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.
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.
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.
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 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.
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.
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.
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.
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.
