A digitális euro
Az eurorendszerben zajlanak a fizikai készpénz kiegészítőjének szánt digitális euro esetleges kibocsátásának előkészületei.
ELŐADÁS
2026. március 6.
A monetáris politika irányítása kínálati sokkok idején
Ahogy a kínálati oldali sokkok felszaporodtak, a monetáris politikának határozottan az árstabilitásra kell irányulnia – mondta Isabel Schnabel igazgatósági tag. Jó a helyzetünk, de résen kell lennünk, tekintettel a geopolitikai és makrogazdasági tényezőkből eredő felfelé irányuló inflációs kockázatokra.
Az előadás szövege
PUBLIKÁCIÓ
2026. március 5.
A digitális euro kísérleti projekt
Az EKB és az euroövezeti nemzeti központi bankok jövő évi kezdettel 12-havi kísérleti projektet indítanak a digitális euróval. Valós életbeli fizetési szituációk segítségével mérjük fel, hogyan működhetnek a digitális euro alapismérvei a gyakorlatban.
Bővebben a projektről
PODCAST
2026. március 3.
Vegye kezébe a pénzügyi jövőjét!
Podcastunk új néven jelentkezik: köszöntjük az Euro Matters hallgatóit! In Conversation sorozatunk első epizódjában Christine Lagarde elnök arról beszélget a podcast háziasszonyával Stefania Secolával, hogy miként szerezte meg a pénzügyi tudását, és miért fontosak a pénzzel kapcsolatos ismeretek, különösen a nők számára.
Az epizód meghallgatása- 5 March 2026
- MONETARY POLICY ACCOUNTRelated
- 5 February 2026
- MONETARY POLICY DECISIONEnglishOTHER LANGUAGES (23) +
- 4 March 2026
- MFI INTEREST RATE STATISTICS
- 3 March 2026
- WEEKLY FINANCIAL STATEMENTEnglishOTHER LANGUAGES (22) +Annexes
- 3 March 2026
- WEEKLY FINANCIAL STATEMENT - COMMENTARY
- 2 March 2026
- PRESS RELEASEPresident Lagarde launches EuroSteps Walking Challenge at event promoting women’s financial literacyEnglishOTHER LANGUAGES (18) +
- 27 February 2026
- GOVERNING COUNCIL DECISIONS - OTHER DECISIONSEnglishOTHER LANGUAGES (23) +
- 6 March 2026
- Speech by Isabel Schnabel, Member of the Executive Board of the ECB, at the 2026 US Monetary Policy Forum
- 6 March 2026
- Slides by Piero Cipollone, Member of the Executive Board of the ECB, at European Banking Federation Executive Committee Meeting
- 5 March 2026
- 2026 Annual Global Risk Lecture by Christine Lagarde, President of the ECB, held in honour of Robert Mundell and organised by Johns Hopkins University in Bologna, Italy
- 26 February 2026
- Speech by Christine Lagarde, President of the ECB, at the Hearing of the Committee on Economic and Monetary Affairs of the European ParliamentAnnexes
- 26 February 2026
- 23 February 2026
- Acceptance speech by Christine Lagarde, President of the ECB, for the 2026 Paul A. Volcker Lifetime Achievement Award at the 42nd Annual NABE Economic Policy Conference in Washington DC, United States
- 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
- 21 February 2026
- Interview with Christine Lagarde, President of the ECB, conducted by Emma Tucker, Chelsey Dulaney, Greg Ip, Nick Timiraos, Daniel Colarusso and Amol Sharma on 19 February 2026
- 19 February 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 Laura Noonan and Nick Comfort on 17 February 2026
- 10 February 2026
- Interview with Luis de Guindos, Vice-President of the ECB, conducted by Marta Vilar on 6 February 2026
- 4 March 2026
- Artificial intelligence is everywhere, and the workplace is no exception. But will it empower workers, or is it set to replace them? This blog post looks at the impact of AI use and investment on firms’ current and future hiring and firing decisions.Details
- JEL Code
- O33 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights→Technological Change: Choices and Consequences, Diffusion Processes
J20 : Labor and Demographic Economics→Demand and Supply of Labor→General
- 27 February 2026
- Economic forecasts rarely hit the mark as reality is full of surprises. Thankfully we can learn from the patterns of forecast errors. They shed light on the types of shocks that are shaping the economy beyond what forecasts anticipated.Details
- JEL Code
- E50 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→General
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
- 25 February 2026
- Tariff hikes are putting European companies under strain at a time when productivity growth is already sluggish. Short-term business sentiment is not the only thing at stake. Tariffs could also dampen business dynamism, a key channel for innovation and long-term growth.Details
- JEL Code
- E50 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→General
F40 : International Economics→Macroeconomic Aspects of International Trade and Finance→General
Related- 11 February 2025
- 19 February 2026
- Climate change has become an important factor for fiscal policy, debt sustainability and sovereign risk. This blog post shows how climate shocks can push up bond yields, especially for highly indebted and developing countries.Details
- JEL Code
- G10 : Financial Economics→General Financial Markets→General
Q54 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Climate, Natural Disasters, Global Warming
E60 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→General
F34 : International Economics→International Finance→International Lending and Debt Problems
- 16 February 2026
- Artificial intelligence has the potential to make economic research more effective. But how exactly? This ECB Blog post gives a concrete example. We look at the use of AI to streamline the processes and analytical capabilities of our Corporate Telephone Survey.Details
- JEL Code
- O33 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights→Technological Change: Choices and Consequences, Diffusion Processes
C00 : Mathematical and Quantitative Methods→General→General
- 6 March 2026
- LETTERS TO MEPS
- 5 March 2026
- WORKING PAPER SERIES - No. 3200Details
- Abstract
- We introduce a novel methodology, ”parametric tilting,” for incorporating external information into econometric model-based density forecasts. Unlike traditional entropic tilting, which can generate unrealistic or unstable distributions under certain conditions, parametric tilting ensures more reliable and numerically stable results. Our approach leverages the flexibility of the skew-T distribution, which captures key moments of macroeconomic time series, and minimizes the Kullback-Leibler divergence between the target and model-based distributions. This method overcomes limitations of entropic tilting, such as multimodal or degenerate distributions, providing a robust alternative for policymakers and researchers aiming to integrate external views into probabilistic forecasting frameworks.
- JEL Code
- C14 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Semiparametric and Nonparametric Methods: General
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
- 3 March 2026
- WORKING PAPER SERIES - No. 3199Details
- Abstract
- This paper studies the effects of stablecoin adoption—crypto-assets designed to maintain a stable value relative to a reference asset—on bank intermediation and the transmission of monetary policy. Using evidence from the rapid expansion of stablecoins combined with confidential granular data on euro area banks and their individual borrowers, we document three main findings. First, stablecoin adoption induces a deposit-substitution mechanism, whereby funds shift from retail bank deposits to digital assets. This reallocation increases banks’ reliance on wholesale funding and can ultimately constrain their intermediation capacity. Second, we show that stablecoins alter the passthrough of policy rates to bank funding costs and lending conditions and potentially weaken the predictability of policy actions. These effects are nonlinear and depend critically on the scale of stablecoin adoption, their design features, and their regulatory treatment. Third, we document a potential risk associated with the growing prevalence of foreign-currency-denominated stablecoins. Their diffusion is likely to increase banks’ reliance on foreign-currency wholesale funding. We show that banks with greater exposure to this source of funding exhibit a weaker loan-supply response to domestic monetary policy shocks, indicating a weakening of monetary policy transmission and a potential erosion of monetary sovereignty.
- JEL Code
- E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
- 3 March 2026
- AMI-SECO REPORT
- 2 March 2026
- OTHER PUBLICATION
- 2 March 2026
- SURVEY OF MONETARY ANALYSTS
- 27 February 2026
- WORKING PAPER SERIES - No. 3198Details
- Abstract
- We investigate whether satellite observations of nitrogen dioxide (NO₂) – a short-lived pollutant primarily emitted by fossil fuel combustion – can improve the forecasting of oil demand. After retrieving, cleaning, and aggregating daily satellite data, we integrate NO₂ into a range of forecasting models. Across a panel of advanced and emerging economies, we find that including NO₂ significantly enhances nowcasting accuracy relative to benchmark models based on autoregressive terms and traditional predictors such as industrial activity, prices, weather, and vehicle registrations. Accuracy gains are particularly strong during crisis episodes but remain present in more stable times. Non-linear models, especially neural networks, yield the largest improvements, highlighting the non-linear link between energy demand and pollution. By offering a timely, globally consistent, and freely available proxy, satellite-based NO₂ data provide a valuable new tool for real-time monitoring of oil dema
- JEL Code
- C51 : Mathematical and Quantitative Methods→Econometric Modeling→Model Construction and Estimation
C81 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Microeconomic Data, Data Access
E23 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Production
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
- 27 February 2026
- WORKING PAPER SERIES - No. 3197Details
- Abstract
- We study the distributional consequences of the recent inflationary surge and the subsequent monetary policy response in the euro area. Using an estimated two-asset Heterogeneous Agent New Keynesian model with an overlapping generations structure, we analyze the macroeconomic shocks driving inflation between 2021 and 2022. We find that these shocks generated substantial redistribution from young and poor households toward older and wealthier ones. By keeping interest rates unchanged until mid-2022, monetary policy largely offset these distributional effects. A policy response based solely on a standard Taylor rule would have failed to mitigate the redistribution.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
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
D31 : Microeconomics→Distribution→Personal Income, Wealth, and Their Distributions
- 26 February 2026
- ANNUAL CONSOLIDATED BALANCE SHEET OF THE EUROSYSTEMEnglishOTHER LANGUAGES (23) +Related
- 26 February 2026
- ANNUAL ACCOUNTSEnglishOTHER LANGUAGES (23) +
- 26 February 2026
- ANNUAL ACCOUNTSEnglishOTHER LANGUAGES (23) +Related
- 26 February 2026
- ANNUAL CONSOLIDATED BALANCE SHEET OF THE EUROSYSTEMEnglishOTHER LANGUAGES (23) +
- 26 February 2026
- WORKING PAPER SERIES - No. 3196Details
- Abstract
- Using granular security-level data from bond funds domiciled in the US and the euro area, we identify a market-based risk-taking channel of monetary policy transmission via the credit-risk and the maturity structure of bond funds’ portfolios. We measure credit risk at the fund level as the weighted average credit rating of the fund’s bond holdings. We find that accommodative monetary policies by the Fed and the ECB are associated with increased risk in bond funds’ portfolios. Interestingly, risk-taking is more pronounced for funds with longer-term holdings relative to short-term ones and unconventional monetary policy exerts stronger market-based risk-taking effects than interest rate policy. Finally, we find that Fed’s monetary policy has a stronger impact on funds’ risk-taking behaviour than the ECB’s, highlighting the dominant role of US monetary policy in global financial markets.
- JEL Code
- E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
G15 : Financial Economics→General Financial Markets→International Financial Markets
G20 : Financial Economics→Financial Institutions and Services→General - Network
- Challenges for Monetary Policy Transmission in a Changing World Network (ChaMP)
- 25 February 2026
- WORKING PAPER SERIES - No. 3195Details
- Abstract
- When default losses elevate borrowing costs, expanding credit cannot stabilize the economy because default rates feedback to lending rates through bank balance sheets. Asset management companies (AMCs) break this loop by purchasing nonperforming loans at their long-run recovery values, thereby fixing the effective default rate that banks face. Government purchases of performing loans expand credit but leave this feedback intact. In a model calibrated to the eurozone, the AMC reduces quarterly default rates by 0.8 percentage points, lowers lending rates by 1.6 percentage points, and raises welfare by 0.2%. Government purchases crowd out bank deposits, contracting credit; default rates rise by 1.8 percentage points, lending rates increase by 1.2 percentage points, and welfare falls by 0.3%.
- JEL Code
- E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
G01 : Financial Economics→General→Financial Crises
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
- 25 February 2026
- WORKING PAPER SERIES - No. 3194Details
- Abstract
- We document a novel transmission channel of monetary policy through the homeowners insurance market. On average, contractionary monetary policy shocks result in higher homeowners insurance prices. Using granular data on insurers’ balance sheets, we show that this effect is driven by the interaction of financial frictions and the interest rate sensitivity of investment portfolios. Specifically, rate hikes reduce the market value of insurers’ assets, tightening insurers’ balance sheet constraints and increasing their shadow cost of capital. These frictions in insurance supply amplify the effects of monetary policy on real estate and mortgage markets by making housing less affordable. We find that monetary policy shocks have a stronger impact on home prices and mortgage applications when local insurers are more sensitive to interest rates. This channel is particularly pronounced in areas where households face high climate risk exposure. Our findings highlight the role of insurance markets in amplifying macroeconomic shocks and the interconnections between homeowners insurance, residential real estate, and mortgage lending.
- JEL Code
- E5 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G22 : Financial Economics→Financial Institutions and Services→Insurance, Insurance Companies, Actuarial Studies
G5 : Financial Economics
R3 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Real Estate Markets, Spatial Production Analysis, and Firm Location - Network
- Challenges for Monetary Policy Transmission in a Changing World Network (ChaMP)
- 24 February 2026
- WORKING PAPER SERIES - No. 3193Details
- Abstract
- Financial Conditions Indices (FCIs) are a widely used tool for assessing the broader monetary policy stance beyond the central bank’s direct control. This paper presents a novel vector autoregressive (VAR) model that includes key macroeconomic variables and maps financial variables into a single index, named Macro-Finance FCI. The VAR coefficients and the FCI weights are estimated jointly in one step, ensuring a model-consistent microfinance feedback. The model-implied long-run mean of the index provides a neutral benchmark to which financial conditions converge when inflation is at target and output is at potential. For the euro area, the proposed FCI incorporates nine asset prices – including risk-free rates, sovereign spreads, risk assets, and the exchange rate – and assigns a dominant role to nominal interest rates. It outperforms existing indices in out-of-sample forecasts of inflation and output. A structural identification of supply, demand, and financial shocks indicates that financial conditions require up to one year to transmit to the real economy and almost up to two years to inflation.
- JEL Code
- C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
- 24 February 2026
- WORKING PAPER SERIES - No. 3192Details
- Abstract
- This paper presents a novel model comparison to examine the challenges posed by changes in carbon-intensive energy prices for monetary policy. The employed environmental monetary models have a detailed multi-sector structure. The comparison assesses the effects of both a temporary and a permanent energy price increase with a particular focus on the euro area and the United States. Temporary and permanent price shocks are both inflationary. However, the inflationary impact of the permanent shock depends on the underlying model assumptions and monetary policy response. The analysis also establishes that these models share large commonalities in their quantitative and qualitative results, while also pointing out cross-country differences.
- JEL Code
- C54 : Mathematical and Quantitative Methods→Econometric Modeling→Quantitative Policy Modeling
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
H23 : Public Economics→Taxation, Subsidies, and Revenue→Externalities, Redistributive Effects, Environmental Taxes and Subsidies
Q43 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→Energy and the Macroeconomy
- 23 February 2026
- WORKING PAPER SERIES - No. 3191Details
- Abstract
- Sequence-space models are becoming increasingly popular in macroeconomics, especially in the heterogeneous-agent literature. However, the econometric toolkit for users of these models remains less developed than that available for traditional state-space methods. This note introduces an algorithm for efficiently filtering unobserved shocks in linear sequence-space models. The proposed filter solves a least-squares optimization problem in closed form and returns the expectation of unobserved shocks conditional on observed data. It handles heteroskedasticity, missing observations, measurement error, and non- Gaussian shock distributions. To illustrate its properties, I apply it to data simulated from a medium-scale heterogeneous-agent New Keynesian model and show that it accurately recovers the underlying structural shocks.
- JEL Code
- C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
E27 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Forecasting and Simulation: Models and Applications
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
- 23 February 2026
- WORKING PAPER SERIES - No. 3190Details
- Abstract
- Using information from the ECB’s Bank Lending Survey, we examine how the implementation of borrower-based macroprudential measures (BBMs) between 2009-Q1 and 2023-Q3 affected mortgage lending standards in a sample of 15 euro area countries. We find that banks generally tightened credit standards around the implementation of BBMs, with the strongest effect occurring contemporaneously. Such tightening of credit standards is observed for different types of BBMs, including limits on loan-to-value or debt-service-to-income ratios and maturities. We also find mild evidence that legally binding measures imply a stronger tightening of credit standards than measures in the form of non-binding recommendations. Finally, this tightening is more pronounced in cases where mortgage loan growth or real estate price growth is high, consistent with BBMs effectively smoothing the credit cycle.
- 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
G51 : Financial Economics
- 23 February 2026
- RESEARCH BULLETIN - No. 140Details
- Abstract
- Using regional data for 11 euro area countries from 1999 to 2023, instead of country-level data, we find that inflation still responds to economic slack, but this relationship is more modest and largely shaped by inflation expectations. This implies that traditional demand-side central bank policies may have limited direct effects on inflation, highlighting that anchoring expectations is essential for effective monetary policy transmission.
- JEL Code
- E24 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Employment, Unemployment, Wages, Intergenerational Income Distribution, Aggregate Human Capital
E30 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→General
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
- 20 February 2026
- LETTERS TO MEPS
- 19 February 2026
- ECONOMIC BULLETIN
Kamatlábak
| Betéti rendelkezésre állás | 2,00 % |
| Irányadó refinanszírozási műveletek (rögzített kamatláb) | 2,15 % |
| Aktív oldali rendelkezésre állás | 2,40 % |
Inflációs ráta
Bővebben az inflációrólÁrfolyam
| USD | US dollar | 1.1561 | |
| JPY | Japanese yen | 182.57 | |
| GBP | Pound sterling | 0.86693 | |
| CHF | Swiss franc | 0.9045 |
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