Digitalni euro
Eurosistem se pripravlja na morebitno izdajo digitalnega eura, ki bo dopolnjeval fizično gotovino.
INTERVJU
18. september 2026
Deregulacija ni rešitev
Poslovanje bank je dražje in manj učinkovito zaradi fragmentacije in ne regulacije, je dejal podpredsednik Boris Vujčić v intervjuju za Reuters. Z dokončanjem bančne unije ter unije prihrankov in naložb bi nastal integriran trg, na katerem bi banke lahko rasle.
Intervju s podpredsednikom
GOVOR
14. september 2026
Nova doba kapitala: rast, suverenost in UI
Umetna inteligenca (UI) je projekt, ki bi lahko popeljal evropske kapitalske trge naprej, tako da prihranke usmerjajo tja, kjer so potrebni, pravi predsednica Christine Lagarde. Potreben je kapital v merilu, ki ga lahko zagotovijo le trgi, usoda Evrope pa je na kocki.
Predsedničin govor
PUBLIKACIJA
15. september 2026
Iščemo trgovce za pilotni projekt digitalnega eura
Eurosistem išče trgovce, ki se ukvarjajo s spletno in mobilno trgovino, da se pridružijo pilotnemu projektu v okviru digitalnega eura. Izbrani kandidati bodo v ECB in nacionalnih centralnih bankah testirali beta različico digitalnega eura in nam tako pomagali izboljšati njegovo zasnovo in funkcionalnosti.
Razpis za prijavo interesa- 18 September 2026
- PRESS RELEASE
- 18 September 2026
- BALANCE OF PAYMENTS (MONTHLY)
- 16 September 2026
- PRESS RELEASE
- 15 September 2026
- WEEKLY FINANCIAL STATEMENTEnglishOTHER LANGUAGES (22) +Annexes
- 15 September 2026
- WEEKLY FINANCIAL STATEMENT - COMMENTARY
- 10 September 2026
- MONETARY POLICY DECISIONEnglishOTHER LANGUAGES (23) +Related
- 10 September 2026
- COMBINED MONETARY POLICY DECISIONS AND STATEMENT
- 14 September 2026
- Speech by Christine Lagarde, President of the ECB, at “Hofburg im Dialog – Economy, Europe, Resilience” in Vienna, Austria
- 14 September 2026
- Keynote speech by Piero Cipollone, Member of the Executive Board of the ECB, at the House of the EuroRelated
- 23 July 2026
- EnglishOTHER LANGUAGES (23) +
- 14 September 2026
- Slides by Isabel Schnabel, Member of the Executive Board of the European Central Bank, at the 2nd Federal Ministry for Economic Affairs and Energy (BMWE) Symposium on European Competitiveness in Berlin, Germany
- 12 September 2026
- Speech by Christine Lagarde, President of the ECB, at Fête de la Pomme in Épreville-en-Lieuvin, France
- 11 September 2026
- Slides by Philip R. Lane, Member of the Executive Board of the ECB, at Richard Cantillon Lecture at 49th DEW Annual Economic Policy Conference 2026 in Wexford, Ireland
- 18 September 2026
- Interview with Boris Vujčić, Vice-President of the ECB, conducted by Francesco Canepa on 16 September 2026
- 12 September 2026
- Interview with Christine Lagarde, President of the ECB, conducted by Jean-Christophe Lalay and Maxime Mainguet on 12 September 2026
- 24 August 2026
- Interview with Piero Cipollone, Member of the Executive Board of the ECB, conducted by Lorenzo Torrisi on 10 August 2026
- 15 July 2026
- Interview with Piero Cipollone, Member of the Executive Board of the ECB, conducted by Élisabeth Montaufray-Bureau on 10 July 2026
- 13 July 2026
- Interview with Piero Cipollone, Member of the Executive Board of the ECB, conducted by Ricardo Jesus Silva on 29 June 2026
- 15 September 2026
- Around 80% of euro area households do not own stocks or any other market-based financial instruments, unlike their counterparts in the United States. This blog post examines the barriers that keep many Europeans from investing and explores ways to broaden capital market participation.Details
- JEL Code
- G11 : Financial Economics→General Financial Markets→Portfolio Choice, Investment Decisions
G51 : Financial Economics
- 2 September 2026
- Synthetic securitisation can free up bank capital. But does that mean banks lend more to firms? This ECB Blog post explores the effects of loan securitisation. We find that banks that issue synthetic securitisations lend marginally more, but also tend to pay more dividends.Details
- JEL Code
- G00 : Financial Economics→General→General
- 1 September 2026
- The drivers of the recent rise in inflation are different from those of the pandemic-era surge. This time the energy supply shock dominates, while demand and public policy stimulus have minor roles. These differences are key to explaining why monetary policy responses differ.Details
- JEL Code
- E30 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→General
- 31 August 2026
- US tech giants are increasingly tapping the euro area bond market to fund their investments. The ECB Blog investigates the consequences for this market and the potential for these developments to reshape it.Details
- JEL Code
- O16 : Economic Development, Technological Change, and Growth→Economic Development→Financial Markets, Saving and Capital Investment, Corporate Finance and Governance
- 26 August 2026
- Use of artificial intelligence at work has doubled over the last two years and people report significant time-savings. But an ECB survey shows that perceived productivity gains vary widely and there are still barriers preventing many from adopting this new technology.Details
- JEL Code
- J01 : Labor and Demographic Economics→General→Labor Economics: General
O33 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights→Technological Change: Choices and Consequences, Diffusion Processes
- 18 September 2026
- WORKING PAPER SERIES - No. 3286Details
- Abstract
- Using exogenous variation generated by the creation of the Single Supervisory Mechanism (SSM) in the euro area, we find that relative to firms borrowing from banks subject to national supervision, firms borrowing from banks subject to supranational supervision reduce their share of intangible assets. This effect does not pre-date the supervisory reform and it does not obtain in non-SSM jurisdictions. The reallocation of investment away from intangible assets is stronger for small and young firms and appears to be driven by a short-term reduction in lending and a persistent increase in collateral standards.
- JEL Code
- D25 : Microeconomics→Production and Organizations
F30 : International Economics→International Finance→General
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
- 18 September 2026
- WORKING PAPER SERIES - No. 3285Details
- Abstract
- This paper examines how bank capital conditions the effect of competition on credit risk in lending markets, informing the debate on banking competition, deregulation, and risk-based supervision. Using ECB supervisory data for 146 euro area banks across 19 countries over 2020Q2–2025Q3, we analyze whether this relationship depends on banks’ regulatory capital positions. We find that greater market power is associated with higher subsequent credit risk, while stronger capitalization is associated with lower risk. Crucially, competition reduces credit risk primarily for well-capitalized banks, whereas the effect is weak or absent for banks with lower capital ratios. By aligning the measurement of competition and risk with the pricing-based mechanism, the paper provides a direct empirical test of the borrower-risk channel and offers an explanation for mixed evidence in the competition–risk literature. The results highlight the importance of considering the interaction between competition and prudential capital requirements when assessing financial stability.
- 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
L11 : Industrial Organization→Market Structure, Firm Strategy, and Market Performance→Production, Pricing, and Market Structure, Size Distribution of Firms
C23 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Panel Data Models, Spatio-temporal Models
- 17 September 2026
- WORKING PAPER SERIES - No. 3284Details
- Abstract
- We develop a direct approach to incorporating survey density forecasts into model-based predictive distributions. Histogram forecasts from the U.S. Survey of Professional Forecasters (SPF) carry rich nonparametric information about expected outcomes, but existing methods rely on moment-based approximations that discard part of it. We instead tilt entropically to the histogram probabilities themselves, matching them exactly. After reformulating the single-histogram problem, we derive a new analytic characterization of the multiple-histogram case, solved by Iterative Proportional Fitting and applicable to simulated densities from essentially any model. Applying the method to real-time forecasts from a Bayesian VAR with time-varying volatility, we find that tilting to SPF histograms substantially improves accuracy relative to the model’s baseline forecasts, especially during the Great Recession and the COVID-19 pandemic. The gains extend beyond the variables the SPF targets, improving forecasts for other variables in the system as well.
- JEL Code
- C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
- 17 September 2026
- WORKING PAPER SERIES - No. 3283Details
- Abstract
- Measuring sentiment from financial news is a central task in economics and finance, yet most existing indicators rely on dictionary-based approaches that infer sentiment from word counts and only partially capture context, negation, and semantic structure. This paper proposes a framework for constructing daily news mood indices using transformer-based language models and evaluates whether they better represent sentiment than dictionary-based alternatives. Using 143,755 financial news articles from Factiva, we classify sentiment at the sentence level with FinBERT and aggregate these predictions into article-level and daily sentiment measures through alternative normalization schemes. We compare the resulting indices with benchmark measures based on Shapiro et al., 2022 and Barbaglia et al., 2025. A central contribution is the validation of alternative sentiment measures against human judgments. We conducted an incentivized annotation exercise in which 444 participants evaluated a validation subsample of 588 financial news articles. Consensus ratings from independent human evaluations serve as an external benchmark for assessing the quality of automated sentiment measures. Across correlation, regression, and classification exercises, transformer-based measures show stronger agreement with human judgments than vocabulary-based alternatives and perform substantially better in distinguishing positive, neutral, and negative articles. Overall, the results suggest that incorporating contextual information through transformer-based language models produces sentiment measures that more closely reflect human assessments of financial news.
- JEL Code
- C55 : Mathematical and Quantitative Methods→Econometric Modeling→Modeling with Large Data Sets?
C81 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Microeconomic Data, Data Access
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
G14 : Financial Economics→General Financial Markets→Information and Market Efficiency, Event Studies, Insider Trading
- 17 September 2026
- OCCASIONAL PAPER SERIES - No. 399Details
- Abstract
- Estimates of potential output and the output gap are widely used in monetary, fiscal and structural policy analysis, but they are unobservable and subject to substantial real-time uncertainty. This paper examines revisions to output gap and potential growth estimates produced by the European Commission, the Eurosystem, the International Monetary Fund (IMF) and the Organisation for Economic Co-operation and Development (OECD) for the euro area and its member countries. Using annual forecast vintages covering up to 20 euro area countries from 2002 to 2025 and a balanced panel of 11 countries from 2007 to 2025, the paper compares the reliability of estimates across institutions, decomposes output gap revisions into their main sources and estimates the impact of real GDP data revisions and forecast errors on potential growth revisions. The results show sizeable differences across institutions: European Commission estimates revise least in the balanced country sample, OECD estimates revise most, and Eurosystem estimates have become markedly more stable over the past decade. Output gap revisions are driven mainly by revisions to real GDP data and potential growth, while nowcast errors play a smaller role. Panel regressions show that both real GDP data revisions and medium-term forecast errors are significantly associated with revisions to potential growth, implying that revised or unexpected GDP developments are to some extent absorbed into estimates of potential growth. The findings highlight the uncertainty surrounding real-time output gap estimates and support the use of complementary indicators of economic slack.
- JEL Code
- E23 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Production
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
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
C82 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Macroeconomic Data, Data Access
- 16 September 2026
- WORKING PAPER SERIES - No. 3282Details
- Abstract
- Suspending loan repayments is a widely used policy tool to provide liquidity during crises. We study the take-up and real effects of the 2020 Austrian corporate debt moratoria, which required banks to temporarily postpone loan repayments for eligible firms. Exploiting a discontinuity in eligibility at a two-million-euro asset threshold, we document a take-up rate of 44%, well below full participation, reflecting both the pecuniary cost of the policy and firms’ fear of stigmatization. Despite the moderate take-up, moratoria increase investment and profitability without increasing defaults once repayments resume. We estimate a marginal propensity to invest of 47 cents per euro of postponed payments. We compare moratoria with grants, the predominant form of business support in the United States. A key feature of the policy is that relief is administered by relationship lenders, who continue to bear credit risk, retain incentives to monitor borrowers, and can credibly discipline them through future lending decisions. Although grants achieve higher take-up, our results suggest that moratoria differ fundamentally by discouraging firms from diverting liquidity to shareholders and instead channeling it toward productive investment.
- JEL Code
- 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
G35 : Financial Economics→Corporate Finance and Governance→Payout Policy
H81 : Public Economics→Miscellaneous Issues→Governmental Loans, Loan Guarantees, Credits, Grants, Bailouts
D25 : Microeconomics→Production and Organizations
- 15 September 2026
- WORKING PAPER SERIES - No. 3281Details
- Abstract
- How does the effectiveness of monetary policy vary over the policy cycle? Do tightenings and loosenings have symmetric effects on the macroeconomy? This paper addresses these questions using a nonlinear empirical framework that allows financial exposure to evolve endogenously in response to macroeconomic conditions and monetary policy changes. We provide new evidence on how monetary policy effectiveness varies over the policy cycle and across economic states. We find that i) monetary policy transmits more strongly to the real economy in periods of elevated private-sector financial exposure; ii) tightening cycles increase financial exposure in the short run, which in turn amplifies the effect of further interest rate increases, whereas loosening cycles lower financial exposure, increasingly dampening the effect of interest rate cuts; iii) tightening during economic downturns further intensifies debt-servicingpressures, making monetary policy even more potent; instead, when the tightening occurs during expansions, monetary policy effectiveness is not materially affected.
- JEL Code
- E3 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles
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
- 14 September 2026
- WORKING PAPER SERIES - No. 3280Details
- Abstract
- Does the Federal Reserve’s monetary policy influence the rates on USD-pegged stablecoins? While major stablecoin issuers do not pay interest, investors can earn returns by depositing stablecoins in Decentralized Finance (DeFi) protocols. We document unusually large and persistent spreads between traditional short-term interest rates and DeFi deposit rates, as well as a weak and unstable transmission of policy rate changes. We show that, in the short run, monetary policy shocks can move stablecoin rates in the opposite direction of policy rates, delaying a convergence that occurs only over the medium run. Both the sign of the short-run effect and the speed of convergence depend on the intensity of deleveraging induced by crypto-price reactions relative to the standard interest-rate arbitrage channel — an effect shaped by investors’ limited ability to bridge traditional and decentralized finance.
- JEL Code
- G14 : Financial Economics→General Financial Markets→Information and Market Efficiency, Event Studies, Insider Trading
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
G29 : Financial Economics→Financial Institutions and Services→Other
- 14 September 2026
- WORKING PAPER SERIES - No. 3279Details
- Abstract
- Government spending falls disproportionately on non-tradable services. We show empirically that government spending shocks stimulate private consumption along with sizable spillovers to the goods sector and a relative decline in goods prices. We rationalize these findings with a two-sector open-economy HANK model. Uninsurable income risk and precautionary savings lead to a persistent income-driven expansion in private consumption. In the tradable sector, import intensity and limited labor reallocation dampen wage pass-through to prices, matching observed co-movements. The resulting expenditure switching produces a positive tradable output response despite deteriorating net exports. Household heterogeneity and trade openness jointly shape sectoral fiscal multipliers.
- JEL Code
- E62 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→Fiscal Policy
F41 : International Economics→Macroeconomic Aspects of International Trade and Finance→Open Economy Macroeconomics
E21 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Consumption, Saving, Wealth
C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
- 11 September 2026
- SURVEY OF MONETARY ANALYSTS - AGGREGATE RESULTS
- 10 September 2026
- MACROECONOMIC PROJECTIONS FOR THE EURO AREAEnglishOTHER LANGUAGES (21) +Annexes
- 10 September 2026
- MACROECONOMIC PROJECTIONS FOR THE EURO AREA
- 31 August 2026
- WORKING PAPER SERIES - No. 3278Details
- Abstract
- This paper examines whether environmental policy uncertainty undermines clean-technology investment in the United States by weakening policy-induced investment incentives. Using quarterly project-level data on U.S. greenfield investments from 2007Q1 to 2019Q1, combined with novel news-based indices that separately measure environmental policy salience and environmental policy uncertainty, we find that policy uncertainty substantially offsets the positive investment effects of environmental policy. At the aggregate level, a one-standard-deviation increase in environmental policy uncertainty eliminates roughly 75% of the policy-induced increase in the number of cleantech projects and around 50% of the increase in capital expenditure. The deterrence effect is substantially stronger for foreign than for domestic investors, consistent with greater informational frictions facing cross-border capital. These effects persist for at least two years following an uncertainty shock and are corroborated by country- and firm-level analyses, though results for capital expenditure are less robust at disaggregated levels. The findings imply that policy credibility is a first-order determinant of clean investment: an environmental policy framework that is ambitious but perceived as unstable may fail to mobilize the capital it is designed to attract.
- JEL Code
- Q58 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Government Policy
F21 : International Economics→International Factor Movements and International Business→International Investment, Long-Term Capital Movements
F23 : International Economics→International Factor Movements and International Business→Multinational Firms, International Business
E22 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Capital, Investment, Capacity
- 24 August 2026
- WORKING PAPER SERIES - No. 3277Details
- Abstract
- We analyze the Probability of Default (PD) of non-financial corporations in Europe using Random Forests (RF) and assess implications for stress testing the banking sector. To this end, we exploit data on firms’ financial statements (Orbis) and banks’ credit registry (Anacredit). We show that RF displays stronger risk sensitivity than logistic regression in stress testing, shedding new light on the non-linear effect of scenario severity on PD. Moreover, we show how RF-based PD can be used in a network of banks and firms to stress test the banking sector through loan exposures as a key transmission channel of adverse scenarios. A granular inspection of banks’ riskiness indices derived from this network sheds light also on RF’s superior ability in capturing non-linearity thanks to its capability in identifying “tail banks”. Our work is relevant for central banks and banking supervisors alike.
- JEL Code
- C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
C55 : Mathematical and Quantitative Methods→Econometric Modeling→Modeling with Large Data Sets?
C58 : Mathematical and Quantitative Methods→Econometric Modeling→Financial Econometrics
G17 : Financial Economics→General Financial Markets→Financial Forecasting and Simulation
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
- 24 August 2026
- WORKING PAPER SERIES - No. 3276Details
- Abstract
- Retail investors increasingly discuss markets in real time on social media, yet these discussions remain difficult to measure systematically. This paper introduces the Reddit Retail Investor Sentiment Indicator (R-RISI), a high-frequency measure of retail investor sentiment based on Reddit posts from major investing and crypto-related subreddits between 2015 and April 2026. Using ChatGPT 5.1, we classify posts by sentiment and topic and show that large language models provide more accurate labels for informal social media language than widely used finance-specific models such as FinBERT, which tends to over-assign neutral sentiment. R-RISI is constructed by aggregating daily positive and negative posts, weighting them by user engagement and standardising the resulting series using a rolling one-year z-score methodology. The indicator can be flexibly built for broad asset classes, portfolios, individual securities or thematic groups, allowing sentiment to be tracked at a much higher granularity than traditional retail investor indicators. We show how sentiment and dominant discussion topics evolve over time within each of the extracted subreddits. R-RISI closely reflects major market developments and aligns with established sentiment indicators while providing higher frequency and more timely signals. Empirically, changes in R-RISI contain statistically significant short-term information for market prices. This relationship is particularly relevant during periods of market stress: changes in R-RISI matter more for next-day S&P 500 returns when markets are in decline. The indicator therefore offers a timely and granular tool for analysing retail investor behaviour and monitoring sentiment-driven market dynamics in an environment of growing retail investor participation. A regularly updated version of the indicator is available through an accompanying R-RISI online dashboard.
- JEL Code
- F1 : International Economics→Trade
G1 : Financial Economics→General Financial Markets
G4 : Financial Economics
G5 : Financial Economics
- 24 August 2026
- SURVEY OF MONETARY ANALYSTS
- 20 August 2026
- WORKING PAPER SERIES - No. 3275Details
- Abstract
- We estimate the cyclical response of labour force participation to growth shocks across EU regions. We use a shift-share instrumental variable approach and local projections on EU Labour Force Survey microdata covering 15 countries and 114 regions over 2000–2020. The aggregate labour force participation rate is remarkably resilient, a clear contrast to the highly cyclical participation rate documented for the U.S. However, this resilience masks pronounced demographic heterogeneity. Men’s participation declines significantly while women’s remains stable, reflecting sectoral segregation and the added worker effect. Young workers exhibit the most persistent responses, with effects lasting up to eight years, consistent with hysteresis through human capital erosion. Less-educated and non-native workers bear disproportionate employment costs. The findings imply that aggregate slack measures may miss important distributional dimensions relevant for monetary, fiscal, and structural policy.
- JEL Code
- J21 : Labor and Demographic Economics→Demand and Supply of Labor→Labor Force and Employment, Size, and Structure
E24 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Employment, Unemployment, Wages, Intergenerational Income Distribution, Aggregate Human Capital
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
R23 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Household Analysis→Regional Migration, Regional Labor Markets, Population, Neighborhood Characteristics
- 20 August 2026
- WORKING PAPER SERIES - No. 3274Details
- Abstract
- This paper investigates the interest rate pass-through of monetary policy in the euro area by focusing on the role of banks’ funding structures. We estimate the interest rate pass-through for loans to non-financial corporations using bank-level balance sheet data. In doing so, we interact the response of lending rates with characteristics of the funding structure, and show that banks that rely more on bond issuance than on the money market tend to be less responsive to policy changes. Finally, we test the presence of the asset-liability-management channel, and find that banks combining longer-term liabilities (higher bond shares) with longer rate fixation periods for loans (higher share of loans with fixed rates) exhibit the most muted lending rate response to policy shocks.
- JEL Code
- C23 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Panel Data Models, Spatio-temporal Models
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
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages - Network
- Challenges for Monetary Policy Transmission in a Changing World Network (ChaMP)
- 20 August 2026
- STATISTICS PAPER SERIES - No. 54Details
- Abstract
- The ECB’s inflation target is formulated in terms of headline inflation. However, domestically determined inflation features prominently in the monetary policy transmission mechanism and in gauging underlying inflation, making it important to assess it regularly. The ECB monitors various proxies for domestically determined inflation, including: (i) “domestic inflation”, which aggregates inflation items with a low import share; and (ii) “Supercore” inflation, which aggregates inflation items found to be sensitive to the aggregate business cycle. This paper provides a detailed overview of the methodologies used to derive both these indicators and updates the relevant input data. It suggests refinements to the methodologies that would also make these measures more robust in future updates. In addition, it explains the changes in these indicators due to the introduction of a new classification of consumer goods and services (European Classification of Individual Consumption according to Purpose (ECOICOP) version 2) for the compilation of the Harmonised Index of Consumer Prices (HICP). First, on domestic inflation, the paper explains the new underlying data on the import share of inflation items made available since the publication of its methodology, and provides an update, combined with a few methodological changes (for example, moving to a constant composition of the included items). Second, with regard to Supercore inflation, the paper explains the challenges of identifying a cyclical inflation indicator for the euro area, especially in the light of the recent large shocks, and explores modelling approaches. It proposes some refinements to the previous methodology, while keeping a Phillips curve approach as a focal point in the analysis. For both indicators, the paper presents the updated indicators and some key properties.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
- 12 August 2026
- OCCASIONAL PAPER SERIES - No. 398Details
- Abstract
- The Eurosystem implements its monetary policy through a set of monetary policy instruments (MPIs). This report reviews the main changes in the use of MPIs and the associated developments in the Eurosystem’s monetary policy implementation framework over 2024-25. Inflation returned to the ECB’s medium-term target of 2%, supported by the smooth transmission of monetary policy. After completing the hiking cycle of 2022 and 2023, the ECB began reducing its key interest rates in June 2024. This easing phase occurred alongside further balance sheet normalisation. Holdings in the monetary policy bond portfolios continued to run-off, and funds lent under the third series of targeted longer-term refinancing operations (TLTRO III) were fully repaid by December 2024. In March 2024, the ECB announced several changes to its operational framework for implementing monetary policy following a review process. Finally, the collateral framework remained broad, while temporary crisis-related measures were phased out and climate-related considerations were further integrated.
- JEL Code
- D02 : Microeconomics→General→Institutions: Design, Formation, and Operations
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
E65 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→Studies of Particular Policy Episodes
G01 : Financial Economics→General→Financial Crises
- 11 August 2026
- WORKING PAPER SERIES - No. 3273Details
- Abstract
- This paper examines the impact of labour and product market reforms on private investment across 26 advanced economies from 1975 to 2020. To this end, we combine a narrative database on major structural reforms with local projections and augmented inverse probability weighting. We find that a major labour market reform typically increases the level of real private investment by 5% cumulatively within six years, while a major product market reform yields an impact of 3%. Structural reforms are particularly effective in stimulating private investment when the private sector has access to ample external finance and the rule of law is strong. Overall, our findings point to an important role for structural reforms in boosting private investment and thus long-term growth prospects in advanced economies.
- JEL Code
- E22 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Capital, Investment, Capacity
O43 : Economic Development, Technological Change, and Growth→Economic Growth and Aggregate Productivity→Institutions and Growth
L51 : Industrial Organization→Regulation and Industrial Policy→Economics of Regulation
Obrestne mere
| Mejni depozit | 2,50 % |
| Operacije glavnega refinanciranja (fiksna obrestna mera) | 2,65 % |
| Mejno posojilo | 2,90 % |
Stopnja inflacije
Več o inflacijiDevizni tečaji
| USD | US dollar | 1.1460 | |
| JPY | Japanese yen | 180.94 | |
| GBP | Pound sterling | 0.85880 | |
| CHF | Swiss franc | 0.9462 |
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