Latviešu valodas versija nav pieejama
Lucas Ter Steege
- 19 November 2025
- MACROPRUDENTIAL BULLETIN - ARTICLE - No. 32Details
- Abstract
- The severity and the plausibility of stress test scenarios are crucial elements for interpreting the results and ensuring the credibility of stress-testing exercises. This article introduces a comprehensive framework for assessing scenario severity and plausibility in the context of the adverse scenarios used in the EU-wide stress tests. Two families of indicators are developed, characterised by a backward-looking and a forward-looking perspective. Backward-looking indicators compare the scenario with historical regularities, using as key metrics deviations from baseline projections and comparisons with the extreme values of key variables. Forward-looking indicators are drawn from macroeconomic modelling and compare the scenario with projected distributions about future economic developments incorporating the co-movement of variables within a unified analytical framework. These forward-looking metrics enable the severity assessment to account for the prevailing financial conditions and the level of systemic risk in the economy. The analysis presented suggests that the adverse scenarios used in the EU-wide stress tests have become more severe over time, peaking in the 2023 exercise and stabilising in 2025. Taking into account systemic risk, the 2025 scenario appears to be slightly more severe than the 2023 scenario. Overall, the article supports the idea of fostering a more effective definition, monitoring and communication of scenario severity, thereby strengthening the policy relevance and transparency of stress-testing exercises.
- JEL Code
- C53, C54, E37, G18 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
- 12 September 2025
- WORKING PAPER SERIES - No. 3108Details
- Abstract
- In contrast to the conventional Fisherian view that inflation reduces real debt positions, we show that significant increases in inflation are strongly associated with financial crises. In the spirit of Jordà et al. (2020), countries with free and fixed ex-change rates can be compared to difference out the confounding reaction of monetary policy. Across a dataset of 18 advanced economies over 151 years, we show that the impact of inflation extends beyond its indirect effect via monetary policy. To further corroborate causality, we instrument inflation with oil supply shocks, finding that a 1pp rise in inflation doubles the probability of financial crisis from its sample average. We give evidence for the redistribution channel, where inflationary shocks directly cut real incomes, as a possible mechanism. In conjunction with recent literature on the dangers of rapidly tightening monetary policy, our results point to a difficult trade-off for central banks once inflation has risen.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G01 : Financial Economics→General→Financial Crises
- 21 October 2024
- WORKING PAPER SERIES - No. 2991Details
- Abstract
- We study the application of approximate mean field variational inference algorithms to Bayesian panel VAR models in which an exchangeable prior is placed on the dynamic parameters and the residuals follow either a Gaussian or a Student-t distribution. This reduces the estimation time of possibly several hours using conventional MCMC methods to less than a minute using variational inference algorithms. Next to considerable speed improvements, our results show that the approximations accurately capture the dynamic effects of macroeconomic shocks as well as overall parameter uncertainty. The application with Student-t residuals shows that it is computationally easy to include the COVID-19 observations in Bayesian panel VARs, thus offering a fast way to estimate such models.
- JEL Code
- C18 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Methodological Issues: 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
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
- 10 May 2024
- OCCASIONAL PAPER SERIES - No. 347Details
- Abstract
- This paper presents the updated macroprudential stress test for the euro area banking system, comprising around 100 of the largest euro area credit institutions across 19 countries. The approach involves modelling banks’ reactions to changing economic conditions. It also examines the effects of adverse scenarios as defined for the European Banking Authority’s 2023 stress test on economies and the financial system as a whole by acknowledging a broad set of interactions and interdependencies between banks, other market participants and the real economy. Our results highlight the resilience of the euro area banking system and the important role banks’ adjustments play in the propagation of shocks to the financial sector and real economy.
- JEL Code
- C30 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→General
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
C54 : Mathematical and Quantitative Methods→Econometric Modeling→Quantitative Policy Modeling
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy