Digitālais euro
Eurosistēma veic sagatavošanās darbus potenciālai digitālā euro emisijai. Digitālais euro papildinātu fizisko skaidro naudu.
TAUTSAIMNIECĪBAS BIĻETENS
05.08.2026.
Neziņas cena
Pieaugot nenoteiktībai, gan uzņēmumi, gan mājsaimniecības nogaida. Mūsu "Tautsaimniecības Biļetenā" konstatēts, ka paaugstināta nenoteiktība būtiski un noturīgi ietekmē eurozonas aktivitāti, īpaši smagi skarot ieguldījumus uzņēmējdarbībā un liekot patērētājiem atlikt izdevumus.
Sk. "Tautsaimniecības Biļetena" 1. rakstu
FINANŠU PRATĪBA
05.08.2026.
Novērst dzimumu nevienlīdzību finanšu pratības jomā
Izpratne par finanšu pamatjēdzieniem var palīdzēt cilvēkiem pieņemt apzinātus lēmumus par uzkrājumu veidošanu, izdevumiem un nākotnes plānošanu. Taču tikai katram piektajam eiropietim ir augsts finanšu pratības līmenis, un šī problēma īpaši smagi skar sievietes. Uzziniet, kāpēc ir svarīgi novērst dzimumu nevienlīdzību.
Uzziniet vairāk
ECB BLOGS
05.08.2026.
Kā enerģijas cenas veicina dzīvojamo māju efektivitāti
Augstās enerģijas cenas radījušas nebijušu interesi par renovācijām, kas vērstas uz energoefektivitātes veicināšanu, un par nefosilā kurināmā apkure sistēmām. Šajā bloga ierakstā parādīts, ka šādas investīcijas mazina enerģijas šoku ietekmi uz būvniecības sektoru.
Lasiet ECB blogu- 4 August 2026
- WEEKLY FINANCIAL STATEMENTEnglishOTHER LANGUAGES (22) +Annexes
- 4 August 2026
- WEEKLY FINANCIAL STATEMENT - COMMENTARY
- 31 July 2026
- MFI INTEREST RATE STATISTICS
- 30 July 2026
- PRESS RELEASE
- 29 July 2026
- PRESS RELEASE
- 28 July 2026
- WEEKLY FINANCIAL STATEMENTEnglishOTHER LANGUAGES (22) +Annexes
- 28 July 2026
- WEEKLY FINANCIAL STATEMENT - COMMENTARY
- 24 July 2026
- Slides by Philip R. Lane, Member of the Executive Board of the ECB, at MacGill Summer School 2026 in Glenties, Co. Donegal, Ireland
- 23 July 2026
- Christine Lagarde, President of the ECB, Boris Vujčić, Vice-President of the ECB, Frankfurt am Main, 23 July 2026EnglishOTHER LANGUAGES (23) +Related
- 17 July 2026
- Lecture by Piero Cipollone, Member of the Executive Board of the ECB, at the Annual Meeting of the Federation of Italian Cooperative Credit Banks (Federcasse)
- 13 July 2026
- Slides by Isabel Schnabel, Member of the Executive Board of the ECB, at the Annual Economic Reception of the Deputy Minister-President of North Rhine-Westphalia in Münster, Germany
- 6 July 2026
- Dinner speech by Philip R. Lane, Member of the Executive Board of the ECB, at the Closing Conference of the European System of Central Banks Research Network on Challenges for Monetary Policy Transmission in a Changing World (ChaMP)[1]
- 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
- 2 July 2026
- Interview with Christine Lagarde, President of the ECB, conducted by Guillaume Benoit and Christophe Jakubyszyn on 24 June 2026
- 25 June 2026
- Interview with Isabel Schnabel, Member of the Executive Board of the ECB, conducted by Mark Schieritz and Kolja Rudzio on 19 June 2026
- 10 June 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 Daan Ballegeer and Rutger Betlem on 19 May 2026
- 5 August 2026
- High energy prices have sparked new interest in energy-related renovations and non-fossil heating systems. This blog post argues that such investments cushion the impact of energy shocks on the building and construction sector.Details
- JEL Code
- Q41 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→Demand and Supply, Prices
Q48 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→Government Policy
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
- 31 July 2026
- Retail fuel prices have surged in 2026 following the outbreak of the conflict in the Middle East, driving up euro area energy inflation. In this blog, we examine the factors that drive fuel price dynamics at the pump.Details
- JEL Code
- Q40 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→General
Q41 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→Demand and Supply, Prices
Q48 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→Government Policy
- 29 July 2026
- Energy prices are surging again, pushing up inflation in the euro area. This ECB Blog post examines whether firms are attributing this to a demand surge or to supply constraints. Two approaches – textual analysis and empirical models – can help make the picture clearer.Details
- 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
E50 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→General
Related - 27 July 2026
- Why have energy prices risen less during the Iran war than after Russia’s invasion of Ukraine? This ECB Blog post compares the two episodes and explains the role of market buffers, demand and competition for LNG shipments.Details
- JEL Code
- Q41 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→Demand and Supply, Prices
Q43 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→Energy and the Macroeconomy
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
Related - 24 July 2026
- Amid ongoing concerns over European productivity growth, this ECB Blog post looks at the relationship between macroprudential policy and productivity.Details
- JEL Code
- E60 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→General
E50 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→General
- 5 August 2026
- ECONOMIC BULLETIN - ARTICLEEconomic Bulletin Issue 5, 2026Details
- Abstract
- Economic uncertainty – the extent to which households, firms, investors and policymakers find it difficult to assess the economic outlook – has increased markedly in recent years with successive geopolitical and trade policy shocks. This article reviews recent developments in various proxies for uncertainty and shows that metrics capturing geopolitical and trade policy uncertainty have remained persistently elevated. The adverse impact of uncertainty shocks on business investment is typically larger and more persistent than the effect on private consumption. These results hold for different types of uncertainty measures, even when alternative empirical methods that employ external instruments are used. At the same time, a more granular assessment shows some differences across types of investment, with intangible investment generally being less sensitive to short-term uncertainty than tangible investment. Moreover, spending on durable goods and services is most strongly affected immediately after a rise in uncertainty, while the recovery in services spending is more protracted.
- JEL Code
- D81 : Microeconomics→Information, Knowledge, and Uncertainty→Criteria for Decision-Making under Risk and Uncertainty
E21 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Consumption, Saving, Wealth
E22 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Capital, Investment, Capacity
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
- 5 August 2026
- WORKING PAPER SERIES - No. 3270Details
- Abstract
- We design an econometric framework to simulate multiple adverse macro-financial scenarios that can be used in top-down stress tests. First, we create a financial stress index informed by shocks generated via a non-parametric copula estimated on a large dataset of daily financial indicators. Second, we simulate the joint dynamics of macroeconomic indicators conditional on the copula-based financial shocks in a large multi-country Bayesian VAR model. This framework,which we refer to as the Multiple macro-financial stress scenario Simulation Engine, MuSE, allows us to replicate thousands of macro-financial stress scenarios where adverse shocks generated in the financial sector propagate into the overall economy, triggering significant macroeconomic fluctuations. We demonstrate its functionality by generating a large number of scenarios inspired from past crises capturing stress stemming from financial markets, sovereign debt, and geopolitical tensions. Using a top-down solvency stress test model, based on recent EU-wide stress tests, we project the capital depletion for euro area banks and find that adverse scenarios triggered by stock market and sovereign shocks appear to threaten the resilience of the euro area banking sector the most at this juncture.
- JEL Code
- C15 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Statistical Simulation Methods: General
G01 : Financial Economics→General→Financial Crises
G17 : Financial Economics→General Financial Markets→Financial Forecasting and Simulation
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
- 5 August 2026
- WORKING PAPER SERIES - No. 3269Details
- Abstract
- We analyse whether textual information extracted from firms’ earnings calls can improve forecasts of the euro area job vacancy rate. Using transcripts from euro area headquartered firms, we construct a monthly indicator of labour demand based on keywords related to labour market pressures and include it into a mixed frequency Bayesian VAR alongside standard hard and soft indicators. A pseudo–real-time evaluation shows that earnings calls provide timely and valuable signals for tracking vacancy dynamics. Among soft indicators, factors limiting production deliver the largest forecasting gains, while real labour-market indicators such as unemployment add little once qualitative signals are included. Forecast improvements are largely driven by information from the manufacturing sector, whose signals prove substantially more informative than those from services, especially when paired with earnings calls. Taken together, our results highlight the usefulness of high-frequency text-based information for improving short-term labour-demand forecasts in the euro area.
- JEL Code
- C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E24 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Employment, Unemployment, Wages, Intergenerational Income Distribution, Aggregate Human Capital
E27 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Forecasting and Simulation: Models and Applications
- 4 August 2026
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 5, 2026Details
- Abstract
- This box examines EU venture capital market developments and the implications for firm financing and growth. Venture capital in the EU remains limited in scale and fragmented across national markets, with gaps particularly evident at later stages of financing where they are partially filled by non-EU investors. Although venture capital from outside the EU can help firms expand, a strong reliance on external investors may reduce Europe’s ability to retain the economic gains generated by its entrepreneurial ecosystem. At the same time, venture capital in Europe appears broadly well targeted towards high-performing firms, suggesting significant potential to support growth. Policy action to deepen and integrate the EU venture capital ecosystem can therefore help strengthen the EU economy.
- JEL Code
- E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E22 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Capital, Investment, Capacity
O16 : Economic Development, Technological Change, and Growth→Economic Development→Financial Markets, Saving and Capital Investment, Corporate Finance and Governance
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
F36 : International Economics→International Finance→Financial Aspects of Economic Integration
- 4 August 2026
- WORKING PAPER SERIES - No. 3268Details
- Abstract
- Banks use their internal models to estimate capital requirements in a risk-sensitive way, subject to a set of rules laid down in banking regulation. However, these models are not flawless as the usage of models suffers from imperfections, such as oversimplifications or wrong assumptions. As a result, risks may be underestimated. This is particularly troublesome, where models are used to assess risks to banks’ solvency. In this paper we address an important gap in the literature with regard to such model risk. We find that a small set of high severity deficiencies in models is responsible for the majority of the counterfactual RWA burden imposed by supervisory capital add-ons. We trace the underlying non-compliances to a subset of CRR articles that mostly govern the handling of IRB-relevant data by banks. Our results help improve the supervision of IRB-banks by proposing more efficient use of scarce supervisory resources.
- 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
G29 : Financial Economics→Financial Institutions and Services→Other
- 4 August 2026
- WORKING PAPER SERIES - No. 3267Details
- Abstract
- While employer-to-employer (E2E) transitions are by now well-documented, these data alone cannot reveal what drives mobility: who searches, why, and how search translates into transitions. Using novel panel data from the ECB and NY Fed consumer expectations surveys, we provide the first systematic cross-country analysis of on-the job search (OJS) and E2E transitions across eleven euro area countries and the U.S. Our data uniquely include direct measures of OJS and its motives (job loss expectations for precautionary, pay satisfaction for job ladder) for all workers, not just searchers. We find that OJS is widespread, making employed workers the majority of searchers, and it strongly predicts E2E transitions. Motives differ dramatically: precautionary search dominates in Europe, while the job ladder motive dominates in the U.S. OJS is highly persistent, with 40% continuing to search even after starting a new job.
- JEL Code
- J64 : Labor and Demographic Economics→Mobility, Unemployment, Vacancies, and Immigrant Workers→Unemployment: Models, Duration, Incidence, and Job Search
D84 : Microeconomics→Information, Knowledge, and Uncertainty→Expectations, Speculations
- 3 August 2026
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 5, 2026Details
- Abstract
- This box examines the mechanisms behind the aggregate and distributional effects of energy price shocks on euro area households, taking its cue from the recent surge in energy prices following the outbreak of the war in the Middle East. Drawing on a quantitative heterogeneous agent New Keynesian model calibrated to the euro area, it shows that energy price shocks reduce aggregate consumption through real income losses. This burden falls disproportionately on liquidity-constrained households, which spend a larger share of their household budget on energy and have fewer resources to absorb such price 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
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E22 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Capital, Investment, Capacity
Q43 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→Energy and the Macroeconomy
- 3 August 2026
- WORKING PAPER SERIES - No. 3266Details
- Abstract
- This paper studies the dynamics of U.S. sectoral producer prices in a large Bayesian Vector Auto Regression (BVAR) model where the Input-Output (IO) matrix is used to structure their long-run relationships. The model provides evidence of a sectoral spillover channel in driving headline inflation without imposing such a mechanism in the model’s structure. Forecasts of headline inflation have accuracy comparable to the Survey of Professional Forecasters’ and greater than those generated by a standard BVAR with the Minnesota prior, confirming that the IO matrix long-run prior conveys relevant information about the data. The study of an oil price shock shows that adding the production network prior alters the transmission of the shock, amplifying headline inflation. Across sectors, the peak price response to the oil shock increases with oil intensity. A narrowly sector-specific disturbance, such as a cereal price shock, has non-negligible aggregate effects once the production network is accounted for. Sectoral asymmetries are crucial for evaluating the macroeconomic consequences of macroeconomic shocks such as an energy price shock and a monetary policy shock, as industries with slower price adjustments amplify inflation persistence, even after the shock dissipates.
- JEL Code
- C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C55 : Mathematical and Quantitative Methods→Econometric Modeling→Modeling with Large Data Sets?
E30 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→General
- 3 August 2026
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 5, 2026Details
- Abstract
- The onset of the war in the Middle East triggered a sharp deterioration in consumer confidence across the euro area, comparable in magnitude to that observed after Russia’s invasion of Ukraine. This box examines the extent to which the decline in confidence is associated with actual consumption behaviour using microdata from the ECB Consumer Expectations Survey. The analysis reveals that nominal consumption growth softened materially in April 2026, driven mainly by reduced discretionary spending, particularly among higher-income households. Looking ahead, the consumption outlook could face additional downside risks if households were to expect lasting losses in real income.
- JEL Code
- D12 : Microeconomics→Household Behavior and Family Economics→Consumer Economics: Empirical Analysis
E21 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Consumption, Saving, Wealth
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
- 30 July 2026
- WORKING PAPER SERIES - No. 3265Details
- Abstract
- The question of how oil supply news shocks transmit to real activity, financial conditions, and regional labor markets is back at the center of the macroeconomic research agenda. To answer this question, we introduce the Factor Bayesian Additive Regression Tree (FABART) model, a nonlinear factor-augmented vector autoregression model, and apply it to a large U.S. macro-financial dataset with externally identified oil supply news shocks. The framework combines a large macro-financial information set with a flexible nonparametric measurement equation, allowing nonlinear transmission to emerge from the data rather than being imposed through a pre-specified functional form. We find that adverse oil supply news shocks generate stronger and more persistent contractions in real activity than the expansions associated with favorable shocks of comparable magnitude, with especially pronounced differences in industrial production, financial variables, and equity prices. Employment responses are highly heterogeneous across U.S. states, with substantially stronger contractions in manufacturing-intensive regions, while energy-producing states display partially offsetting dynamics following adverse oil supply news shocks. Across shock magnitudes, nonlinearities arise mainly between very small and moderate oil-price movements: small shocks generate weak and imprecisely estimated responses, while moderate shocks already produce economically meaningful effects on industrial production and regional employment. Larger shocks do not systematically generateproportionally stronger responses across variables and shock signs.
- JEL Code
- 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
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
Q43 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→Energy and the Macroeconomy
- 30 July 2026
- WORKING PAPER SERIES - No. 3264Details
- Abstract
- We develop a new approach to estimating earnings, job, and employment dynamics using subjective expectations data from the NY Fed Survey of Consumer Expectations. These data provide beliefs about future earnings offers and acceptance probabilities, offering direct information on counterfactual outcomes and enabling identification under weaker assumptions. Our framework avoids biases from selection and unobserved heterogeneity that affect models using realized outcomes. First-step fixed-effects regressions identify risk, persistence, and transition effects; second-step GMM recovers the covariance structure of unobserved heterogeneities such as ability, mobility, and match quality. We find lower risk and persistence of the individual productivity component than in prior work, but greater heterogeneity in ability and match quality. Simulations show that reduced-form estimates overstate persistence and volatility on individual-level productivity due to job transitions and sorting. After accounting for heterogeneity, volatility declines and becomes flat across the earnings distribution. These results underscore the value of expectations data.
- JEL Code
- C23 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Panel Data Models, Spatio-temporal Models
C81 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Microeconomic Data, Data Access
D15 : Microeconomics→Household Behavior and Family Economics
- 30 July 2026
- OTHER PUBLICATION
- 29 July 2026
- WORKING PAPER SERIES - No. 3263Details
- Abstract
- We develop an endogenous threshold VAR that addresses contemporaneous dependence between the threshold variable and reduced-form innovations— a pervasive issue when regime indicators are jointly determined with system dynamics. A regime-specific copula-based control function removes this dependence instrument-free, without parametric assumptions on the threshold’s marginal distribution, while preserving the linear regime-wise least-squares structure. We characterize the resulting misspecification through excess sensitivity and excess propagation errors in impulse responses, clarify structural and proxy-SVAR identification under endogenous regimes, and establish conditions under which Chan-type threshold asymptotics remain valid with generated controls. A Hermite sieve extension accommodates tail-dependent and asymmetric dependence. Monte Carlo evidence documents large distortions from ignoring endogeneity. Applied to monetary transmission, the framework avoids the price and persistence puzzles displayed by the linear VAR, delivers regime-dependent sacrifice ratios, and aligns estimated regimes with historical inflation episodes.
- 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
C34 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Truncated and Censored Models, Switching Regression Models
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
- 29 July 2026
- WORKING PAPER SERIES - No. 3262Details
- Abstract
- Financial stability risks consist of two distinct components: vulnerabilities and possible trigger events. While there has been considerable progress regarding the measurement of vulnerabilities, the assessment of possible trigger events remains largely qualitative. To fill this gap, we employ Large Language Models to extract information about the Severity and Probability Of potential Trigger events (SPOT) from a large dataset of financial news articles over the period2005 – 2026. The SPOT indicator increases ahead of major historical trigger events, correctly identifies trigger sources, and helps to improve forward looking model estimates of downside risks to the economy. The results indicate that the use of AI-based signal extraction from text can be a promising avenue to improve the monitoring of financial stability risks.
- JEL Code
- C55 : Mathematical and Quantitative Methods→Econometric Modeling→Modeling with Large Data Sets?
C88 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Other Computer Software
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
G01 : Financial Economics→General→Financial Crises
- 28 July 2026
- WORKING PAPER SERIES - No. 3261Details
- Abstract
- The climate crisis is an urgent, human-driven systemic challenge whose impacts are unfolding through increasingly frequent and severe extreme events. Although the 2015 Paris Agreement advanced global climate governance, implementation remains insufficient to limit warming to well below 2 °C and pursue 1.5 °C. Accelerating risks, interacting crises and potential tipping points suggest that climate change could become unmanageable if current GHGs emissions trajectories persist. This paper makes three contributions. First, it examines why we are failing to act decisively, highlighting a persistent awareness gap, competing priorities and weak political incentives for ambitious climate action. Second, it draws on NGFS climate-policy scenarios, the climate policy trilemma and a precautionary approach to clarify policymaking trade-offs under uncertainty. Third, it reviews policy, financial and technological levers to accelerate a just green transition. A new climate policy paradigm is needed: a systemic, precautionary, adaptive and incentive-compatible framework that can “tilt the odds” away from irreversible climate damage, even when probabilities are poorly known.
- JEL Code
- D81 : Microeconomics→Information, Knowledge, and Uncertainty→Criteria for Decision-Making under Risk and Uncertainty
E61 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→Policy Objectives, Policy Designs and Consistency, Policy Coordination
D62 : Microeconomics→Welfare Economics→Externalities
Q54 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Climate, Natural Disasters, Global Warming
- 28 July 2026
- OCCASIONAL PAPER SERIES - No. 395Details
- Abstract
- This paper explores the adoption of artificial intelligence (AI) technologies among euro area firms, using harmonised firm-level data from two dedicated modules of the Survey on the Access to Finance of Enterprises (SAFE) conducted in June and December 2025. Based on responses from around 6,000 firms across 12 euro area countries, the study examines AI adoption rates, drivers, barriers and economic implications. The findings suggest that AI diffusion among euro area firms is progressing rapidly but unevenly, with significant variation across countries and firm characteristics. Approximately 70% of firms report some level of AI use, but only 7% classify their adoption as significant. Adoption is highest in the Netherlands, Finland and Austria, and lowest in Italy and Ireland. Larger and younger firms, particularly in technology-intensive sectors, are leading adopters. Firms identify expected improvements in business processes as the main driver of adoption, while key barriers include skill shortages, data privacy concerns and system incompatibilities. Current AI use and investment are primarily financed through internal funds, complemented by grants and subsidised bank loans. AI adoption is positively associated with firm productivity, turnover growth, fixed investment and own selling price expectations, particularly among intensive users. Survey data show no evidence yet of aggregate labour shedding; instead, AI adoption is positively associated with employment growth. However, firms’ inflation expectations appear largely unaffected by current AI use.
- JEL Code
- C93 : Mathematical and Quantitative Methods→Design of Experiments→Field Experiments
D22 : Microeconomics→Production and Organizations→Firm Behavior: Empirical Analysis
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
L25 : Industrial Organization→Firm Objectives, Organization, and Behavior→Firm Performance: Size, Diversification, and Scope
O33 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights→Technological Change: Choices and Consequences, Diffusion Processes
- 28 July 2026
- RESEARCH BULLETIN - No. 145Details
- Abstract
- Monetary policy tightening generates valuation losses on banks’ securities portfolios, reducing the collateral available for interbank borrowing. Using detailed euro area data, we show that banks with larger securities losses during the 2022-23 monetary policy tightening cycle obtained less interbank funding and reduced lending to firms, even when losses did not affect regulatory capital. These effects were strongest for banks with limited liquidity buffers and high collateral utilisation. While internal capital markets partly shield domestic subsidiaries within banking groups, foreign subsidiaries receive less support, pointing to persistent fragmentation in cross-border liquidity allocation and uneven monetary policy transmission across the euro area.
- JEL Code
- G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
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
- 27 July 2026
- WORKING PAPER SERIES - No. 3260Details
- Abstract
- This study investigates the effect of the large shock to energy prices following the Russian invasion of Ukraine on bank credit to firms. To isolate the causal effect of the shock, it compares bank lending to high-energy-intensive firms to that of similar low-energy-intensive firms. Following the shock, bank credit to high-energy-intensive firms persistently declined, while their interest rates on new loans rose and other loan terms tightened. Across the distribution, safer firms reduced outstanding credit lines and paid unchanged interest rates on new bank loans, while riskier firms borrowed at higher interest rates.
- 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
Q43 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→Energy and the Macroeconomy
- 27 July 2026
- WORKING PAPER SERIES - No. 3259Details
- Abstract
- Elevated repo rate specialness for German government bonds in 2016–17, and particularly in 2022-23, has often been linked to the absorption of these securities by the ECB’s asset purchase programmes. We provide the first evidence on how the debt management office mitigates these effects by jointly analyzing daily secondary-market trades and repo operations of the Deutsche Finanzagentur (DFA) alongside Eurosystem transactions in Bunds from 2015–2024. We find two points: first, that Eurosystem purchases depress repo rates about four times more than DFA purchases (0.4 bp vs 0.1 bp per 1% of free float), while DFA repo lending raises repo rates by roughly 0.2 bp per 1% of outstanding volume. Our evidence suggests that DFA interventions helped mitigate scarcity-induced specialness. Second, with elevated hedge fund demand for bonds, the overall alleviating impact was constrained by segmentation in the repo market and by the design of the facilities themselves, which aimed to prevent collateral shortages and fails-to-deliver rather than to provide price support.
- JEL Code
- E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
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
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
H63 : Public Economics→National Budget, Deficit, and Debt→Debt, Debt Management, Sovereign Debt
- 24 July 2026
- SURVEY OF MONETARY ANALYSTS - AGGREGATE RESULTS
Procentu likmes
| Noguldījumu iespēja uz nakti | 2.25 % |
| Galvenās refinansēšanas operācijas (ar fiksētu procentu likmi) | 2.40 % |
| Aizdevumu iespēja uz nakti | 2.65 % |
Inflācija
Vairāk par inflācijuValūtu kursi
| USD | US dollar | 1.1554 | |
| JPY | Japanese yen | 182.08 | |
| GBP | Pound sterling | 0.85720 | |
| CHF | Swiss franc | 0.9345 |
PĀRĀK SAREŽĢĪTI? SK. SADAĻU "NODERĪGA INFORMĀCIJA"
UZZINIET VAIRĀK
Kas ir Eiropas Centrālā banka?