Digitālais euro
Eurosistēma veic sagatavošanās darbus potenciālai digitālā euro emisijai. Digitālais euro papildinātu fizisko skaidro naudu.
RUNA
06.05.2026.
Eiropas noturība pret jaunu enerģijas šoku
Jaunais enerģijas šoks ir ekonomiskās noturības pārbaude, atzīmēja Valdes loceklis Pjēro Čipollone. Paaugstinātas nenoteiktības apstākļos nepieciešams rūpīgs vērtējums, lai saglabātu cenu stabilitāti un vienlaikus investētu ilgtspējā, nostiprinot Eiropas spēju stāties pretī nākotnes šokiem.
Lasiet Pjēro Čipollones runu
NOTIKUMS
06.05.2026.
Aicinām uz tikšanos ar mūsu darbiniekiem Eiropas dienas pasākumā
Svētdien, 2026. gada 9. maijā mēs būsim Eiropadomē Briselē un Römerberg tirgus laukumā Frankfurtē, lai atzīmētu Eiropas dienu un Eiropas Savienības dibināšanu. Aicinām tikties ar mums un uzzināt, kā mēs strādājam ikviena Eiropas iedzīvotāja labā.
Uzziniet par Eiropas dienas pasākumiem
ECB BLOGS
06.05.2026.
Digitālās bankas un monetārā politika
Digitalizācija maina banku monetārās politikas transmisiju. Salīdzinājumā ar tradicionālajām bankām digitālās bankas ātrāk pielāgo noguldījumu cenas atbilstoši politikas pārmaiņām, taču lēnāk aktualizē aizdevumu cenas.
Lasiet ECB blogu- 6 May 2026
- MFI INTEREST RATE STATISTICS
- 6 May 2026
- PRESS RELEASE
- 5 May 2026
- WEEKLY FINANCIAL STATEMENTEnglishOTHER LANGUAGES (22) +Annexes
- 5 May 2026
- WEEKLY FINANCIAL STATEMENT - COMMENTARY
- 4 May 2026
- GOVERNING COUNCIL DECISIONS - OTHER DECISIONSEnglishOTHER LANGUAGES (23) +
- 4 May 2026
- PRESS RELEASERelated
- 4 May 2026
- SURVEY OF PROFESSIONAL FORECASTERS
- 6 May 2026
- Keynote speech by Piero Cipollone, Member of the Executive Board of the ECB, at the 2026 Sustainable Development FestivalAnnexes
- 6 May 2026
- 5 May 2026
- Keynote speech by Philip R. Lane, Member of the Executive Board of the ECB, at the Climate, Nature and Monetary Policy Conference jointly organised by the ECB, the Centre for Economic Transition Expertise and the Frankfurt School of Finance and Management
- 5 May 2026
- Introductory remarks by Christine Lagarde, President of the ECB, at the Climate, Nature and Monetary Policy Conference organised by the ECB, Frankfurt School and CETEX
- 4 May 2026
- Introductory remarks by Luis de Guindos, Vice-President of the ECB, at the ECON Committee of the European ParliamentRelated
- 4 May 2026
- Speech by Piero Cipollone, Member of the Executive Board of the ECB, at a workshop on digital assets and monetary policy transmission organised by the European Central Bank, Banca d’Italia, the Euro Area Business Cycle Network and the Centre for Economic Policy Research
- 3 May 2026
- Interview with Luis de Guindos, Vice-President of the ECB, conducted by Amanda Mars on 30 April 2026
- 22 April 2026
- Interview with Frank Elderson, Member of the Executive Board of the ECB and Vice-Chair of the Supervisory Board of the ECB, conducted by Eva Smal on 15 April 2026
- 23 March 2026
- Interview with Luis de Guindos, Vice-President of the ECB, conducted by Carlos Segovia on 20 March 2026
- 8 March 2026
- Interview with Christine Lagarde, President of the ECB, conducted by Benedetta Poletti on 12 February 2026
- 3 March 2026
- Interview with Philip R. Lane, Member of the Executive Board of the ECB, conducted by Olaf Storbeck on 26 February 2026
- 6 May 2026
- Digitalisation is reshaping how banks pass on monetary policy. Compared with their branch‑based peers, digital banks are faster at adjusting deposit pricing for policy changes, but slower at updating their loan pricing.Details
- JEL Code
- E50 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→General
G20 : Financial Economics→Financial Institutions and Services→General
- 21 April 2026
- Artificial intelligence (AI) can help track inflation risks in real time. A new ECB model based on machine learning informs experts how likely it is that inflation will be much higher or much lower than they expect.Details
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
- 13 April 2026
- During the latest tightening episode, interest rate hikes were especially effective. This ECB Blog finds a strong policy transmission to inflation during 2022 and 2023, a forceful response to supply-driven shocks and a low “sacrifice ratio”.Details
- JEL Code
- E50 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→General
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
- 9 April 2026
- Many Bulgarians feared large price increases when the euro replaced the lev. However, preliminary evidence shows that the changeover in Bulgaria has so far had a limited impact on consumer prices and on perceptions of inflation.Details
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E42 : Macroeconomics and Monetary Economics→Money and Interest Rates→Monetary Systems, Standards, Regimes, Government and the Monetary System, Payment Systems
Related - 7 April 2026
- Europe’s energy dependence increasingly complicates the task of maintaining price stability. Meeting the continent’s clean‑energy targets would weaken the link between volatile global markets and domestic prices. Crucially, the tools to make this transition are already within reach.Details
- JEL Code
- E50 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→General
Q40 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→General
Q50 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→General
- 6 May 2026
- WORKING PAPER SERIES - No. 3225Details
- Abstract
- Does artificial intelligence (AI) pose a threat to financial stability? We study AI investor behavior, specifically Q-learning and large language model (LLM) investors, in a mutual fund redemption problem with economic and strategic uncertainty. Different AI architectures generate systematically different outcomes. Q-learning investors coordinate well but under default risk exhibit excessive redemption that amplifies fragility. LLM investors internalize equilibrium structure but display belief heterogeneity, weakening coordination and predictability. Our findings show that AI architecture is a first-order determinant of financial stability.
- JEL Code
- G01 : Financial Economics→General→Financial Crises
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
C63 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Computational Techniques, Simulation Modeling
- 6 May 2026
- WORKING PAPER SERIES - No. 3224Details
- Abstract
- We study how physical climate risk shapes bank lending activity and credit quality by combining high-resolution Copernicus flood geospatial maps with loan-level AnaCredit data. We exploit four major European floods (2021–2024) in a spatial regression discontinuity design comparing firms located just inside versus just outside flood boundaries (within 300–500 meters). We find that immediately after floods there is an increase by about 3.5 to 5% in lending, driven by liquidity demand, followed by a contraction of similar magnitude in the subsequent quarter. Interest rates follow a similar pattern, while default rates rise persistently by around 0.7 percentage points. Exploiting multiple lending relationships and firm–time fixed effects, we show that demand factors dominate: banks with greater exposure to affected firms do not systematically tighten credit supply. Nonetheless, relationship banks extend roughly 10 percentage points more credit to affected firms while imposing tighter collateral requirements, consistent with risk-sharing rather than unconditional support. Sectoral composition and pre-existing firm risk are the primary axes of heterogeneity in the immediate response. The findings shed light on how physical climate shocks propagate through credit markets and inform financial stability analysis.
- JEL Code
- Q54 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Climate, Natural Disasters, Global Warming
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill
C21 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Cross-Sectional Models, Spatial Models, Treatment Effect Models, Quantile Regressions
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
- 5 May 2026
- WORKING PAPER SERIES - No. 3223Details
- Abstract
- Using who-to-whom data for the last quarter of 2024, I build networks of financial interconnections in the euro area countries. After representing them in chord diagrams, I consider centrality metrics and find that banks dominate, with four exceptions: Cyprus, Ireland, Luxembourg and Malta. In these countries, other financial institutions and investment funds are at the core, with limited links to domestic sectors and strong ones with the rest of the world. A comparison across countries reveals substantial homogeneity between networks in the sixteen euro area countries and large differences with Cyprus, Ireland, Luxembourg and Malta. For each country, two communities are identified, one focused on the real economy and including banks, and the second comprising other financial intermediaries and the rest of the world. The consistent mapping of sectoral linkages and the accompanying descriptive analysis can be useful for policymakers and may also serve as platform for further analytical work.
- JEL Code
- D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
G10 : Financial Economics→General Financial Markets→General
G20 : Financial Economics→Financial Institutions and Services→General
G51 : Financial Economics
- 5 May 2026
- WORKING PAPER SERIES - No. 3222Details
- Abstract
- Investment in cybersecurity in an interconnected banking system has public-good proper- ties: positive externalities can generate systemic underinvestment. Using confidential supervi- sory data from the European Central Bank, we first identify “laggard” European banks that underinvest relative to their cyber-risk profiles, and then examine how supervisory scrutiny af- fects their incentives to invest. We exploit the 2024 ECB Cyber Resilience Stress Test (CyRST) as a quasi-natural experiment. In a difference-in-differences design, we find that following the CyRST announcement, laggard banks increased cybersecurity investment by about 80% rel- ative to their peers. The response is stronger among laggards subject to high-intensity su- pervisory oversight, consistent with scrutiny exerting a disciplining effect. Overall, the results suggest that targeted supervisory scrutiny may help mitigate underinvestment incentives and strengthen banks’ operational risk management.
- JEL Code
- G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill
L86 : Industrial Organization→Industry Studies: Services→Information and Internet Services, Computer Software
K23 : Law and Economics→Regulation and Business Law→Regulated Industries and Administrative Law
- 5 May 2026
- OTHER PUBLICATION
- 4 May 2026
- ANNUAL REPORTEnglishOTHER LANGUAGES (22) +Related
- 4 May 2026
- FEEDBACK ON THE INPUT PROVIDED BY THE EUROPEAN PARLIAMENT AS PART OF ITS RESOLUTION ON THE ECB’S ANNUAL REPORTEnglishOTHER LANGUAGES (21) +Related
- 4 May 2026
- WORKING PAPER SERIES - No. 3221Details
- Abstract
- This paper provides novel evidence on how income inequality shapes the heterogeneity of US monetary policy spillovers to GDP across foreign economies. Using state-dependent local projections and exploiting variation in disposable income inequality across 87 countries over 1966-2020, we show that household heterogeneity influences how foreign GDP responds to a US monetary tightening. GDP contracts up to one and a half times more when inequality is above average. However, while higher inequality amplifies negative spillovers in advanced economies, it mitigates them in emerging markets. To rationalise this finding, we use a three-country open economy Two-Agent New Keynesian (TANK) model, which suggests this divergence is driven by differences in participation in international financial markets. Households in emerging markets face greater barriers to international investment, limiting their ability to re-balance portfolios towards higher-return foreign bonds after the shock.
- JEL Code
- D31 : Microeconomics→Distribution→Personal Income, Wealth, and Their Distributions
E21 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Consumption, Saving, Wealth
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
F42 : International Economics→Macroeconomic Aspects of International Trade and Finance→International Policy Coordination and Transmission
- 4 May 2026
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 3, 2026Details
- Abstract
- This box summarises the main findings from recent contacts between ECB staff and representatives of 67 leading non-financial companies operating in the euro area. According to these exchanges, which mainly took place between 23 March and 1 April 2026, there had been good business momentum in the first quarter, with few signs as yet of demand reacting to the latest war in the Middle East. The war was, however, already pushing some costs and prices higher, particularly for fuel, logistics, chemicals, plastics, paper and packaging. Concerns centred on the impact that the conflict was having on consumer confidence and the risk that a protracted conflict could induce global supply chain disruption due to shortages of oil and oil-based products, pushing prices higher and dampening activity later in the year.
- JEL Code
- E2 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy
E3 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles
L2 : Industrial Organization→Firm Objectives, Organization, and Behavior
- 4 May 2026
- SURVEY OF PROFESSIONAL FORECASTERSAnnexes
- 4 May 2026
- SURVEY OF PROFESSIONAL FORECASTERS
Related- 4 May 2026
- PRESS RELEASE
- 4 May 2026
- SURVEY OF MONETARY ANALYSTS - AGGREGATE RESULTS
- 28 April 2026
- OTHER PUBLICATIONAnnexes
- 28 April 2026
- OTHER PUBLICATION
- 28 April 2026
- OTHER PUBLICATIONLast updated on 28 April 2026
- 28 April 2026
- EURO AREA BANK LENDING SURVEYAnnexes
- 28 April 2026
- EURO AREA BANK LENDING SURVEY - ANNEX
- 27 April 2026
- SURVEY ON THE ACCESS TO FINANCE OF ENTERPRISES IN THE EURO AREAAnnexes
- 27 April 2026
- SAFE QUESTIONNAIRE
- 27 April 2026
- OCCASIONAL PAPER SERIES - No. 387Details
- Abstract
- This paper describes and evaluates the European Union (EU) banking sector capital framework, focusing on how the international standards set by the Basel Committee on Banking Supervision have been implemented within the EU. Using granular supervisory data for significant institutions under the Single Supervisory Mechanism (SSM), we quantify the capital impact of EU-specific regulatory choices, supervisory measures and macroprudential policies. We show that most EU capital requirements stem from Basel standards, which encompass both prescriptive “Pillar 1” components and elements that are expected to be designed and calibrated at the jurisdictional level. The paper describes the evolution of capital ratios and requirements since the inception of the SSM and discusses the relationship between changes in capital levels and indicators of banking sector performance. To provide a comparative perspective, a model-based counterfactual exercise compares capital requirements of EU banks with those that would arise if EU banks were subject to the main prudential regulations that currently apply in the United States, which vary depending on the size of the bank. The results show that for the largest EU banks, the current US rules would entail stricter requirements, whereas mid-sized EU banks would be subject to less stringent requirements. Our findings show that EU capital requirements are broadly comparable to those in other jurisdictions and are largely in line with international standards. When assessing broader indicators of bank performance, we highlight the importance of considering not only private costs and benefits, but also intended effects and broader societal objectives. [...]
- JEL Code
- G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
F36 : International Economics→International Finance→Financial Aspects of Economic Integration
- 22 April 2026
- RESEARCH BULLETIN - No. 142Details
- Abstract
- We model central bank communication when there is disagreement between the markets and the central bank about the central bank’s confidence surrounding its point forecast. We show that such a disagreement leads the markets to misunderstand a given announcement, so that the markets either over- or underreact to the bank’s announcement. Communicating only a part of the central bank’s information set is a way to correct the markets’ over- or underreaction. The model also produces predictions for how the central bank’s statement drafting process can take the disagreement about uncertainty into account, which we find support for in data on Federal Reserve System communication.
- JEL Code
- E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
C49 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→Other
- 21 April 2026
- OCCASIONAL PAPER SERIES - No. 386Details
- Abstract
- This paper studies the effectiveness of risk management, one of the two channels identified by the Network for Greening the Financial System (NGFS, 2024) as those through which the financial system contributes to physical risk adaptation in the European Union (EU). We assess the efficacy of Level 3 prudential regulations in encouraging banks to include physical risk adaptation in their risk management and client engagement strategies. Our analysis adopts a broad perspective, encompassing not only prudential risk management but also, and in our view more importantly, prudential transparency regulation, given the positive leverage that stakeholders can exert to incentivise adaptation efforts. Our findings suggest that banks should consistently integrate physical risk adaptation into their stress tests, transition plans and Pillar III disclosures. Transition plans must address physical hazards, exposure and vulnerability and must set adaptation targets. Adaptation measures should be treated as risk mitigants reflected in losses given default (LGDs), with the severity and consistency of those losses being reflected in transition plans and stress tests.
- JEL Code
- K23 : Law and Economics→Regulation and Business Law→Regulated Industries and Administrative Law
O52 : Economic Development, Technological Change, and Growth→Economywide Country Studies→Europe
Q54 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Climate, Natural Disasters, Global Warming
Q58 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Government Policy
- 16 April 2026
- WORKING PAPER SERIES - No. 3220Details
- Abstract
- We analyze how bank lending to non-bank financial institutions (NBFIs) affects credit supply to the real economy. Using granular supervisory and loan-level data, we document rapid growth in bank lending to NBFIs relative to lending to non-financial firms. This growth is driven primarily by reverse repos to NBFIs that invest in securities, e.g., investment funds, rather than by loans to NBFIs that extend credit to firms, e.g., private credit funds. We show that the expansion in bank–NBFI lending reflects rising NBFI borrowing demand to fund government securities, which stems in part from the tapering of QE and the expansion of government bond supply in the Euro area, US, UK, and Japan. Importantly, loans to NBFIs disproportionately crowd out loans to non-financial firms rather than securities on bank balance sheets, which ultimately contracts credit supply to the real economy. A model rationalizes our empirical findings and quantifies the aggregate crowding-out effect. Taken together, our results imply that the rise of bank lending to NBFIs represents a narrowing of bank business models and a contraction in bank credit intermediation.
- JEL Code
- G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
G24 : Financial Economics→Financial Institutions and Services→Investment Banking, Venture Capital, Brokerage, Ratings and Ratings Agencies
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
- 14 April 2026
- WORKING PAPER SERIES - No. 3219Details
- Abstract
- We propose a new approach to estimate selection-corrected quantiles of the gender wage gap. Our method employs instrumental variables that explain variation in the latent variable but, conditional on the latent process, do not directly affect selection. We provide semiparametric identification of the quantile parameters without imposing parametric restrictions on the selection probability, derive the asymptotic distribution of the proposed estimator based on constrained selection probability weighting, and demonstrate how the approach applies to the Roy model of labor supply. Using German administrative data, we analyze the distribution of the gender gap in full-time earnings. We find pronounced positive selection among women at the lower end, especially those with less education, which widens the gender gap in this segment, and strong positive selection among highly educated men at the top, which narrows the gender wage gap at upper quantiles.
- JEL Code
- C14 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Semiparametric and Nonparametric Methods: General
C21 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Cross-Sectional Models, Spatial Models, Treatment Effect Models, Quantile Regressions
J16 : Labor and Demographic Economics→Demographic Economics→Economics of Gender, Non-labor Discrimination
J21 : Labor and Demographic Economics→Demand and Supply of Labor→Labor Force and Employment, Size, and Structure
J31 : Labor and Demographic Economics→Wages, Compensation, and Labor Costs→Wage Level and Structure, Wage Differentials
Procentu likmes
| Noguldījumu iespēja uz nakti | 2.00 % |
| Galvenās refinansēšanas operācijas (ar fiksētu procentu likmi) | 2.15 % |
| Aizdevumu iespēja uz nakti | 2.40 % |
Inflācija
Vairāk par inflācijuValūtu kursi
| USD | US dollar | 1.1762 | |
| JPY | Japanese yen | 183.74 | |
| GBP | Pound sterling | 0.86370 | |
| CHF | Swiss franc | 0.9165 |
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