New method guides monetary policy amid economic uncertainty
The Banque de France proposes a statistical method to weigh multiple economic scenarios, rather than relying on a single forecast, to inform monetary policy decisions. This approach addresses the challenges of great uncertainty, building on recent recommendations for central banks.
Weighing multiple futures for policy
Central banks typically base monetary policy decisions on a single baseline macroeconomic projection.
However, this approach has been criticized as insufficient in times of high uncertainty by figures such as Nobel laureate Bernanke, who recommended greater visibility for alternative scenarios.
The European Central Bank's 2025 strategic review also highlighted the usefulness of alternative scenarios for assessing different policy paths.
This post introduces a statistical method that assigns specific weightings to various economic scenarios based on their plausibility.
These weightings are then used to construct a single, synthesized monetary policy path that incorporates both the scenarios considered and their likelihood.
This framework builds on ideas presented by Banque de France Governor François Villeroy de Galhau in December 2025, where a risk management approach based on a weighted synthesis of scenarios was discussed.
Scenarios from trade policy to forecaster views
The Eurosystem's June 2025 macroeconomic projections serve as an example, where significant uncertainty surrounded US trade policy.
This led to the development of baseline, moderate, and severe scenarios, each implying a different optimal monetary policy path.
The proposed method uses an adaptation of the Bayesian predictive synthesis to assess the likelihood of each scenario.
Weightings are adjusted so that the aggregate distribution closely matches an independent baseline forecast, such as the ECB Survey of Professional Forecasters.
Scenarios that best reproduce forecasters' expectations receive higher weightings.
An additional "artificial" scenario is included to account for any incompleteness in the Eurosystem's defined scenarios.
Based on real GDP forecasts for 2026, the baseline and artificial scenarios each received approximately 30% weighting, the moderate scenario 27%, and the severe scenario a more modest 12%.
A pragmatic step, not a paradigm shift
The proposed method offers a more robust framework for monetary policy by explicitly integrating uncertainty, moving beyond the limitations of single-scenario forecasting.
While a significant methodological improvement, its practical impact on actual policy decisions may be limited when dominant scenarios imply similar outcomes, as shown by the June 2025 example.
This approach provides valuable transparency and a structured way to consider risks, but it does not fundamentally alter the core challenges of forecasting in complex environments.