Throughout a forecast process the OBR, in conjunction with other government departments, uses a number of approaches to understand uncertainty in our fiscal forecasts. This box set out these approaches in detail and looked at those taken when incorporating the fiscal impacts of new policy announcements.

In each Economic and fiscal outlook (EFO) we consider the risks and uncertainties around the forecasts of key fiscal aggregates – such as borrowing and debt – through the use, as set out above, of fan charts, alternative scenarios, sensitivity analysis, and specific risk assessment sections. This often builds on analysis produced for the economy forecast and explains how aggregate level macroeconomic risks could affect the overall fiscal forecast. In addition, the forecasts of the fiscal aggregates are built up through forecasts produced by government departments for all the individual elements of tax and spending. We engage continuously with these departments to understand the uncertainties in their forecasts that are not related to those that we consider at the aggregate level. Throughout the forecast process we use several approaches, in conjunction with departments, to understand these uncertainties:

  • Challenge meetings are held for most tax and spending forecasts at least once during a forecast process, where departmental analysts present their central forecasts and the key uncertainties and risks around these for the OBR to scrutinise. We take a proportional approach to assessing these risks based on the complexity and size of the individual forecast components.
  • Model returns are often compared against ready reckoner tools to test the sensitivity of a forecast to key economic assumptions. Where there are material deviations from what we would expect given economic changes, we will highlight and explain the reasons disaggregated into individual fiscal forecast factors.
  • Sensitivity analysis is presented around some individual tax and spend forecasts to explain the impact of material fiscal forecast judgements. Examples of this have included the impact different electric vehicle uptake assumptions on the transport taxes forecasts and different scenarios for the underspend assumption within the departmental expenditure limits (DELs) forecast.
  • We work closely with departments on in-year monitoring of tax and spend data to track the performance of our forecast against latest outturn data, based on our published monthly profiles. We hold regular meetings throughout the year to understand if differences are temporary or structural and the uncertainty that these differences may create for individual forecast areas at our next forecast. We also use tools such as the FER to analyse overall differences from outturn.

We also with work with departments to make further assessments of risk and uncertainty when we incorporate the fiscal impact of new policy announcements into the forecast:

  • Costing notes written by the responsible departments provide a detailed analysis and assessment of the fiscal impact of each new policy and contain a section on the key assumptions and uncertainties, maintaining a proportional approach to the size and complexity of the policy. Departmental analysts will also often provide sensitivity analysis of key assumptions and the impact of alternative assumptions.
  • Based on costing notes and engagement with departments we assign an uncertainty rating to all policy costings supplied to us following the costings engagement outlined above.a We assign uncertainty rankings for each of three components of the costing – data, behaviour and modelling – highlighting the largest concern of these three components and assigning an overall uncertainty rating. In the EFO we specifically highlight the measures that we have deemed to have an overall ‘high’ or ‘very high’ uncertainty rating.

This box was originally published in Forecast evaluation report – July 2025

a See our policy costings uncertainty ratings database for a measure-by-measure breakdown of uncertainty ratings for all policy costings since December 2014.