Cannabis Policy and Consumption: Taking into account Substitution Effects

Abstract

Background: Previous studies examining the cannabis-alcohol substitution effect have found that medical cannabis policies may result in substituting the use of cannabis in place of alcohol use. Objectives: This study adds to the literature on cannabis-alcohol substitution by analyzing the effect of decriminalization, medicinal cannabis, and adult-use legalization cannabis policies (2002-2019) on cannabis and alcohol use and substance substitution for all 50 states and the District of Columbia (N=867). Results: Results support the notion that liberalized cannabis policies can increase the prevalence of cannabis use. An adult-use legalization specific analysis yielded findings suggesting a complex and heterogenous effect of such laws on cannabis-alcohol complementation. Conclusion: Given the lack of clarity and heterogenous effects of cannabis laws, policy makers should carefully take into consideration the benefits of medical cannabis laws, along with the risks of decriminalization and adult-use legalization.

Keywords:

• Substitution theory
• cannabis laws
• cannabis/alcohol use

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Drug Scheduling. Retrieved from https://www.dea.gov/drug-information/drug-scheduling

2 https://www.samhsa.gov/data/nsduh/state-reports

3 The National Organization for the Reform of Marijuana Laws (NORML) is a non-profit organization founded in 1970 by Ethan Nadelmann that collects up to date information on the rapidly changing cannabis legislation throughout the United States, including links to the legislation to be used for verification of their information, the date(s) of enactment, and the implementation criteria set out by the passed legislation, see more information at: https://norml.org/laws/

4 Census demographic data for sex, race, and age were accessed for 2000-2009 and 2010-2019 from https://www2.census.gov/programs-surveys/popest/datasets/2000-2009/state/asrh/ and https://www2.census.gov/programs-surveys/popest/tables/2010-2019/state/asrh/

5 Unemployment rate data downloaded from https://www.icip.iastate.edu/tables/employment/unemployment-states for 1999-2018 and https://www.bls.gov/lau/lastrk19.htm for 2019.

6 Per an anonymous reviewer’s suggestion, the authors ran supplemental analyses utilizing a coding scheme that used July 1 as the effective coding date. In this supplemental approach, laws enacted prior to July 1 would be coded as going into effect that same year, whereas laws enacted after July 1 would be coded as going into effect the subsequent year.

7 Poverty rate data downloaded from Table 21. Retrieved June 1, 2022, from https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-people.html

8 Female headed household data was retrieved from https://data.nber.org/cps-basic2/

9 Health insurance data came from two sources. Data for 2002-2012 were sourced from the Current Population Survey Annual Social and Economic Supplement found here: https://www.census.gov/data/tables/time-series/demo/health-insurance/historical-series/hib.html. Data for 2013-2019 were sourced from the American Community Survey found here: https://www.census.gov/data/tables/time-series/demo/health-insurance/historical-series/hic.html

10 Year dummy effects are suppressed from Table 2 to reduce space taken up by the table but were included while estimating both models.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.