Stuart Grant - Developing long-term pensioner microsimulation modelling in Great Britain

  • Presenting author: Stuart Grant (Department for Work and Pensions, United Kingdom)

  • Authors: Stuart Grant

  • Session: A02A - Dynamic / Long term [1] - Monday 16:30-18:00 - Ceremonial Hall

  • Slides: PDF

The Department for Work and Pensions (DWP) is responsible for welfare, pensions and child maintenance policy. As the UK’s biggest public service department, 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 responsible for over £200 billion of expenditure every year (equivalent to €230bn or $250bn). People spend a huge proportion of their lives either paying into a pension or benefitting from it. As a result, the impact of any policy reform unfolds over several decades and the modelling used to provide the evidence base for reform needs to cover that timescale. Additionally, modelling will need to 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 existing long-term model, Pensim3, has been heavily used, supporting the evidence base for every major state and private pension reform in the last two decades. However, over those decades new data sources have become available and best practice in microsimulation techniques have moved on. It can also be hard for new analysts to pick-up and use. This paper tells the story (so far!) of our work to develop a next-generation long term model in the DWP. It explores potential new data sources and modelling methodologies. Away from the technical implementations, the paper discusses how long-term modelling should be implemented in the 2020s, answering questions like:

  • What is the most helpful functionality in a model looking across 80-100 years?
  • How can we move away from a single model that supplies a single projection in response to a single set of assumptions towards a more holistic suite of tools for exploring policy options?
  • How do we make the tool accessible to analysts, whilst keeping powerful options for analysis?

This “next generation model” is still a work in progress, so don’t expect definitive answers. Instead, I will explore the options we’re considering and the pros and cons of various approaches.