Rosanna Smart

Variation in cannabis potency and prices in a newly legal market: evidence from 30 million cannabis sales in Washington state

AIMSnTo (1) assess trends and variation in the market share of product types and potency sold in a legal cannabis retail market and (2) estimate how potency and purchase quantity influence price variation for cannabis flower.nnnDESIGNnSecondary analysis of publicly available data from Washington States cannabis traceability system spanning 7 July 2014 to 30 September 2016. Descriptive statistics and linear regressions assessed variation and trends in cannabis product variety and potency. Hedonic regressions estimated how purchase quantity and potency influence cannabis flower price variation.nnnSETTINGnWashington State, USA.nnnPARTICIPANTSn(1) A total of 44u2009482u2009176 million cannabis purchases, including (2) 31u2009052u2009123 cannabis flower purchases after trimming price and quantity outliers.nnnMEASUREMENTSnPrimary outcome measures were (1) monthly expenditures on cannabis, total delta-9-tetrahydrocannabinol (THC) concentration and cannabidiol (CBD) concentration by product type and (2) excise tax-inclusive price per gram of cannabis flower. Key covariates for the hedonic price regressions included quantity purchased, THC and CBD.nnnFINDINGSnTraditional cannabis flowers still account for the majority of spending (66.6%), but the market share of extracts for inhalation increased by 145.8% between October 2014 and September 2016, now comprising 21.2% of sales. The average THC-level for cannabis extracts is more than triple that for cannabis flowers (68.7% compared to 20.6%). For flower products, there is a statistically significant relationship between price per gram and both THC [coefficientxa0=xa00.012; 95% confidence interval (CI)xa0=xa00.011-0.013] and CBD (coefficientxa0=xa00.017; CIxa0=xa00.015-0.019). The estimated discount elasticity is -0.06 (CIxa0=xa0-0.07 to -0.05).nnnCONCLUSIONSnIn the state of Washington, USA, the legal cannabis market is currently dominated by high-THC cannabis flower, and features growing expenditures on extracts. For cannabis flower, both THC and CBD are associated with higher per-gram prices, and there are small but significant quantity discounts.

Medical Marijuana and Marijuana Legalization

State-level marijuana liberalization policies have been evolving for the past five decades, and yet the overall scientific evidence of the impact of these policies is widely believed to be inconclusive. In this review we summarize some of the key limitations of the studies evaluating the effects of decriminalization and medical marijuana laws on marijuana use, highlighting their inconsistencies in terms of the heterogeneity of policies, the timing of the evaluations, and the measures of use being considered. We suggest that the heterogeneity in the responsiveness of different populations to particular laws is important for interpreting the mixed findings from the literature, and we highlight the limitations of the existing literature in providing clear insights into the probable effects of marijuana legalization.

The Kids Aren't Alright but Older Adults Are Just Fine: Effects of Medical Marijuana Market Growth on Substance Use and Abuse

Almost half of the US states have adopted “medical marijuana” laws (MMLs), and 58% of Americans now favor marijuana legalization. Despite public support, federal law continues to prohibit the use and sale of marijuana due to public health concerns of increased abuse, drugged driving, and youth access. Using evidence from MMLs, this is the first paper to study whether growth in the size of legal marijuana markets affects illegal use and its associated health consequences. By collecting new data on per capita registered medical marijuana patient rates, I investigate how state supply regulations and changes in federal enforcement affect the size of this legal market. I then study how illegal marijuana use and other health outcomes respond to changes in legal availability. I find that growth in the legal medical marijuana market significantly increases recreational use among all age groups. Increased consumption among older adults has positive consequences in the form of an 11% reduction in alcohol- and opioid-poisoning deaths. However, increased consumption among youths leads to negative externalities. Raising the share of adults registered as medical marijuana patients by one percentage point increases the prevalence of recent marijuana use among adolescents and young adults by 5-6% and generates negative externalities in the form of increased traffic fatalities (7%) and alcohol poisoning deaths (4%).

Breaking Down Barriers: Experiments into Policies That Might Incentivize Employers to Hire Ex-Offenders

The rate of criminal punishment in the United States has had far-reaching economic consequences, in large part because people with criminal records are marginalized within the labor market. According to a 2008 estimate (Rodriguez and Emsellem, 2011), 64.6 million Americans (25 percent of the population) have a criminal record, and of that group, 19.8 million have at least one felony criminal conviction (Shannon et al., 2011).1 Evidence shows that people with a criminal record have substantially lower probabilities of being hired, even compared with other disadvantaged individuals—such as welfare recipients, high school dropouts, unemployed people, and those with “spotty” work histories—who do not have a criminal record (Holzer, 1996). Given these negative economic implications, federal, state, and local officials have developed a host of policies to encourage employers to hire ex-offenders, with varying degrees of success. Examples include the “Ban the Box” policy, which delays the point in the recruitment process that criminal-background information is made available to employers; the federal Work Opportunity Tax Credit (WOTC); certificates of rehabilitation, which restore rights to convicted felons; and programs supported by Department of Labor Reintegration of ExOffenders grants. But all these programs to incentivize the hiring of ex-offenders have important limitations to improving ex-offender employment. To inform policies and programs aimed at improving employment rates for ex-offenders, we conducted experiments to examine employer preferences regarding policy options targeted to incentivizing the employment of C O R P O R A T I O N

Differences in alcohol cognitions, consumption, and consequences among first-time DUI offenders who co-use alcohol and marijuana

BACKGROUNDnA significant portion of alcohol-related DUI offenders engage in co-use of alcohol and marijuana (AM). Given expanding marijuana legalization and the impaired driving risks associated with co-use, it is of increased importance to understand how characteristics of AM co-users compare to those who use alcohol only (AO) in order to inform DUI interventions and prevent recidivism.nnnMETHODSnParticipants were 277 first-time DUI offenders enrolled in a first-time DUI offender program across three locations. Using well-established measures, we evaluated differences in alcohol-related cognitions (positive expectancies and self-efficacy), frequency and quantity of alcohol consumption, and alcohol-related consequences between AO users and AM co-users by running a series of multivariate generalized linear models.nnnRESULTSnCompared to AO users, AM co-users reported lower self-efficacy to achieve abstinence and avoid DUI. Differences in abstinence self-efficacy largely explain higher relative rates of average and peak drinking quantity and higher odds of binge drinking among AM co-user. Despite lower self-efficacy and higher drinking quantity, there were no significant differences between AM and AO-users on alcohol-related consequences and past month reports of drinking and driving.nnnCONCLUSIONSnOur results provide preliminary evidence that DUI offenders who co-use alcohol and marijuana have higher alcohol use and lower self-efficacy than AO-users, and long-term consequences for this group should be monitored in future research. DUI programs may screen and identify co-users and consider tailoring their interventions to build self-efficacy to address the risks associated with AM co-use uniquely.