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Is There a Relationship Between Imprisonment and Crime in Western Europe?

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Abstract

This article examines the evolution of prison populations in Western Europe from 1982 to 2011 and its relation with recorded crime trends in the region. Data are taken mainly from the Council of Europe Annual Penal Statistics in the case of prison statistics and the European Sourcebook of Crime and Criminal Justice Statistics in the case of police and conviction statistics, both complemented with the Nordic Criminal Statistics and Eurostat Crime Statistics. The results show that prison populations rates (stock) rose constantly until 2005 and seem relatively stable since then. On the contrary, the annual flow of entries into penal institutions has decreased almost continuously since 1987. This apparent paradox is explained by the fact that the average length of detention has steadily increased during the whole period under study. In brief, less people are sent to prison each year, but they remain in prison for longer periods of time. The upward trend in the average length of detention is related to the development of tough on crime policies across Western Europe and to the increase of drug offences and non-lethal violent crime until the mid-2000s. In that context, an analysis by offence shows similar trends in police, conviction, and prison statistics. These results falsify the hypothesis of total independence between crime trends and imprisonment rates. They also suggest that the deterrent effect of imprisonment has often been overestimated, and they cast a shadow on the validity of criminological theories that place property as the main cause of crime.

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Notes

  1. While in this article the units of analysis are countries, it is also possible to conduct similar studies using states or cities as units.

  2. Ouimet (2012) also found a positive correlation between incarceration rates and homicide rates for the year 2010 and using a sample of 160 countries.

  3. For example, Aebi and Kuhn (2000: 73) “have serious doubts about the veracity” of their findings; while, according to Lappi-Seppäla (2011: 308) “we cannot rule out the possibility that incarceration rates are partly influenced by differences in crime, especially in the East European and Baltic countries. This applies especially to homicide. […] However, it is equally possible that high incarceration and homicide rates are both a product of a third factor. […] This hypothesis deserves further examination in the future”.

  4. In a similar perspective, one of the main critics that Nelken (2009, 2010) addresses to the work of Cavadino and Dignan (2006b) is that they, “like most of those comparing a large range of incarceration rates, spend little time on persuading us that crime rates are really the same in all the countries they are comparing” (Nelken 2010: 61).

  5. The acronym SPACE derives from the French title of this series: Statistiques Pénales Annuelles du Conseil de l’Europe.

  6. The annual SPACE surveys since 2000 are available at www.unil.ch/space (last accessed on 14 December 2014). The previous surveys are available only in paper format.

  7. Available at www.gov.uk/government/organisations/ministry-of-justice/about/statistics. Last accessed on 14 December 2014.

  8. Available at http://ec.europa.eu/eurostat/data/database. Last accessed on 14 December 2014.

  9. Imagine a country in which ten persons enter into prison every year, of which two persons are sentenced to 5 years, two to 4 years, two to 3 years, two to 2 years, and two to 6 months. If one places this figures on a spreadsheet, it can be seen that, from the 5th year onward, the prison population of that country would be stable at 29 prisoners yearly. Thus, the stock of that hypothetical country is 29 and the flow 10, while the average length of the sentences is 2.9 years (5 + 5 + 4 + 4 + 3 + 3 + 2 + 2 + 0.5 + 0.5 = 29÷10 = 2.9). This means that knowing two of these numbers is it always possible to calculate the third one through the above formula. For example, with a stock of 29 and a flow of 10, the average length can be calculated by dividing the stock by the flow (29÷10) as 2.9 years or 34.8 months (2.9*12).

  10. “Geometric means are often more meaningful than arithmetic means, because they are closer to the central figure (median). […] To calculate the [geometric] mean of n numbers, […] multiply them, then take the n th root” (Taagepera 2008: 120). According to Dodge (1993: 248–9), the geometric mean is used in particular to calculate the average of ratios and reduces the influence of extreme values (outliers). Thus, it seems particularly appropriate for the data analyzed in this article, which include rates per 100,000 population and some outliers. In the field of crime trends, the geometric mean have been used namely by Eisner (2003) and Pinker (2011: 64).

  11. Linear interpolation and extrapolation are the standard procedures for the replacement of missing data, which are used, for example, by the World Health Organization for the calculation of regional averages of homicide according to health statistics (WHO 2014).

  12. Belgium, Denmark, England and Wales, Finland, France, Ireland, Italy, Netherlands, Northern Ireland, Norway, Portugal, Scotland, Spain, and Sweden.

  13. This means that data on the distribution of the sentenced prisoners by offence as well as offences recorded by the police are available for England and Wales, Finland, France, Norway, Portugal, Scotland, Spain, and Sweden.

  14. It was impossible to include assault figures for England and Wales because of several major modifications in the legal definition and the statistical counting rules of that offence, which have increased artificially the number of assaults recorded by the police. Similarly, no reliable police data were available for theft and drug offences in Spain. Drug offences correspond to drug trafficking in England and Wales and to the total number of drug offences in the rest of the countries included in the analysis. Homicide corresponds to intentional homicide excluding attempts.

  15. Conviction data for 2011 were not yet available for most countries. Data on persons convicted usually includes attempts.

  16. Only the rate of persons convicted for drug offences registered a higher increase than the rate of police recorded drug offences.

  17. As mentioned in the section on Data and methods, no reliable data on police recorded assaults were available for England and Wales.

  18. Data on persons convicted for robbery in France were not available.

  19. The reader interested in such explanations can consult the essays collected by van Dijk et al. (2012) and Tonry (2014a). Solivetti (2010) has also provided a multivariate explanation that pays particular attention to the integration of foreigners in Western Europe.

  20. Nelken (2010: 56–70) has clearly addressed the issues at stake in the debate on punitiveness in industrialized societies, and the complexity of such a debate from a cross-national perspective.

  21. For a review of the main explanations proposed by researchers, see Blumstein and Wallman (2006) and Zimring (2007).

  22. See van Dijk (2006, 2008), van Dijk et al. (2007), Rosenfeld and Messner (2009) and Tonry (2010).

  23. See, for example, Farrell et al. (2011), Knepper (2012), and most of the essays collected by Van Dijk et al. (2012) and Tonry (2014a).

  24. Only England and Wales seems to be experiencing a general crime drop since the 1990s (Britton et al. 2012).

  25. The evolution of offences involving the use of guns deserves particular attention. As mentioned before, Tonry (1999) considers that the main difference in crime between Europe and the United States is that the US rates of homicides, robberies, and assaults involving guns are substantially higher than in Europe. In this perspective, serious violent crime involving weapons has decreased by 26 % in the United States from 2002 to 2011 (Truman and Planty 2012: 2). In Europe, in 2002/3, the police forces of England and Wales recorded 10,248 offences involving firearms; while in 2012/13 that number decreased to 5094 (Office for National Statistics 2013). In France, police statistics show that robberies with a firearm increased from 6500 in 1987 to 11,000 in 1993, and decreased after that until reaching in 2005 a lower level than in 1987; a similar trend was observed in prosecution statistics as the number of persons prosecuted for armed robberies decreased from 4200 in 1994 to 2500 in 2005 (Kensey 2007: 104). In our opinion, this decrease in the use of firearms could be one of the explanations of the contradiction between the decreasing homicide rates and the increasing rates of non-lethal violent offences in France. Indeed, the presence of a gun has a clear influence on the fatal outcome of cases of assault and domestic violence (Cook and Moore 1999: 281, with references). As a consequence, the decrease in lethal violence could be due to the decrease in the use of firearms. Indeed, as France shows in this respect the same general trends as Western Europe, the authors of this study are currently extending this kind of analysis to the rest of Europe.

  26. For example, the analysis of Lappi-Seppälä (2012: 213) shows that, in Finland, from 1998 to 2005, the length of uncustodial prison terms imposed by the courts for aggravated assault increased by 30 %, but for sexual offences the increase was 17 % and for aggravated drug offences 16 %, while the author provides no information on the length of the sentences imposed for property offences. Even if the analysis of Lappi-Seppälä (2012) also starts from a premise (i.e., the characteristics of the offences judged by the courts have been identical during the period under study), it seems plausible to accept —at least as a working hypothesis— that trends in the average length of detention vary across offences.

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Aebi, M.F., Linde, A. & Delgrande, N. Is There a Relationship Between Imprisonment and Crime in Western Europe?. Eur J Crim Policy Res 21, 425–446 (2015). https://doi.org/10.1007/s10610-015-9274-x

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