Influences on cannabis policy design and adaptation in the American states

Datos Bibliográficos

ID6328320
AutoresGrant W Neeley (0000-0003-2323-0848, Department of Political Science University of Dayton Dayton Ohio USA), Lilliard E Richardson (0000-0003-2716-3101, School of Public Policy Penn State University University Park Pennsylvania USA)
Año2025
Volumen53
Número3
Páginas723-746
Fecha de publicación2025-08-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaPolicy Studies Journal (JOURNAL)
Identificadores de la revistaISSN: 0190-292X • E-ISSN: 1541-0072
EditorialWiley (PUBLISHER • GB)
DOI10.1111/psj.70002
OpenAlexW4408384800
IdiomaEN
Citas recibidas1
Referencias citadas65

Despite federal prohibitions, three‐quarters of states had implemented medical marijuana laws (MML) and one‐third had implemented recreational cannabis laws (RCL) by 2020. State policy designs varied considerably, and we focus on policy development and maturation in policy implementation, examining factors influencing design features of policy bundles for MML and RCL policies. Using data for 50 states from 1994 to 2020, we categorized 36 policies into three distinctive policy bundles. The pharmaceutical bundle regulates cannabis like other medicinal drugs. The permissive bundle gives individuals discretion to use cannabis with minimal state regulation. The fiscal bundle treats cannabis as a state revenue source. Most importantly, policy design choices continue beyond adoption into implementation, and each bundle score can change over time and by state. Using panel regression with state and year fixed effects, we test five influence pathways for the policy design of cannabis policy bundles: (a) the average bundle score of neighboring states, (b) the partisan‐weighted neighbor average, (c) the neighbor average weighted by citizen ideology, (d) the average of all states with similar unified party control, and (e) the policy leader bundle score weighted by ideological similarity. Models also include partisanship, economics, public finance, citizen ideology, demographics, and policy‐specific variables. Besides internal factors of Democratic legislative composition, state citizen ideology, and the relative percentage of a state's population receiving disability benefits, we find support for external cue‐taking from other states, particularly among those with similar ideological leanings

Adaptation (eye · Cannabis · Political science · Psychotherapist · Global Public Health Policies and Epidemiology · Neuroscience · Policy Transfer and Learning · Psychology · Substance Abuse Treatment and Outcomes