welcome its adoption, because it prepares the next institutional cycle and sets the political priorities by the 27 EU Leaders for the next years. So this provides an important input for the Commission to develop the next Political Guidelines that I would have to put on the table when it comes to the vote in the Parliament. This Strategic Agenda starts with a very sober assessment of the new geopolitical realities. I will skip them because we have already discussed them tonight. The response to these challenges, are very clearly defined in the Strategic Agenda: scaling up the European defence, from the spending to interoperability, but also a very clear look at the climate threats that are out there, so the goal to become the first climate-neutral continent whilst strengthening the competitiveness of our social market economies – there is a very strong focus on the topic of competitiveness –, and of course, the endorsement of implementing our twin green and digital transitions and scaling up Europe’s manufacturing capacity for clean technologies. So there is a wide range of topics in the Strategic Agenda, an important input for the Political Guidelines for the Commission.
For more information, please contact:

Eric MAMER, Chief Spokesperson

Arianna PODESTA, Deputy Chief Spokesperson

 
 
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The Council today decided to impose restrictive measures against two individuals and four entities responsible for actions undermining or threatening the territorial integrity, sovereignty and independence of Ukraine.
The Council is listing Dmitry Beloglazov, and his company LLC Titul. Dimitry Beloglazov is responsible for setting up a complex circumvention scheme together with Oleg Deripaska, who is already subject to EU restrictive measures. His company LLC Titul created a subsidiary called Joint Stock Company Iliadis to acquire Oleg Deripaska’s share in the International LLC Rasperia Trading Limited. Rasperia owns €28,5 million shares in another European company, STRABAG SE, the assets of which have been frozen as a result of EU restrictive measures. Through this mechanism, Deripaska managed to sell his Rasperia frozen assets, and received an equivalent economic benefit. In view of this circumvention scheme, JSC Iliadis and Rasperia were also sanctioned by the Council.
Today’s new listings also include PJSC TransContainer and its General Director Mikhail Kontserev. PJSC TransContainer is a Russian transportation company and Russia’s largest railway container operator. Its revenues increased throughout 2023 also thanks to the flow of Belarusian cargoes, and the company’s participation in illegal weapon trade schemes with the Democratic People’s Republic of Korea (DPRK) in support of the Russian Government.
Altogether, EU restrictive measures in respect of actions undermining or threatening the territorial integrity, sovereignty and independence of Ukraine now apply to over 2 200 individuals and entities. Those designated today are subject to an asset freeze and EU citizens and companies are forbidden from making funds available to them. Natural persons are additionally subject to a travel ban, which prevents them from entering or transiting through EU territories.
The relevant legal acts have been published in the Official Journal of the European Union.
On 24 June 2024, the Council adopted a 14th package of economic and individual restrictive measures targeting high-value sectors of the Russian economy, making it ever more difficult to circumvent EU sanctions, and adding 116 individuals and entities to the list of those responsible for actions undermining or threatening the territorial integrity, sovereignty and independence of Ukraine.
In its conclusions of 27 June 2024, the European Council reconfirmed the European Union’s continued support for Ukraine’s independence, sovereignty and territorial integrity within its internationally recognised borders and the EU’s unwavering commitment to providing continued political, financial, economic, humanitarian, military and diplomatic support to Ukraine and its people for as long as it takes and as intensely as needed.
Russia must not prevail.
The European Council also welcomed the adoption of the 14th package of sanctions against Russia and the agreement on further restrictive measures against Belarus. It called for the full and effective enforcement of sanctions as well as for further measures to counter their circumvention, including through third countries. The European Union remains ready to further limit Russia’s ability to wage war and urges all countries not to provide any material or other support for Russia’s war of aggression.
For more information, please contact:

Maria Daniela Lenzu, Press Officer

 
 
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Blog post by Othman Bouabdallah, Ettore Dorrucci, Lucia Hoendervangers and Carolin Nerlich | Europe needs trillions of euros to manage climate change, become digital and defend itself. How can EU and national policymakers support these projects? This Blog post discusses the options in times of low growth and high public debt levels.
The European Union (EU) needs to move forward with the green transformation, the digitalisation of the economy and the strengthening of its military defence. This requires a lot more investment than in the past: using official estimates by the European Commission and NATO, we calculate additional €5.4 trillion for the period 2025-2031 (Figure 1)[1].
 
Massive investment needs…
Both private capital and governments will need to fill the financing gap. The lion’s share has to be borne by private firms, investors and households. But a substantial share – around €1.3 trillion euro, in our calculations – will have to be funded via public sources.[2]
Let’s focus on the public channel. Just under €400 billion can be expected to come from existing EU resources.[3] So, we are talking about a gap between available and needed public funding of more than €900 billion for the whole Union in the period 2025-2031, to be financed at national and EU level. While these are rough estimates, they provide an order of magnitude of the challenges ahead. To account for the high degree of uncertainty, we apply a range of +/- 20%. On this basis, the public funding gap would correspond to between 0.6% and 1% of EU GDP per year.
Figure 1
Additional cumulated EU private and public investment needs and its funding: Estimates for green-digital transitions and defence spending

(2025-2031; by funding entities and in billions of euro)

Sources: European Commission, 2023 Strategic Foresight Report. Sustainability and people’s wellbeing at the heart of Europe’s Open Strategic Autonomy; European Defence Fund (EDF); NATO; ECB staff own calculations.
Notes: For the assumptions used in this chart, see footnotes 1 to 3. The chart shows the additional investment which is the difference between total investment needs and historical averages. The funding of the cumulative additional investment needs is decomposed into what is expected to be financed by the private vs. the public sector.. Planned EU investment funding initiatives include the EU budget, the Recovery and Resilience Facility (RRF) of Next Generation EU (NGEU) until end-2026, the European Investment Bank and other EU funds, as defined in footnote 3.

Footing this bill will not be easy, especially for high-debt countries with large structural deficits.[4] This is illustrated in Figure 2, which focuses on the euro area where countries’ fiscal positions vary considerably. Government debt-to-GDP ratios ranged between 20% and 160% in 2023. On top of that, some of the high-debt countries suffer from large underlying fiscal deficits, captured in our chart by their government budget balances net of interest expenditure and adjusted for the business cycle (“structural primary balances”).
Figure 2
Government debt ratios and structural primary balances in the euro area countries (2023)

(in percent of GDP, percent of GNI* for IE and percent of GNI for LU)

Sources: European Commission, European Economic Forecast, Spring 2024, ECB calculations
Note: The horizontal line identifies the threshold – 60% of GDP – set in the EU fiscal governance to identify countries with high deficits. Ratios for Ireland and Luxembourg are expressed in percentage of GNI* and percentage of GNI respectively, which are considered better proxies of underlying economic activity in these countries.

Some help to the national governments comes from the new EU fiscal governance[5] adopted at the end of April this year, which lays more emphasis than in the past on combining fiscal consolidation needs with growth-enhancing investments and reforms. Compared with the previous governance, this may ease part of the national funding pressure for strategic investments. Two new rules may prove helpful:
First, during the budgetary adjustment phase that will start in 2025, the European Commission will give member states the option to take more time – up to seven years until 2031 – to implement their fiscal consolidation plans and put their debt trajectories on plausibly declining paths. This implies that governments would have to meet lower fiscal adjustment requirements each year. But it would be allowed only if the Commission finds that countries are implementing credible investment and reform plans. We estimate that this novel framework may create fiscal space for public investment in the EU for up to €700 billion over the period 2025-2031[6].
Second, once the fiscal adjustment phase is over, member states are allowed to keep structural public deficits at 1.5% of GDP, which are higher than in the past[7]. This would in principle give up to one percentage point more fiscal space for investment than under the previous rules.
This breathing space helps, but will it be enough?
There are reasons to believe that it may not be the case. The additional investment will foster potential growth, and therefore mitigate the risks to debt sustainability,[8] but only with a time lag. Implementation bottlenecks will emerge, such as limited administrative capacity in the public sector. Also, the estimates of the investment needs presented above are rather conservative; they do not consider other strategic investment required in areas such as health or education. For some countries, the fiscal space made available by the new fiscal rules may still not be sufficient. And even the countries which start from a comfortable fiscal position and can afford spending more than others should be concerned. No country, not even the richest, can stop climate change on its own. Strategic investments pursue shared goals and, as such, they also require common responses[9].
 
…call for a coordinated approach in Europe
Our back-of-the-envelope calculations lay bare the tension between investment needs and fiscal space that Europe’s policymakers are facing.
There is no silver bullet one can count on. More investment-friendly EU fiscal rules go in the right direction, but disproportionate reliance on public investment at national level would not only encounter limits in terms of administrative capacity and risk crowding out private investment; it would also not be affordable from a public finance perspective. As Figure 1 suggests, the bulk of funding of strategic investment will need to come from private sources, and even this will not be enough if not supported and integrated by EU-level initiatives.
This calls for a coordinated, holistic, and multi-pronged approach to both private and public investment in Europe, involving a wide range of initiatives at both the Union and the national level. Without claiming to be exhaustive, in Figure 3 we provide examples of complementary policy avenues – some already existing but in need of being enhanced, others more innovative.
These initiatives would reinforce each other.
To mobilise private funding, a fully-fledged European capital market would need to be accompanied by a strengthened single market, better framework conditions for doing business, more investment-friendly corporate taxation, as well as more specific initiatives, such as those listed in the first column of the table.
In high-debt countries, growth and debt performances will depend on how successfully the governments implement the Recovery and Resilience Plans of Next Generation EU. Whether countries are able to comply with fiscal adjustment requirements in an investment-friendly way will be crucial here. This includes improving the quality of public finance by cutting less productive expenditure.
The public funding gap of €900 billion, however, cannot be closed without additional involvement of the Union. The next EU budget (2028-2034) could act as a catalyst by financing investment in genuine EU public goods,[10] ranging from joint procurement in defence to energy grids, from high power computers to EU cloud expansion. Budget reprioritisation, new own resources, and joint borrowing[11] are all avenues to consider.
Europe’s massive strategic investment needs and the policy options to address them can be identified, as we suggest in this blog. What matters now is that these options find their way into the political space of the Union and its member countries. And that a genuine public debate starts, so that Europeans collectively can make informed choices about their future.

The “additional investment needs” in the climate, digital and defence spheres are defined as difference between total investment needs and historical averages. Calculations are built on the following main assumptions: (i) we extrapolate the Commission’s estimates for green and digital investment to 2031 to account for the recent economic governance reform, which envisages the adoption by member states of fiscal-structural plans lasting up to 7 years (2025-2031); (ii) green investment needs include estimated investment under the Fit-for-55 package, RePowerEU (excluding fossil fuel investments), Net-Zero Industry Act and environment protection; (iii) defence expenditure refers to the NATO commitment to reach 2% of GDP, with this commitment being here assumed to be taken by all EU Member States, including non-NATO members; (iv) historical averages refer for green investment to the period 2011-2020, for digital investment to the period 2014-2020, and for military expenditure in the EU to 2022.
We account for different shares of public sector investment across categories (green, digital, defence) and sub-components of the green transition. We then apply a weighted share for each category, based on historical averages.
This includes (i) the EU budget, which is assumed to be extended beyond 2027 and to remain constant, (ii) the Recovery and Resilience Facility (until end-2026) of Next Generation EU (NGEU), (iv) the European Investment Bank, and (v) other EU funding initiatives such as InvestEU.
For a detailed analysis of sovereign debt in the EU, see European Commission (2023), Debt Sustainability Monitor 2023.
On 30 April 2024, the new EU fiscal legislation was published in the EU Official Journal, consisting of: (1) Regulation (EU) 2024/1263 of the European Parliament and of the Council of 29 April 2024 on the effective coordination of economic policies and on multilateral budgetary surveillance and repealing Council Regulation (EC) No 1466/97 ; (2) Regulation (EU) 2024/1264 ; and (3) Directive – 2024/1265.
Starting from the latest forecast of the European Commission for the 2024 budget balance, we calculate, for each euro area member state and for each year, the difference between the budget balance under the 4-year adjustment plan (higher) and the budget balance under the 7-year plan (lower). Cumulating the estimated fiscal room for manoeuvre over the period 2025-31 and across Member States, we obtain a figure of around €700 billion.
Under the previous fiscal framework, the medium-term objective was setting the structural public deficit threshold at 0.5% of GDP for countries with debt above 60% of GDP, and 1% of GDP for countries with debt significantly below 60% of GDP.
Robust economic growth is a key parameter for fiscal sustainability and provides a buffer against negative shocks. In the euro area, a drop by one percentage point per year of potential output growth would be more than sufficient to put the public debt ratio on unfavourable dynamics.
See M. Draghi (2023), “The Next Flight of the Bumblebee: The Path to Common Fiscal Policy in the Eurozone”, NBER, 15th Annual Feldstein Lecture.
A public good can be defined as a good from which everybody benefits and where the benefits for one individual do not reduce the benefits for others. It is argued that investments in the green/digital transition and defence require a response not only at national but also at European level, as underinvestment in some EU countries would produce negative externalities on the other countries and ultimately affect all EU citizens. The case for strategic investment in European public goods is made, for instance, in F. Panetta (2022), ‘Investing in Europe’s future: The case for a rethink’, speech delivered at the Istituto per gli Studi di Politica Internazionale (ISPI). For a discussion of European vs. national public goods, see e.g. G. Claeys and A. Steinbach (2024), “A conceptual framework for the identification and governance of European public goods“, Bruegel Working Paper (30 May).
Joint issuance would also enhance the chances of establishing a genuine European safe asset, which will be important for further developing the capital markets union.

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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The Commission is setting up a new Climate City Capital Hub, an international finance resource to further support cities participating in the EU Mission on Climate-Neutral and Smart Cities.
Thanks to the new hub, cities that have already received the EU Cities Mission Label will be able to:

Access financial advice in cooperation with advisory services of the European Investment Bank (EIB);
Structure their financial needs so they understand various ways of funding projects, including pooling of projects; and
Introduce projects to a range of capital providers, including lenders and investors from the public and private sectors (such as philanthropic and corporate capital, as well as innovative financing like crowdfunding and sustainability-linked bonds), and support the process to deal closure.

Complementing EIB services, the Climate City Capital Hub will be created with the support of both the EU Mission on Climate-Neutral and Smart Cities Mission and the EU Mission on Adaptation to Climate Change. Its particular focus will be on engagement with private capital. For cities that signed both the Charter of the Mission on Climate Adaptation and have received the EU Cities Mission Label, the services will cover both mitigation and adaptation projects, taking a holistic approach to tackle climate change.
The hub will be run by the Commission’s Cities Mission implementation platform, which is currently managed by the project NetZeroCities. The Commission announced its creation at the 2024 Cities Mission conference held in Valencia on 25 and 26 June.
In addition, the EIB has earmarked a lending envelope of €2 billion dedicated to cities with the Cities Mission Label to support their plans to invest in energy, efficient buildings, district heating systems, renewable energy, sustainable mobility, urban renewal and regeneration, water and social infrastructure. It reinforces the EIB support to labelled cities and adds a dedicated finance facility to advisory services.
Next Steps
So far, 33 cities have been awarded the Label of the EU Mission for Climate-Neutral and Smart Cities: 10 in October 2023 and 23 in March 2024. The label is an important milestone in the cities’ work. It acknowledges successful development of Climate City Contracts, which outline the cities’ overall vision for climate neutrality and contain an action plan as well as an investment plan. Cities co-create their Climate City Contracts with local stakeholders including the private sector and citizens. From the 33 Investment Plans that have been submitted so far, approximately €114.1 billion have been budgeted for climate actions – on average €3.6 billion per city. Currently, the Commission is reviewing another 23 Climate City Contracts.
In parallel, the EU Mission for Climate-Neutral and Smart Cities has also collected more than 200 solutions that will help cities on their way to climate neutrality. The solutions cover from A – “Advanced Renovation Support” to Z – “Zero Emission Buses” and can be found in the Knowledge Repository.
Background
Cities account for more than 70% of global CO₂ emissions and consume over 65% of the world’s energy. Urban action is crucial for climate mitigation and can contribute significantly to accelerating the efforts to achieve the legally binding commitment to achieve climate-neutrality in the EU as a whole by 2050, as well as to the EU’s target of reducing greenhouse gas emissions by 55% by 2030 and more generally delivering the European Green Deal. The EU Cities Mission aims to help European cities become climate-neutral, offering cleaner air, safer transport and less congestion and noise to their citizens.
In April 2022, 100 cities in the EU and 12 cities in countries associated to Horizon Europe, the EU research and innovation programme, were selected to participate in the Mission. They are testing innovative cross-sectoral approaches including for citizen engagement, stakeholder management and internal governance to accelerate their path to climate neutrality. This makes them experimentation and innovation hubs to enable all European cities to follow suit by 2050.
For more information, please contact:

Thomas Regnier, Spokesperson

Roberta Verbanac, Press Officer

 
 
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Biennial report assesses progress towards euro adoption in Bulgaria, Czech Republic, Hungary, Poland, Romania and Sweden
Inflation above reference value seen as key economic obstacle in central and eastern European countries under review
Legislation in five of six countries under review not fully compatible with legal requirements for euro adoption
Economic activity expected to strengthen in 2024, but outlook clouded by geopolitical uncertainty

Limited progress has been made by non-euro area Member States of the European Union (EU) on economic convergence with the euro area since 2022, according to the 2024 Convergence Report of the European Central Bank (ECB). This is mainly due to challenging economic conditions.
Over the past two years, the countries under review have been hit by the fallout from Russia’s invasion of Ukraine, which led to a significant weakening of economic activity and soaring inflation. Countries with a history of higher energy dependence on and stronger trade links with Russia were the most affected. Looking ahead, economic activity is expected to strengthen in all of the countries under review, but geopolitical tensions and risks are clouding economic prospects.
As regards the price stability criterion, five of the countries under review – Bulgaria, the Czech Republic, Hungary, Poland and Romania – recorded average inflation rates well above the reference value of 3.3%, while inflation was slightly above the reference value in Sweden (Chart 1). The reference value is based on the three best-performing Member States over the past 12 months, i.e. Denmark (1.1%), Belgium (1.9%) and the Netherlands (2.5%), taking their average inflation rates over the past 12 months and adding 1½ percentage points. One outlier, Finland, was excluded from this calculation.
Chart 1
HICP inflation
(average annual percentage changes)Source: Eurostat.
Chart 2
General government surplus (+) or deficit (-)
(percentages of GDP)Source: Eurostat.
The fiscal deficit in 2023 improved compared with its 2021 level in four of the countries covered in this report, owing to the post-pandemic economic recovery and the phasing-out of fiscal support measures. However, this improvement was in part curbed by the economic impact of Russia’s war against Ukraine, including weaker economic activity, and fiscal policy measures taken in response to high energy prices. In 2023 the Czech Republic, Hungary, Poland and Romania exceeded the deficit reference value of 3% of GDP (Chart 2). The government debt-to-GDP ratio in 2023 was below the reference value of 60% in all of the countries under review except Hungary. In 2024 and 2025 the budget balance is expected to continue to exceed the reference value in Hungary, Poland and Romania.
Romania continues to be subject to an excessive deficit procedure, which was opened in 2020. On 19 June 2024 the European Commission found that Romania had not taken effective action to end its excessive deficit. The Commission recently also concluded that Hungary and Poland did not fulfil the government deficit criterion under the Stability and Growth Pact. The Commission will recommend to the EU Council to open excessive deficit procedures for these countries.
As regards the exchange rate criterion, only the Bulgarian lev is participating in the exchange rate mechanism (ERM II). Bulgaria joined ERM II with its existing currency board in place as a unilateral commitment in July 2020. This agreement on participation in ERM II was based on a number of policy commitments made by the Bulgarian authorities. Bulgaria is currently working towards completing these policy commitments, including by strengthening its anti-money laundering framework.
With regard to the convergence of long-term interest rates, three of the six countries under review (Poland, Romania and Hungary) recorded long-term interest rates above the reference value of 4.8%.
The strength of public and economic institutions is an important factor in the sustainability of convergence over time. With the exception of Sweden, indicators published by international organisations suggest that the quality of institutions and governance in the countries under review remains weaker than elsewhere in the EU.
As for the compatibility of national legislation with the Treaties and the Statute of the ESCB and of the ECB, five of the six countries under review were not fully compatible with the requirements for the adoption of the euro. With regard to Bulgaria’s legislation, the report concludes that its national legislation is consistent with the Treaty and the Statute, subject to conditions and interpretations set out in the relevant country assessment.
For media queries, please contact Eszter Miltényi-Torstensson, tel.: +49 171 769 5305.
Notes

The European Commission’s Convergence Report
The ECB’s Convergence Report reviews the economic and legal convergence of non-euro area EU Member States with a derogation every two years or at the request of a specific country. It assesses the degree of sustainable economic convergence with the euro area, whether the national legislation is compatible with the EU legal framework, and whether the statutory requirements are fulfilled for the respective national central banks. Given its “opt-out” clause, Denmark is not included in the assessment unless it so requests.
The cut‑off date for the statistics included in this Convergence Report was 19 June 2024. The reference period for both the price stability criterion and the long-term interest rate criterion is from June 2023 to May 2024. For exchange rates, the reference period is from 20 June 2022 to 19 June 2024. Historical data on fiscal positions cover the period up to 2023. Forecasts are based on the European Commission’s Spring 2024 Economic Forecast and the most recent convergence programmes of the countries concerned, as well as other information relevant to a forward-looking examination of the sustainability of convergence.

 
 
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More climate-friendly production of foods, clean fuels and chemicals in Europe is receiving a boost from the EU-Catalyst partnership, a joint initiative by the European Investment Bank (EIB), the European Commission and Breakthrough Energy Catalyst.
Energy equipment manufacturer Rondo Energy is receiving €75 million through grants and venture debt (subject to the satisfaction of funding conditions), so it can deploy in Europe a technology for turning intermittent renewable electricity into the continuous, high-temperature heat and power required by food, clean-fuel and chemical producers.
Rondo will use the funding to expand its European presence and build projects delivering low-cost, continuous, high-pressure, zero-carbon steam and power as a service.  This involves the construction of first-of-a-kind utility-scale long duration energy storage units with power-to-heat technology. The solution is based on a traditional heating of specially designed bricks by electric wires. The charging is done from dedicated renewable generation source or from the grid during the off-peak hours or hours of excess renewable production. The discharge ensures stable and reliable 24/7 heat supply in the form of steam, heated gas or cogeneration. This technology allows for decarbonization of industrial heat supply and can contribute to increased flexibility of the power system, therefore ensuring security of electricity supply, and for increasing the grid resiliency to intermittent power generation from renewable energy sources.
“The green transition requires massive investment for innovative technologies to replace industrial processes based on fossil fuels,” said EIB Vice-President Thomas Östros. “With today’s announcement, we are writing the next chapter of the EU-Catalyst partnership. We are delighted to support Rondo’s first-of-a-kind energy storage units. As the climate bank, we aim to finance many more net-zero technologies that will provide clean and affordable energy to power our industry and homes, while strengthening Europe’s competitiveness.”
“This project funding is a strong addition to our long-term relationship with Breakthrough, and puts Rondo firmly on the path to helping to eliminate the green premium for industrial heat electrification and to becoming a fully bankable technology which can be deployed at scale,“ said Eric Trusiewicz, CEO of Rondo Energy. “The grant from Breakthrough Energy Catalyst and the loan from the European Investment Bank together underpin Rondo’s development throughout Europe, where we see very strong tailwinds to the adoption of our technology.”
Commission Executive Vice-President for the European Green Deal, Maroš Šefčovič, said: “It is vital that Europe’s future green economy is built here. The EU-Catalyst Partnership is therefore an excellent blueprint for public-private support for large-scale green tech projects based in Europe. Thanks to the support provided by the Innovation Fund and Horizon Europe, this can help us step up funding levels, as the average investment needed for the EU to reach its 2030 climate target – to reduce greenhouse gas emissions – is equivalent to some 700 billion dollars per year. We also need to frontload this financing, and ease access to it to ensure a level playing field for smaller companies. These are make-it-or break-it conditions for the green transition.”
“Rondo’s technology offers industry a unique opportunity to decarbonize with inexpensive renewable electricity,” said Mario Fernandez, Head of Breakthrough Energy Catalyst. “Rondo’s deployment is crucial at a time when European manufacturers are urgently looking for ways to eliminate their dependence on natural gas. We’re proud to support these important projects across Europe and to work with such great partners in Rondo, the European Investment Bank, and the European Commission who bring the commitment and vision to commercialize this critical technology.”
The EU-Catalyst partnership creates a blueprint for public-private support for clean tech innovative technologies. It aims to accelerate the deployment of innovative low-carbon technologies while also reducing their green premiums, that is, bringing their costs to a level competitive with fossil fuels. EU funding for the partnership comes from EU’s research and innovation programme Horizon Europe and the Innovation Fund within the framework of InvestEU, according to the established governance procedures. Breakthrough Energy Catalyst mobilises equivalent private capital and philanthropic grants to fund the selected projects.
Background information
The EIB is the long-term lending institution of the European Union owned by its Member States. It is active in more than 160 countries and makes long-term finance available for sound investment in order to contribute towards EU policy goals.
The EIB, as implementing partner of the Commission under InvestEU, has been tasked to deploy for the benefit of this partnership up to €420 million, made available from both Horizon Europe, which has already committed €200 million, and the Innovation Fund, which has committed €220 million. The EU-Catalyst Partnership does not exclude potential additional contributions from EU Member States or other private partners that decide to further support the projects. Interested projects can apply for support through the Breakthrough Energy Catalyst website.
Horizon Europe is the EU’s key funding programme for research and innovation with a budget of €93.5 billion (2021-2027). The Innovation Fund is one of the world’s largest funding programmes for the deployment of net-zero and innovative technologies and sources its funds from the selling of EU Emissions Trading System allowances (estimated to amount to €40 billion from 2020-2030).
Breakthrough Energy is a global network of climate leaders committed to accelerating the world’s journey to a clean energy future. The organization funds breakthrough technologies, advocates for climate-smart policies, and mobilizes partners around the world to take effective action, accelerating progress at every stage.
Breakthrough Energy Catalyst is a novel platform that funds and invests in first-of-a-kind commercial projects for emerging climate technologies. By investing in these opportunities, Catalyst seeks to accelerate the adoption of these technologies worldwide and reduce their costs.
Rondo is purpose-built for industrial facilities: its Heat Batteries are constructed from proven, durable materials and are designed for seamless integration with existing industrial equipment and processes. Whether deployed as a drop-in replacement for retiring fossil-fueled heating equipment or as a resilient complement to existing systems, Rondo requires no disruptive changes to customers’ operations. Rondo currently operates the world’s highest temperature, highest efficiency commercial energy storage system, at Calgren Renewable Fuels in Pixley, California.
 
 
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By Giovanni Melina | Artificial intelligence can increase productivity, boost economic growth, and lift incomes. However, it could also wipe out millions of jobs and widen inequality.
Our research has already shown how AI is poised to reshape the global economy. It could endanger 33 percent of jobs in advanced economies, 24 percent in emerging economies, and 18 percent in low-income countries. But, on the brighter side, it also brings enormous potential to enhance the productivity of existing jobs for which AI can be a complementary tool and to create new jobs and even new industries.
Most emerging market economies and low-income countries have smaller shares of high-skilled jobs than advanced economies, and so will likely be less affected and face fewer immediate disruptions from AI. At the same time, many of these countries lack the infrastructure or skilled workforces needed to harness AI’s benefits, which could worsen inequality among nations.
As the Chart of the Week shows, wealthier economies tend to be better equipped for AI adoption than low-income countries. The data draw from the IMF’s new AI Preparedness Index Dashboard for 174 economies, based on their readiness in four areas: digital infrastructure, human capital and labor market policies, innovation and economic integration, and regulation.
Measuring preparedness is challenging, partly because the institutional requirements for economy-wide integration of AI are still uncertain. As the dashboard shows, different countries are at different stages of readiness in leveraging the potential benefits of AI and managing the risks.
Under most scenarios, AI will likely worsen overall inequality, a troubling trend that policymakers can work to prevent. To this end, the dashboard is a response to significant interest from our stakeholders in accessing the index. It is a resource for policymakers, researchers, and the public to better assess the AI preparedness and, importantly, to identify the actions and design the policies needed to help ensure that the rapid gains of AI can benefit all.
AI can also complement worker skills, enhancing productivity and expanding opportunities. In advanced economies, for example, some 30 percent of jobs could benefit from AI integration. Workers who can harness the technology may see pay gains or greater productivity—while those who can’t, may fall behind. Younger workers may find it easier to exploit opportunities, while older workers could struggle to adapt.
For policymakers, those in advanced economies should expand social safety nets, invest in training workers, and prioritize AI innovation and integration. Coordinating with one another globally, these countries also should strengthen regulation to protect people from potential risks and abuses and build trust in AI. The policy priority for emerging market and developing economies should be to lay a strong foundation by investing in digital infrastructure and digital training for workers.

For more on how artificial intelligence affects economies, see the December issue of Finance & Development, the IMF’s quarterly magazine, and the recent Analyze This! video.

 
Full post can be found here
 
 
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