Revisiting Crime Rates as a Measure of Crime Prevention Effectiveness: Does the "Crime Drop" Reveal a Policy Effectiveness 'Outcomes' Gap?

By Ronald F. Pol
2016, Vol. 8 No. 02 | pg. 4/4 |

Policy Implications and Suggestions

The following proposals seek tentatively to offer initial practical suggestions, with brief commentary to aid constructive criticism and help advance new research questions.

  1. Identify ultimate intended outcomes. rates offer a useful measure, and economic cost-of-crime and crime-harm indices usefully complement standard crime rate ‘output’ measures, yet such measures might themselves be characterised proxy ‘output’ measures; as not fully reflecting the harm reduction ‘outcomes’ ultimately intended by crime prevention policies. To demonstrate policy effectiveness, in the sense of the effects or impact of policy initiatives, the next step may involve expressly identifying the ultimate outcomes intended, in terms of the economic and social benefits and reduced harm from less crime.
  2. Develop a practical effectiveness measure based on the ultimate outcomes intended by crime prevention policies. A simple ‘outcomes’ oriented operational metric that connects more directly with the economic and societal benefits of crime prevention offers an alternative measure of crime prevention effectiveness.

Crime rates are effective in part because they are easy to use and understand. Increasingly complex cost-of-crime models suffer from a lack of simplicity, in part because attempts to resolve their complexities often add more layers of complexity, inexorably drifting further from operational usefulness. Tonry concluded that “estimating specific costs of crime does more harm than good, and … for policy purposes an entirely different literature on citizens’ rankings of the seriousness of crimes tells us all we need to know” (Tonry, 2015, p. 665).

It is beyond the scope of this article to map an alternative, but an operationally feasible ‘back to the future’ approach might add the rigour of Thurstone’s paired comparisons (Kwan, Ip, & Kwan, 2000; Thurstone, 1927; Thurstone & Chave, 1929; Torgenson, 1958), updated for complex decision-making by Saaty’s analytic hierarchy process (Saaty, 1980, 1990). Such rankings offer the prospect of a parsimonious solution compared with the “highly complex” (Black et al., 2015) and “pernicious” (Manski, 2015) models based on criminal justice punishment guidelines or the “unhappy relic of a bleak period” (Tonry, 2015) of cost-benefit analyses. Such a method instead produces the prospect of a simple and operationally effective measure based on ranking the perceived harms caused by crime, and the benefits of crime prevention as its inverse; thus more directly targeting the ultimate economic and social benefits and harm reduction outcomes intended by crime prevention policies.

Although he didn’t mention pairwise comparisons, the utility of a method that systematically ranks alternatives to establish rank order is also consistent with Tonry’s “variety of methods” by which “researchers simply ask people what is more serious than what. The answers are robust and consistent across time and space. Economic estimates of the cost of crime are not needed to learn that homicide is more serious than robbery or robbery than shoplifting” (Tonry, 2015, p. 668). Adding pairwise comparisons to the methodology mix avoids the need for respondents to make complex explicit judgments about “marginal changes in crime victimization risks” (Ludwig, 2010, p. 309), or to have detailed knowledge about the incidence of crime and methods of crime control (Tonry, 2015, p. 666). Pairwise comparisons therefore help harness, without becoming ensnared by, the inherent complexities of complicated cost-of-crime calculations; enabling the simplicity necessary for operational usefulness.

This suggested approach may also help policymakers evaluate policy effectiveness more directly against the perceived social benefits and reduced harms from less crime. This is consistent with a "focus on achieving outcomes", ensuring "alignment with policy objectives" (Cabinet, 2014, pp. 1-2, 13), and meeting the 'impacts' and 'outcome' goals expressed as "less crime", "less harm from crime" and "reduced victimisation" (NZ Police, 2012, p. 3; 2014a, p. 3). “Rather than ask how much crime exists, a more appropriate question should be to ask how much harm is caused by crime. Harm has the distinct advantage of being a broader and more realistic measure than a narrowly defined measure based on the criminal law” (Ratcliffe, 2015b, p. 179). Operationalised, this approach would enable resources to be better directed towards preventing the most harmful crime, and further enhances policy effectiveness by offering a more direct line of sight to the effects or impact of modern preventive policing.

Conclusion: Realising Better Crime Prevention Outcomes

Crime rates retain legitimacy as a simple ‘output’ measure because it is often difficult to identify direct links between policy initiatives and crime, but the ongoing development of crime rates as an effectiveness metric has arguably not kept pace with organisational change towards preventive policing models.

Quantifying the social benefits from meeting crime prevention targets, and demonstrating ultimate policy outcomes beyond broad statements about reducing harm and misery is the obvious next step for a police force committed to "using crime science" to "understand the crime problem [and] make sound decisions that lead to good outcomes" (NZ Police, 2015a, p. 25).

Similarly for other jurisdictions that have adopted the resolution to advance a "collaborative agenda" of evidence-based strategies to prevent crime and reduce victimisation (UN ECOSOC, 2002). Rigorously defining and measuring ultimate policy outcomes, in the sense of their intended effects or impact, and implementing crime prevention policies in an operational setting to help direct focus and resources accordingly, may help advance policy intentions to improve public safety and value-for-money, and better outcomes.


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Endnotes

1.) In similar vein, reduced recidivism rates was also claimed to be a “clear” sign that ‘three strikes’ legislation helps “deter and prevent serious violent offenders from committing crimes” (Adams, 2015b). The legislation may have had that effect, or it may reflect a general crime drop, or a combination of these and other factors. Simple ‘before and after’ observations alone are insufficient to attribute a direct causal link between the policy intervention and subsequent recidivism rates.

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