The Spillover Effect of Recreational Marijuana Legalization on Crime: Evidence From Neighboring States of Colorado and Washington State

Abstract

An ongoing debate exists about the implications of recreational marijuana legalization to public safety. One important public concern is how recreational marijuana legalization may affect crime in neighboring states that have not legalized. Based on Uniform Crime Report (UCR) data from 2003 to 2017, this study used difference-in-differences (DID) analysis to examine the potential spillover effect of recreational marijuana legalization in Colorado and Washington State, with a special focus on the examination of the changes in the rates of a variety of crimes in the border counties of neighboring states relative to the nonborder counties in these states following Colorado’s and Washington’s legalization. Results provide some evidence suggesting a spillover crime reduction effect of legalization, as reflected by the significant decreases in the rates of property crime, larceny, and simple assault in the Colorado region that includes six neighboring states. Results also suggest that the effects of marijuana legalization on crime in neighboring states vary based on crime type and state.

Illegal drug market responses to state recreational cannabis laws

“…Another key finding is that RCLs led to declines in law enforcement submissions of cannabis, as expected, but also of other drugs. Our findings coincide with studies documenting reductions in some types of index crimes after RCL implementation [16,48,49] and with police reports based on state data indicating reductions in cannabis-related crimes, arrests and seizures [34][35][36]. Qualitative evidence from focus groups of police and prosecutors indicated a de-prioritization of cannabis crime by law enforcement [36].…”

Causal Inference Challenges and New Directions for Epidemiologic Research on the Health Effects of Social Policies

“…Electoral cycles [28], immigration laws [29], motor vehicle safety laws [30], paid family leave laws [31] Timing of delivery of benefits of a policy Tax credits and short-term health outcomes in months on tax disbursements (February, March, April) [15], monthly Supplemental Nutrition Assistance Program disbursements and health outcomes in first half versus second half of the month [32] Policy intensity, restrictiveness, or generosity Earned income tax credit benefit generosity [16], unemployment benefit generosity [33], firearm law restrictiveness [34], alcohol law restrictiveness [35], minimum wage level [36], beer excise tax [37] Physical proximity to a jurisdiction with a policy or a resource delivered by a policy Proximity to educational institutions [38], proximity to borders of states with cannabis legalization [39,40] Clinicians who have different preferences for treatment modalities [57,58], judges who have different propensities for leniency [59,60] We distinguish methods for evaluating HTEs based on a priori specified characteristics from data-driven methods which more agnostically search for groups with heterogeneous responses to the policy [82•]. Heterogeneity across pre-specified characteristics (e.g., race/ethnicity, age) is usually quantified via stratification or interaction terms in statistical models, and the chosen dimensions can be guided by theory or evidence [82•].…”

Societal Costs and Outcomes of Medical and Recreational Marijuana Policies in the United States: A Systematic Review

“…Wu and colleagues examined the potential spillover effect of RMLs on states without RMLs that bordered Colorado and Washington. Significant decreases in the rates of property crime, larceny, and simple assault were found in the six states bordering Colorado, but the Washington region experienced no significant changes in the rates of multiple types of crimes (Wu et al, 2020). Considering the 11 states in the Western Census Region, MMLs did not lead to significant negative spillover effects on violent or property crimes (Shepard & Blackley, 2016).…”