Цифрово евро
Евросистемата се подготвя за евентуалното емитиране на цифрово евро, което да допълни физическите пари в брой.
ИКОНОМИЧЕСКИ БЮЛЕТИН
6 август 2026 г.
ЕЦБ публикува Икономическия бюлетин
В тази публикация се представя информация по икономически и парични теми. Въз основа на нея Управителният съвет взема своите решения по политиките. Излиза осем пъти годишно, две седмици след всяко заседание по паричната политика.
Новия Икономически бюлетин
ФИНАНСОВА ГРАМОТНОСТ
5 август 2026 г.
За равенство между половете във финансовата грамотност
Познаването на основни финансови понятия може да помогне на хората да вземат обосновани решения за спестяванията, разходите и плановете си. Но само една пета от европейците имат висока финансова грамотност, а жените са особено засегнати. Вижте защо е важно да затворим ножицата.
Научете повече
БЛОГ НА ЕЦБ
7 август 2026 г.
От нефт към електрони
Енергийната матрица на Европа вече не е толкова уязвима на резки промени в цените на горивата. Днес въпросът е как да електрифицираме и транспорта, отоплението и промишлеността. На какво ни учат '70-те? Трябва не само да разнообразим енергийните доставки, но и да търсим структурни промени.
Прочетете блога на ЕЦБ- 7 August 2026
- PRESS RELEASE
- 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
- 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
- 7 August 2026
- Europe’s electricity mix has become cleaner and less exposed to fossil fuel price swings. The challenge now is to extend electrification to transport, heating and industry. The lesson from the 1970s is that we must not just diversify energy supply but push for structural change too.Details
- JEL Code
- N70 : Economic History→Transport, Trade, Energy, Technology, and Other Services→General, International, or Comparative
Q40 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→General
- 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
- 7 August 2026
- LETTERS TO MEPS
- 6 August 2026
- WORKING PAPER SERIES - No. 3271Details
- Abstract
- We show that monetary policy transmission is shaped not only by a sector’s own financial frictions but also by those prevailing in the broader production network. The latter, indirect frictions amplify the output and price effects of monetary policy and empirically dominate the direct ones. The amplification results from a downstream demand channel, as customers respond to tighter policy by purchasing fewer inputs. This is partly offset by an upstream cost channel, reflecting that suppliers raise prices to protect margins when financing costs rise. We inspect the mechanism in a multi-sector general equilibrium model with input-output linkages and working-capital constraints.
- 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
C67 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Input?Output Models
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
- 6 August 2026
- OCCASIONAL PAPER SERIES - No. 396Details
- Abstract
- This paper introduces reduced-form macroeconometric tools, emphasising quantile regression models, to identify key risk drivers for the euro area economy and assess risks around the baseline ECB/Eurosystem staff macroeconomic projections for the euro area inflation and growth. The analysis uses a large number of risk factors, going beyond the usual financial factors, employing a sequential selection approach with robustness checks. To support the analysis a MATLAB toolbox (M@RX) was developed, incorporating several quantile regression-based model classes with a novel parametric tilting methodology and a copula approach for transforming predictive densities across frequencies. This paper contributes to the literature on the treatment of the COVID-era data in quantile regression models. Results indicate that the predictive content of risk factors is horizon, time and objective-dependent. For example, labour market indicators are particularly relevant for assessing upside inflation risks, but to a time-varying extent and with limited predictive power for downside risks. Conversely, uncertainty, money and credit indicators perform better for downside inflation risks. As regards risks to growth, the results confirm the established role of financial conditions, while also highlighting the relevance of monetary indicators, particularly for downside risks. Combined risk factor frameworks – with several different risk indicators – tend to systematically outperform single-factor specifications for density forecasting, due to complementarities across risk indicator groups. An empirical application highlights the policy relevance of these tools, as they provide timely signals and accurately track the direction of realised outcomes. Given the time-varying and state-dependent nature of their predictive performance, a regular performance assessment of the specifications is recommended to maintain reliability.
- JEL Code
- C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E27 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Forecasting and Simulation: Models and Applications
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
- 6 August 2026
- ECONOMIC BULLETIN
- 6 August 2026
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 5, 2026Details
- Abstract
- This box assesses the scope for euro area governments to adopt compensatory fiscal measures against the backdrop of the recent energy shock. It examines the available fiscal space, reviews the discretionary fiscal support provided so far, and assesses whether the current inflation environment has generated additional revenues that could partially finance current and future measures. The box concludes that, since fiscal space is more constrained than it was during the 2022 energy crisis and there is only modest scope for self-financing through inflation-driven revenues, it is all the more important for fiscal support to be temporary, targeted and tailored.
- JEL Code
- E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
C5 : Mathematical and Quantitative Methods→Econometric Modeling
- 6 August 2026
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 5, 2026Details
- Abstract
- This box introduces the European Central Bank Broad Intermediation Gauge (ECB-BIG) index, a new indicator designed to provide a timely assessment of intermediation conditions in the euro area. The ECB-BIG index summarises information from a large set of variables covering bank and non-bank credit conditions, and complements indicators of more narrowly defined financial conditions. It also provides insights into the transmission of monetary policy to the real economy by measuring the impact of credit shocks on investment. Currently, the index is signalling a moderate tightening of credit conditions after the start of the war in the Middle East.
- 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
G20 : Financial Economics→Financial Institutions and Services→General
- 6 August 2026
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 5, 2026Details
- Abstract
- This box assesses the anchoring of longer-term inflation expectations following the recent energy price shock using level, higher-moment and shock-sensitivity measures from surveys of consumers, firms and professional forecasters. A holistic approach reflecting the structurally different expectation patterns, uncertainty levels and biases of these different agents yields three main findings. First, level anchoring broadly holds, as the longer-term expectations of professional forecasters remain at 2%, while firms and consumers have revised their expectations upwards only modestly and still largely view the recent increase in inflation as temporary. Second, disagreement and high inflation tail risks remain contained relative to 2022-2023 peaks, although signals are weaker for consumers and firms than for professional forecasters. Third, while consumers (unlike professional forecasters) tend to revise longer-term expectations alongside short-term ones, longer-term expectations have not become more sensitive to short-term expectations since the outbreak of the war in the Middle East. Overall, longer-term inflation expectations appear to be broadly anchored but warrant continued close monitoring.
- 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
E66 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→General Outlook and Conditions
D84 : Microeconomics→Information, Knowledge, and Uncertainty→Expectations, Speculations
- 6 August 2026
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 5, 2026Details
- Abstract
- Have labour market prospects deteriorated more for young workers than for the aggregate labour market? This box analyses labour market developments across age and skill groups in relation to economic activity. It shows that in recent quarters young workers have indeed faced a more difficult job market. However, taking the relation with developments in real GDP into account, Okun's law residuals suggest that this weakness remains broadly in line with normal cyclical dynamics, also reflecting the higher sensitivity of young workers to the economic cycle and strong employment growth during the post-pandemic recovery.
- 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
J23 : Labor and Demographic Economics→Demand and Supply of Labor→Labor Demand
- 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
Лихвени проценти
| Депозитно улеснение | 2,25 % |
| Основни операции по рефинансиране (фиксиран лихвен процент) | 2,40 % |
| Пределно кредитно улеснение | 2,65 % |
Темп на инфлация
Още по темата за инфлациятаОбменни курсове
| USD | US dollar | 1.1535 | |
| JPY | Japanese yen | 182.64 | |
| GBP | Pound sterling | 0.85765 | |
| CHF | Swiss franc | 0.9347 |
Финансова стабилност
Нашите задачи Институционална рамка Преглед на финансовата стабилност Мерки на макропруденциалната политикаПазарни операции
Операции на открития пазар Програми за закупуване на активи Отдаване в заем на ценни книжа, придобити по програмата за закупуване на активи на публичния секторЗА НЕСПЕЦИАЛИСТИ: ПРОЧЕТЕТЕ НАШАТА ОБЯСНИТЕЛНА СТАТИЯ
НАУЧЕТЕ ПОВЕЧЕ
Какво представлява ЕЦБ?