Developing long-term pensioner microsimulation modelling in Great Britain with a mixed discipline team

The Department for Work and Pensions (DWP) is responsible for welfare, pensions and child maintenance policy. It administers the State Pension and a range of working age, disability and ill health benefits to around 20 million claimants and customers. This makes it directly responsible for over £300 billion of expenditure every year (equivalent to €340bn or $410bn), as well as providing the regulatory framework for over £2 trillion of private pension assets.

People spend most of their lives either paying into a pension or benefitting from it, so the impact of any policy reform unfolds over several decades. The modelling used to provide the evidence base for reform needs to cover that timescale and take in to account a wide variety of life factors including employments, benefit claiming, pensions (accumulation and decumulation), wealth, health, disability, births and deaths. The Department’s current long term dynamic microsimulation model, Pensim3, has underpinned the evidence base for every major state and private pension reform over the past two decades. However, new administrative and survey data sources, alongside improved microsimulation techniques, have created opportunities for a modernised approach.

In response, DWP has undertaken an ambitious programme to build a new dynamic microsimulation model, SimPLE, to simulate the entire Great Britain population on an annual time step. The model integrates multiple data sources at the starting point and implements regression-based rules to project long term outcomes. SimPLE is nearing completion, with work focused on finalising priority components ahead of an extensive quality assurance phase.

Throughout development, the team has varied in size—from a single modeller to a multidisciplinary group of eight—with staff rotating through promotion, career development and departmental moves. Team members brought mixed levels of prior modelling experience: some with substantial microsimulation expertise, some with general analytical experience, and some entirely new to analytical work. This created challenges in managing the build process and highlighted the importance of:

Knowledge management — clear documentation, code comments and development logs.

Model modularity — common design principles, consistent coding practices, and a single shared model structure.

Training and capability-building — equipping staff with the necessary modelling skills while recognising specialist strengths.

Extensive quality assurance — including structured code reviews, testing and validation of outputs.

While these practices are valuable in any setting, they are especially important in a government department, where teams are multidisciplinary, turnover can be high, and institutional knowledge must be preserved.

This presentation will share our experience of developing SimPLE within this environment, outlining the methods used, the challenges faced, and the steps taken to build long-term modelling capability inside government.