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Does Mandatory Diversion to Drug Treatment Eliminate Racial Disparities in the Incarceration of Drug Offenders? An Examination of California’s Proposition 36

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Abstract

Objective

This paper addresses previous shortcomings in the literature on racial disparities in incarceration for drug offenders by taking advantage of a change in sentencing policy in California and a rich administrative dataset that is able to create a sample of comparable White and Black offenders.

Method

We use a nonparametric propensity weighting approach to identify similarly situated White and Black male offenders charged with drug-related offenses. We combine this approach with a difference-in-differences model to estimate the effect that a change in California sentencing law for convicted non-violent drug offenders had on racial disparities in prison and drug treatment dispositions.

Results

We find substantial reductions in the probability of a prison sentence after the policy change, but not differentially for Blacks. Blacks remain more likely to go to prison than similarly situated Whites after the policy, although the policy does lead to more referrals to treatment for Blacks.

Conclusions

This paper shows that even after comparing Blacks and Whites in similarly situated contexts that racial disparities in prison commitments remain after sentencing law changes that mandate diversion to drug treatment. The results suggests that addressing racial gaps in the commitments to state prisons will likely require more than shifting the eligibility of drug convictions for prison, as accumulated criminal histories are the primary driver of prison sentences. This means that expanding diversion options from prison alone will not reduce the racial gap in commitments to prison for drug offenses more than incrementally.

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Notes

  1. (http://bjs.ojp.usdoj.gov/content/glance/tables/corr2tab.cfm).

  2. On May 27, 2005, California’s Supreme Court ruled that driving under the influence of an illicit drug would not be an eligible offense and offenders could not be sent to treatment in lieu of prison.

  3. http://www.adp.ca.gov/sacpa/prop36.shtml, accessed 12/16/2011.

  4. http://www.adp.ca.gov/DrugCourts/overview.shtml.

  5. Three-month moving averages are weighted .5 for the current and .25 for the previous and subsequent months.

  6. The single largest other ethnic group to compare comprised of Hispanic males. The Hispanic-White disparities in outcomes were less pronounced in the unadjusted data.

  7. Cal DOJ provided the list of Proposition 36 eligible offenses that linked to health and safety code violations.

  8. Because our sample of arrests is drawn from a random sample of criminal histories, the same individual can appear multiple times in our sample of drug arrests. What this also means is that these individuals with repeat arrests are accumulating longer and potentially more severe criminal history records, which may affect the likelihood of diversion as well as prison dispositions especially over time.

  9. An additional 12 % (n = 13,077) of cases were removed because of a coding error, which made it impossible to tell whether the arrests occurred before or after the court dispositions. Including these cases in the analysis, however, did not materially change the results. In fact, the effective sample size for our matched sample of Whites was larger (n = 8517) when we excluded this coding error cases than when we included them (n = 8,055).

  10. The severity index is a measure used by Cal DOJ to describe the severity of a given offense with 1 equaling murder and 72 representing misdemeanor offenses.

  11. Some argue that race cannot be construed as a causal variable because it cannot be manipulated. We adopt a less conservative framework along the lines cited by the National Academy of Sciences and argue that after controlling for all confounding observables that we provide “a framework in which causal statements about nonmanipulable variables such as race are possible” (National Research Council 2004; p.79). See related arguments from Paternoster and Brame (2008) in their study of racial disparity in Maryland’s use of the death penalty.

  12. Blacks, for example, were more likely to come from urban counties. After weighting on the propensity scores, however, cases are balanced on county-level variation. The results are available from the authors.

  13. The effective sample size is calculated by \({\text{ESS}} = \frac{{\left( {\sum\limits_{{i \in {\text{comparison}}}} {w_{i} } } \right)^{2} }}{{\sum\limits_{{i \in {\text{comparison}}}} {w_{i}^{2} } }}.\)

  14. Kang and Schafer (2007) argue that using propensity score weights can be unstable, but Ridgeway and McCaffrey (2007) demonstrate that this is largely due to the use of parametric logistic regression models for estimating the propensity score rather than a deficiency in the method itself. Our use of the boosted nonparametric logistic regression model to estimate the propensity score avoids these issues. Our single largest weight (=23) is equivalent to a propensity score of 0.959 (w = p/1−p), bounded some distance from 1.0 where instability might arise. Furthermore, our ESS computation shows that we retain substantial information in our dataset.

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Acknowledgments

The authors gratefully acknowledge comments from RAND’s Drug Policy Research Center’s brownbag seminar series, the NBER Summer Institute Economics of Crime Working Group participants, Christopher Carpenter, and Patrick Bayer for comments on earlier drafts of this paper. Finally, we would like to acknowledge Joseph Hayes from CDCR for his help. Points of view are those of the authors and do not reflect the opinions of NIDA or the RAND Corporation.

Funding

Support for this project was provided by the National Institute on Drug Abuse (NIDA) (grant R01DA022719).

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Authors and Affiliations

  1. 20 Park Plaza, Suite 920, Boston, MA, 02116, USA

    Nancy Nicosia

  2. University of Pennsylvania, 3718 McNeil, Suite 483, Philadelphia, PA, 19104, USA

    John M. MacDonald

  3. 1776 Main St., P.O. Box 2138, Santa Monica, CA, 90407-2138, USA

    Rosalie Liccardo Pacula

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  1. Nancy Nicosia
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  2. John M. MacDonald
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Correspondence to John M. MacDonald.

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Nicosia, N., MacDonald, J.M. & Pacula, R.L. Does Mandatory Diversion to Drug Treatment Eliminate Racial Disparities in the Incarceration of Drug Offenders? An Examination of California’s Proposition 36. J Quant Criminol 33, 179–205 (2017). https://doi.org/10.1007/s10940-016-9293-x

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