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Assessing Substitution and Complementary Effects Amongst Crime Typologies

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Abstract

This paper aims at assessing how offenders allocate their effort amongst several types of crime. Specifically, complementary and substitution effects are investigated amongst the number of recorded homicides, robberies, extortions and kidnapping, receiving stolen goods, falsity and drug-related crimes. Furthermore, the extent to which crime is detrimental for economic growth is also analysed. The case-study country is Italy, and the time span under analysis is from the first quarter of 1981 to the fourth quarter of 2004. A Vector Error Correction Mechanism (VECM) is employed after having assessed the integration and cointegration status of the variables under investigation. Empirical findings show that, in the long run, an increase in the overall welfare has a negative impact on the most serious crimes. In addition, the long-run elasticities reveal symmetric results in terms of positive and negative relationships amongst types of crime. In the short run, the cross-deterrence elasticities highlight a complementary effect between more serious crimes (i.e. robberies, extortions and kidnapping) and milder crimes (i.e. drug-related crimes and falsity) and a substitution effect amongst all other types of offences. Policy implications are drawn.

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Notes

  1. “Social psychologists and police officers tend to agree that if a window in a building is broken and is left unrepaired, all the rest of the windows will soon be broken. This is as true in nice neighbourhoods as in rundown ones. Window-breaking does not necessarily occur on a large scale because some areas are inhabited by determined window-breakers whereas others are populated by window-lovers; rather, one unrepaired broken window is a signal that no one cares, and so breaking more windows costs nothing.” Wilson and Kelling (2000, p. 2).

  2. Solving Eq. (1) by substituting Eq. (2), and given Eqs. (3) and (4), we find:

    $$ {t_a}h\left( {1-{p_a}{q_a}} \right)+{t_b}k\left( {1-{p_b}{q_b}-{p_c}{q_c}} \right)+{t_d}y $$

    Given the perfect linearity of the utility function, we can have only corner equilibria. Comparing the different possible equilibria, it is possible to identify the thresholds of each type of crime specialisation as shown in solutions (5), (6), and (7).

  3. Notably, the annual series of Mafia-related homicides and total number of homicides are highly correlated (ρ = 0.975). Precisely, the share of Mafia homicides over the total number ranges between 14 % and 37 % during the 1984–2006 period. It is empirical evidence of the fact that homicides “constitute the main instrument through which [criminal] organisations exert the monopoly of violence” (Pinotti 2012).

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  1. Department of Economics (DiSEA) and CRENoS, University of Sassari, Via torre tonda, 34, Sassari (Sardinia), Italy

    Claudio Detotto & Manuela Pulina

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  1. Claudio Detotto
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  2. Manuela Pulina
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Correspondence to Claudio Detotto.

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Detotto, C., Pulina, M. Assessing Substitution and Complementary Effects Amongst Crime Typologies. Eur J Crim Policy Res 19, 309–332 (2013). https://doi.org/10.1007/s10610-013-9196-4

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