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The benefit and cost of prison in the UK. The results of a model of lifetime re-offending

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Abstract

With prisons in the UK reaching full capacity, and with similar trends in other European countries and the USA, there is much political debate about the efficacy of prison and community sentences. This paper aims to inform this debate by testing the hypothesis that prisons are an effective and efficient way of reducing re-offending. A rapid review of effectiveness studies was performed to determine the relative impact of prison and community sentences on re-offending. An economic analysis was undertaken to transform the estimates of effect into estimates of the economic efficiency of alternative sentencing options in the context of the UK. When compared with standard prison sentences, a number of community-based interventions and enhancements of standard prison sentences were found to save money, both for the public sector and for society more broadly. Diverting adult offenders from standard prison sentences to alternative interventions saves the UK public sector between £19,000 and £88,000 per offender. When victim costs are considered, diverting offenders from standard prison sentences saves UK society between £17,500 and £203,000 per offender. It was concluded that standard prison sentences are not an economically efficient means for reducing re-offending.

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Notes

  1. The following search terms were used to interrogate the databases: [(offender* or prisoner*) and (violence and [domestic or person*]) or “partner abuse” or sexual or burglary or robbery or theft or rape* or fraud or paedophilia* or forger* or drug* or motoring or driving] and [conviction or recidivism or arrest* or re-arrest or reconviction or offending] and [discharge* or fine* or compensation or (community and [order*” or service or supervision or sentence*]) or probation or custody or reparation or curfew* or “house arrest” or suspended or surveillance or deferred] or [electronic and (monitor* or tagging)] or [licence or parole or “control order*” or licence* or parole or resettlement or imprisonment or incarcerat* or intervention* or attitude* or thinking or cognitive or “anger management” or “aggression replacement” or “victim aware*” or counsel* or therapy or mentor* or “offender management” or “after care” or “correctional intervention*” or “offender prevention” or restitution or mediation] and effectiv* not [cctv or Africa* or Asia* or India* or “far east” or “south America” or mexico or “middle east” or mediterr*]

  2. The following offence types were included in the analysis: violence, robbery, sexual offences, burglary, theft and handling, fraud and forgery, motoring offences, drug offences and other offences.

  3. The number of offences committed per conviction is calculated as the product of the average number of convictions per recorded offence (source: RDS NOMS 2007) and the average number of offences per recorded crime estimated from data from the British Crime Survey (source: Nicholas et al. 2005).

  4. The model specifies the following crime types: violence, robbery, sexual offences, burglary, theft and handling, fraud and forgery, motoring offences, drug offences and other offences. The sum of the probabilities that a crime is of a particular type is equal to 1.

  5. It is assumed that the offence distribution of community service and community supervision is the same as that for those receiving a community order in the UK, that the distribution of offence types for residential drug treatment and surveillance with drug treatment is the same as that for those receiving a Drug Treatment and Testing Requirement (DTTR) in the UK, and that the distribution of offence types for any prison sentence and surveillance is the same as that for those receiving a custodial sentence in the UK.

  6. The odds ratios estimated in the meta-analysis were converted to relative risks by the following equation: RR = OR/[(1-EC)+(OR.EC)], where RR is the relative risk, OR is the odds ratio, and EC is the baseline risk.

  7. It is assumed that the offence distribution of community service and community supervision is the same as that for those receiving a community order in the UK, that the distribution of offence types for residential drug treatment and surveillance with drug treatment is the same as that for those receiving a DTTR in the UK, and that the distribution of offence types for any prison sentence and surveillance is the same as that for those receiving a custodial sentence in the UK.

  8. The following offence types were included in the analysis: violence, robbery, sexual offences, burglary, theft and handling, fraud and forgery, motoring offences, drug offences and other offences.

  9. The following search strategy was employed to search the databases: (crim* or offend* or reoffend* or recidivis*) and (econ* or cost*) and (benefit*) and (intervention* or outcome*).

  10. It is assumed that the length of community service and community supervision is the same as that for a community order in the UK, that the length of residential drug treatment and surveillance with drug treatment is the same as that for a DTTR in the UK, and that the length of any prison sentence and surveillance is same as that for custodial sentence in the UK.

  11. The confidence intervals around the estimates of net benefit are derived by applying the economic model to the confidence intervals on the estimates of effect derived from the meta-analysis. No other estimates of uncertainty are incorporated into the confidence intervals. Any uncertainty in the other parameters of the economics model are considered in the sensitivity analysis.

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Acknowledgements

The study was funded by the Monument Trust, the Lankelly Foundation and the Bromley Trust. The authors would like to acknowledge the contribution of researchers at The Matrix Knowledge Group, especially Kerry McCarthy and Rashmi Sarmah. The authors would also like to thank Paul Dolan and Carol Hedderman for their comments and support throughput the project.

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  1. The Matrix Knowledge Group, Epworth House, 25 City Road, London, EC1Y 1AA, UK

    Kevin Marsh

  2. Manchester Metropolitan University, Manchester, UK

    Chris Fox

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  1. Kevin Marsh
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Correspondence to Kevin Marsh.

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Marsh, K., Fox, C. The benefit and cost of prison in the UK. The results of a model of lifetime re-offending. J Exp Criminol 4, 403–423 (2008). https://doi.org/10.1007/s11292-008-9063-3

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