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  1. Prison population projectionsa cautionary perspectiveCrime and justice statistics user dayMarch 2012Sarah Armstrong (University of Glasgow)Elizabeth Fraser (Scottish Government Justice Analytical Services)

  2. Scottish prison population - the history

  3. Scottish prison population - current drivers

  4. Why do long term prison projections? • Anticipate future need and plan development of prison estate • Inform policy development - but this is only part of the story

  5. How we do the projections • Sentenced receptions projected for adults and young offenders • A range of time periods in order to account for changes in trend over time • Time series analysis based on linear regression and exponential smoothing • Six variants reflecting the overall trends over the short (10 years), medium (25 years) and long (40 years) term: which best reflects the current situation? • Need to compensate for inherent volatility over time, particularly for the smaller groups

  6. Projections - special groups • Remand receptions are particularly volatile and projected as proportion of direct sentenced receptions • Recalls from licence projected as a proportion of the long-term population as It is very difficult to estimate how long such prisoners will remain in custody

  7. Some issues • Projections are based on assumptions about how the past relates to the future can be used for planning or cautionary tales • If the future is uncertain, the one thing one can be sure of is that the projections will be wrong to some extent • Sometimes the past may be misleading as well...

  8. Long term projections (receptions)

  9. Population projections to 2019-20

  10. Accuracy of long term projections

  11. Other population modelling • Short term monthly projections • quick to produce, seasonally adjusted • still very volatile with large margin of error • useful for emphasis • Bespoke modelling of potential policy impact • shows scale and sensitivity to base assumptions • timely and transparent • Mathematical modelling • can we improve the mathematical fit and quantify the underlying uncertainty?

  12. Short term monthly projections

  13. Scenario modelling

  14. Scary mathematical model NB. mean & variance satisfy the same equations

  15. Mathematical model - forecast

  16. Context is important - short sentences

  17. Policy does not occur in a vacuum

  18. Are prison populations appropriate phenomena for forecasting?

  19. Projected and actual population England & Wales 2001

  20. Three questions • Are drivers of prison growth like hurricanes or health care? • What effects do projections have? • What other options are there?

  21. Like hurricanes or health care? • Defined drivers are unpredictable and unconnected to demographic change • Other possible drivers excluded: prisons and projections

  22. What effects do projections have? • Are there any costs of getting it wrong? • Power to make a future while estimating futures • Quantification of fear?

  23. Other options? • Within statistics, ‘What If’ planning models • Outwith statistics, ‘That’s What’ planning models

  24. Wha’s like us?

  25. “In our grammar we have the future tense, which enables us to imagine and visualize a state of affairs different from the presently existing – a ‘matter’ with quite different ‘facts’… the only way of ‘predicting’ the future [is] to join forces and pool our efforts to cause future events to conform to what we desire.” (Zygmunt Bauman) S Armstrong (2012) ‘The Quantification of Fear through Prison Population Projections’ available at: www.sccjr.ac.uk