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The effects of police contracting on crime: An examination of Compton, California

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Abstract

Objectives

The utility of police consolidation, and in particular police contracting of services, has received widespread attention in academic and practitioner circles. However, the bulk of empirical research centers on potential fiduciary benefits; only limited scholarship has explored the possibility that changes in police services may correspond with differences in crimes solved and offenses observed. To address this gap, we examine consolidation in police services in a historically high crime, disadvantaged urban setting (Compton, California), which began contracting with the Los Angeles County Sheriff’s Department (LACSD) after the closure of Compton Police Department in 2000.

Methods

Independent samples difference in means tests are used to examine variations in crime clearance rates prior to and following the transition in Compton. Group-based trajectory analysis combined with difference-in-difference regression estimation is used to assess changes in criminal offenses while minimizing selection differences in comparison settings.

Results

With the exception of homicide, clearance rates for six Part I crimes experienced statistically significant improvements in Compton’s post-contractual period. Additionally, while the vast majority of Part I offenses remained stable during the transition to LACSD policing, burglary crime rates experienced a statistically significant and sustained decline, net of controls.

Conclusions

A primary concern with police contracting centers on a lack of local police control, disconnect between local needs and actual services provided, and the potential for backlash related to a reduction in the quality of police services. Our findings from Compton suggest that contracting with a well-resourced agency experienced in police consolidation has the ability to maintain and, in some circumstances, improve the quality of law enforcement services.

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Notes

  1. Of the 13 sites that provide contractual services to other agencies listed by the WHE, 12 are in California (Fontana, Moreno Valley, Santa Clarita, Jurupa Valley, Rancho Cucamonga, Lancaster, Palmdale, Thousand Oaks, Victorville, Norwalk, Temecula, Pompano Beach, and Compton) and one is in Minnesota (Wright County).

  2. Fontana (CA), Jurupa Valley (CA), Moreno Valley (CA), Santa Clarita (CA), Wright County (MN), and Norwalk (CA) all provide local as well as external services, or are integrated with another police force (Temecula, CA).

  3. All of these early-onset sites are within California and all began contracting with a partner agency in 1977 or earlier (Rancho Cucamonga, Lancaster, Palmdale, and Victorville).

  4. Pompano Beach (FL) began contracting with Broward County Sheriff’s Office in 1999. When examining Pompano Beach’s crime rates relative to other urban settings in 1998 (the year immediately preceding the contractual year), the city was in the bottom quartile (lower 25%) for both property and violent crime rates.

  5. One potential explanation for the decreased clearance rate in homicides (relative to all other Part I crimes) is the history of gang homicides in Compton (Kennedy 2009). A retrospective assessment shows that gang homicides were a considerable problem in Compton at the time when the LACSD began policing the city. Where gang homicide data exist (using LACSD data), as many as 64 of the 66 homicides in Compton (97%) were classified as gang related in 2005. Thus, it is likely that the dynamics of gang homicides in Compton were a considerable challenge to homicide clearance rates, at least early in the consolidation period. Indeed, LACSD homicide rates in Compton were never higher than 35% between 2000 and 2005, but were higher than 40% each year after 2006.

  6. The standard likelihood ratio test is based on the following formula: 2(ll(model b) – ll(model a)), where ll is the log likelihood of a given model for comparison. This statistic is distributed chi-squared with degrees of freedom equal to the difference in the number of degrees of freedom between the two models.

  7. Our initial start value specification was performed by using the “start” command in Stata (incorporating the intercept and end values from the initial model output into the code), which was followed by the “detail” command to visually inspect the minimization of iterations and to ensure that optimal model selection was performed. As an addendum to this step, we used the “altstart” command in Stata to randomize the start values as a further sensitivity test and the results were robust to suboptimal model selection. This is likely due to the fact that the model was quite simple (a latent growth curve model with a linear functional form). Hipp and Bauer (2006: 43) showed that the use of multiple start values is particularly important for growth mixture modeling (GMM) with more complex functional forms, such as those that include random effects, though less of a concern for more simplistic models (latent class growth analysis models).

  8. The fixed effects model comparisons show that the log likelihood value for the burglary model is a statistically significant improvement (relying on the chi-square distribution) against all other models. For example, when comparing the burglary model log likelihood to the homicide model log likelihood, we take 2*(− 16,869 − (− 17,890) = 2042. We compare the observed difference with the difference in degrees of freedom (77 − 6 = 71), which has an expected chi-square value of roughly 90.5 (p < 0.05). Given that the chi-square value observed here is larger than the expected chi-square value, this indicates the burglary model to be a significant improvement when compared to the homicide model. The same is true when comparing burglaries to the remaining five UCR outcomes.

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Authors and Affiliations

  1. University of Cincinnati, Cincinnati, OH, 45220, USA

    Nicholas Corsaro

  2. Michigan State University, East Lansing, MI, USA

    Jeremy M. Wilson

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  1. Nicholas Corsaro
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Correspondence to Nicholas Corsaro.

Additional information

This project was supported by award no. 2013-IJ-CX-0019, awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice. The opinions, findings, and conclusions or recommendations expressed in this presentation are those of the authors and do not necessarily reflect those of the Department of Justice.

Appendix

Appendix

Table 6 Sensitivity tests (fixed effects negative binomial regression models)
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Fig. 2
figure 2

Synthetic control analysis of the burglary crime rate in Compton, 1985–2012

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Corsaro, N., Wilson, J.M. The effects of police contracting on crime: An examination of Compton, California. J Exp Criminol 14, 59–81 (2018). https://doi.org/10.1007/s11292-017-9310-6

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