Scenario synthesis bridges BoE risk outlook, policy paths
Bank of England staff have adapted a 'scenario synthesis' approach to rigorously assess how well a set of scenarios collectively captures macroeconomic risks. This methodology connects density forecasts to narrative scenarios, offering insights into inflation and Bank Rate outlooks.
Connecting forecasts to narratives
The scenario synthesis is a statistical framework connecting density forecasts to narrative scenarios.
It assesses how well a set of scenarios collectively captures macroeconomic risks, identifying statistically indistinguishable scenarios or flagging gaps where estimated risks are not covered.
This approach combines a reference distribution, reflecting the overall 'unconditional' risk outlook (from surveys, models, or markets), with a set of projections or scenarios, each expressing a 'conditional' view based on alternative assumptions.
Its outputs are implied scenario weights, quantifying each scenario's contribution to the reference distribution, and a predictive synthesis distribution, a weighted mixture of scenario densities that best matches the reference.
This framework rigorously informs scenario design by indicating statistical relevance and assessing risk coverage across specific segments of the outlook.
Inflation risks broadly captured
The April 2026 Monetary Policy Report (MPR) used Scenarios A, B, and C to model global energy price paths and their second-round effects on the UK economy.
Applying the synthesis to these inflation projections confirmed all three are essential to span the full range of inflation risks.
Synthesized against the Decision Maker Panel (DMP) survey, Scenario B received nearly two-thirds of the weight, Scenario C one-third, and Scenario A near zero, reflecting their statistical alignment.
The combined scenarios span 99% of inflation risks across the central, right, and left segments of the DMP-implied reference.
Omitting Scenario C reduces this coverage to 87%–89%, highlighting its vital role.
Bridging the analytical gap
The scenario synthesis approach offers a rigorous method to evaluate scenario coverage, moving beyond purely qualitative assessments.
While it does not dictate the appropriate policy response, it refines scenario design and highlights uncovered risks.
Its value lies in enhancing the robustness of risk analysis for policymakers, particularly when calibrating and choosing between different scenarios.