Prison population projections a cautionary perspective Crime and justice statistics user day March 2012 Sarah Armstrong (University of Glasgow) Elizabeth.

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Presentation transcript:

Prison population projections a cautionary perspective Crime and justice statistics user day March 2012 Sarah Armstrong (University of Glasgow) Elizabeth Fraser (Scottish Government Justice Analytical Services)

Scottish prison population - the history

Scottish prison population - current drivers

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

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

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

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...

Long term projections (receptions)

Population projections to

Accuracy of long term projections

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?

Short term monthly projections

Scenario modelling

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

Mathematical model - forecast

Context is important - short sentences

Policy does not occur in a vacuum

Are prison populations appropriate phenomena for forecasting?

Projected and actual population England & Wales 2001

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

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

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

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

Scenario A = Scottish Prisons Commission target (91) Scenario B = Norway becomes penal model for Scotland (78) Scenario C = USA becomes penal model for Scotland (200) Wha’s like us?

“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: