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.
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.
The Artificial Intelligence Consortium (AIC) aims to provide a platform for public-private engagement to further dialogue on the capabilities, development, deployment, use, and potential risks of artificial intelligence (AI) in UK financial services.
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.
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.
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.
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.
Following an external recruitment process, the Bank of England (the Bank) has appointed Nicholas Segal as Chair of its Enforcement Decision Making Committee (EDMC), and Peter King as Deputy Chair, with effect from 1 August 2026.
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.
Manuel Gonzalez-Astudillo, Jean-Philippe Laforte, Antoine LepetitPotential output and the natural rate of unemployment are commonly estimated through trend-cycle decompositions, where they are identified as underlying trends reflecting slow-moving supply factors.
