Did Drug Courts Lead to Increased Arrest and Punishment of Minor Drug Offenses?

Abstract

Drug courts were implemented nationwide during the 1990s to expand alternatives to incarceration for individuals with substance use disorders that were charged with nonviolent felonies or misdemeanors. Although these courts were publicized as a facilitator of treatment and alternative to incarceration, researchers and advocates have suggested that this approach may have unintentionally intensified law enforcement focus on casual drug users and individuals with minor substance dependency. The primary objective of this study was to determine whether there is evidence that drug courts systemically increased the arrest and punishment of misdemeanor drug use and possession by conducting a series of panel data analyses among more than 8,000 city and county jurisdictions while controlling for economic, demographic, and nationwide law enforcement trends. Analyses in this study provide evidence that local police increased their attention toward minor drug offenses in jurisdictions where drug courts were implemented across the nation.

Keywords:

• drug courts
• police
• arrest
• crime
• drug use

Notes

¹ The term jurisdiction refers to the area that is serviced by a municipal or county government. At present, there are 1,538 adult drug courts serving more than 1,700 jurisdictions (National Institute of Justice, 2015). Jurisdictions may have more than one drug court.

² Among the 222 cities with at least 100,000 residents that reported complete arrest data in the current study, 218 were already served by a municipal or county drug court by 2002 (see Table 1).

³ The years 2003–2004 were included in a final model as a check of robustness. However, the absence of variation among the already saturated (drug court-serviced) larger cities in the current study makes population-weighted fixed-effects untenable for nationwide analysis after 2002.

⁴ Jurisdiction fixed-effects were generated by time-demeaning the variables (Wooldridge, 2000). This approach facilitates weighted regressions and results in more accurate R-square values than the use of dummy variables. Given that neither arrests nor drug court creation occurred in a random fashion and that unmeasured stable jurisdictional characteristics could potentially correlate with the error term, fixed rather than random effects models were more conceptually and empirically appropriate (Leymon, 2010).

⁵ The database utilized in this study was developed by a team of criminologists, economists, and data analysts over a two year period with federal funding.

⁶ Not all agencies reported arrest data during each individual year of the 1990–2002 time period. Agencies with more than 4 years of missing data were removed from analyses. The vast majority of these jurisdictions were small, with low crime and drug arrest rates. Eliminating every agency that missed a single year of data would introduce systematic bias.

⁷ Comparison data were downloaded from the Office of Justice Programs (OJP) Drug Court Clearinghouse and Technical Assistance Project, housed at American University and via another data-set that was requested via Freedom of Information Act (FOIA) from the U.S. Government Accountability Office (GAO).

⁸ Stata software was utilized to generate robust standard errors in all regression models. Other weighting methods were also tested in alternative models.

⁹ To facilitate accurate national estimates, all mean arrest values were weighted by population.

Additional information

Notes on contributors

David R. Lilley

David R. Lilley is a Criminal Justice Professor at University of Toledo and previously worked as a Senior Justice Analyst in Washington, DC. His current research involves quantitative analyses of crime control programs, drug policies, and analysis of national and global crime trends. He recently conducted a nationwide study of Drug Courts and the Weed and Seed crime reduction program.