Mark Pont, Assessment Programme Lead, Office for Statistics Regulation to John Marais, Acting Chief Statistician, Ministry of Justice.
As you are aware, we recently completed our review of the compliance with the Code of Practice for Statistics of the Ministry of Justice’s Prison Population Projections. This letter confirms that these projections should continue to be designated as National Statistics.
We began this check given the importance of the projections and the length of time since Assessment 7 in 2009, after which their designation of National Statistics was confirmed. We particularly focused on the quality and value of the prison population projections in relation to the Code.
The projections have undoubted value for policy development, capacity planning and resource allocation within the Ministry of Justice and the criminal justice system. Your team told us that it was exploring with the NHS the possibility of enhancing the value of the projections by incorporating projections on prisoner health, and we welcome this kind of development. Evidence given to the Justice Committee’s parliamentary inquiry Prison Population 2022 demonstrates the potential to extend the value of the projections to other audiences. There are areas where we see the potential to develop the value of the statistics further:
- We strongly encourage you to actively seek dialogue with a wider audience, including those contributing to the recent parliamentary inquiry, to understand their needs and help add further value to the projections.
- Given interest in groups of prisoners such as women and young offenders, providing context around the results would also extend their use and enhance their value.
The annual publication provides useful context around the methodology and the model used to simulate population projections. For example, it describes the two different methods used to develop the assumptions on which prison populations projections are based and is transparent about the effect that these two different approaches have. Uncertainty in the projections is clearly illustrated. Comparing previous projections with the current projection, and giving reasons for these differences both provide useful context to the uncertainty. We consider that it may help to further enhance the quality of these projections if you were to publish the headline assumptions of the model and the names of the external experts who contributed to specifying them, to enable greater understanding and provide greater transparency.
Thank you for engaging effectively with us during this short review. I would welcome updates from you as your work proceeds. If you wish to discuss any part of this letter please let me know.