INFORM2, DWP’s main forecasting model for Universal Credit
INFORM2 is a dynamic microsimulation model developed within the Department for Work and Pensions (DWP) for forecasting claim volumes that underpin the benefit expenditure forecast for Universal Credit. Development began in 2018 and builds on earlier iterations of the INFORM framework. The model simulates independent benefit units and individuals on a monthly time step, using Universal Credit (UC) administrative data as its core input.
INFORM2 outputs provide a detailed, benefit-unit level simulation of the UC caseload and its composition for Great Britain over the medium term. Its design allows results to be broken down by UC eligibility rules including age, health and carer status, family composition, housing costs, and work and earnings patterns. This detailed compositional information is crucial not only for accurate and consistent estimation of caseloads but also estimating the average benefit amounts that complete the expenditure forecast.
The model integrates onflows synthesised from historical data across both UC and the six “Legacy” working age benefits that UC replaces, simulating new claims, transitions from the Legacy system, and the complex flow dynamics at the margin of benefit entitlement and take-up. Internal transition- and off-flow-probabilities are handled using a combination of discrete probability matrices and logistic regressions in addition to deterministic ageing rules, for example when claimants move to the pension-age Benefits.
A range of structural and data constraints shaped the development of the model. Although 2019 offered the first full year where UC was fully rolled out to new claims, the system was still far from steady state: the legacy stock remained substantial, transitions were immature; and these behavioural patterns risked biasing estimated probabilities. COVID19 added further complexity by disrupting labour market dynamics to such an extent that the modelling data could not be robustly updated until 2022-23, when operational and claimant behaviour appeared to be stabilising. Even then, major increasing pace of Legacy-to-UC transition, and economic and policy changes continued to produce new discontinuities that required substantial development work. For example, the earnings modelling was refined separately up to 2024-25 to account for substantial changes in earnings distributions and conditionality rules.
Several research and development strands are in progress. A major one, investigated through a co-sponsored PhD study with the Centre for Microsimulation and Policy Analysis the Centre for Microsimulation and Policy Analysis at The University of Essex is the incorporation of economic forecasts into INFORM2 modelling, via a new onflows model estimated on the link between UC onflow volumes to unemployment rates, levels of benefit and working-age population changes. Also, machine‑learning techniques such as neural networks are being explored as alternatives to the increasingly large DPM structures used in the current off‑flows module.
INFORM2 is a highly significant model in Government, and is receiving increased scrutiny at all levels of Government, placing high value on explainability of its outputs, which is challenging to balance alongside the appetite for accuracy and detail that a microsimulation model affords.