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Antoine Sigwalt
- 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
- 30 June 2025
- OCCASIONAL PAPER SERIES - No. 371
- 31 July 2024
- ECONOMIC BULLETIN - ARTICLEEconomic Bulletin Issue 5, 2024Details
- Abstract
- This article provides a technical evaluation of the performance of ECB/Eurosystem staff inflation projections since 2000. It complements the existing literature by examining the influence of HICP components as well as conditioning variables on the properties of HICP inflation projections, also taking into account potential time variation in forecast performance. The article shows how, from the low projection errors over the period leading up to the pandemic, Eurosystem/ECB staff forecast accuracy deteriorated in the face of atypical post-pandemic shocks before improving again since late 2022. However, it finds that the accuracy of Eurosystem/ECB staff projections of headline HICP inflation is broadly comparable to real-time market-based and private professional forecasts even after including the post-pandemic period of high inflation. The HICP forecast accuracy is comparable across main HICP components, including HICP excluding energy and food (HICPX), although HICPX inflation projections tend to show smaller errors than headline inflation projections. The article finds that ECB/Eurosystem staff inflation projections are unbiased overall but exhibit specific periods over the last 25 years in which this unbiasedness broke down. It also points to some rigidities in ECB/Eurosystem staff inflation projections, in particular for HICPX, which might explain part of this occasional bias. Finally, the article underscores the contribution of not only oil price assumptions but also other conditioning assumptions to the rigidities, occasional bias and reduced accuracy of ECB/Eurosystem staff projections of HICP inflation.
- JEL Code
- C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies