Department of Agricultural Economics and Rural Sociology, University of Idaho. 875 Perimeter Drive; Moscow, Idaho 83483, United States.
Department of Agricultural Economics and Rural Sociology, University of Idaho. 875 Perimeter Drive; Moscow, Idaho 83483, United States.
Int J Drug Policy. 2023 May;115:104000. doi: 10.1016/j.drugpo.2023.104000. Epub 2023 Mar 24.
This study examines the effect of retail recreational marijuana legalization on traffic fatalities using the most current data available and recent advancements in difference-in-difference estimation methods proposed by Callaway and Sant'Anna, (2021).
A modified difference-in-difference (CS-DID) is used to estimate the effect of recreational marijuana legalization on traffic fatalities reported in the Fatality Analysis Reporting System (FARS). Difference-in-difference regression models are run at the state-year level, using data from 2007 through 2020, and compared to estimates using traditional two-way-fixed-effects (TWFE) models.
Consistent with past studies, results from conventional TWFE suggest traffic fatalities increase at a rate of 1.2 per billion vehicle miles traveled (BVMT) after retail of recreational marijuana begins. However, using the CS-DID model, we find slightly larger average total treatment effects (∼2.2 fatalities per BVMT). Moreover, the size of the effect changes across time, where cohorts "treated" earlier have substantially higher increases than those who more recently legalized.
Traffic fatalities increase by 2.2 per billion miles driven after retail legalization, which may account for as many as 1400 traffic fatalities annually. States who legalized earlier experienced larger traffic fatality increases. TWFE methods are inadequate for policy evaluation and do not capture heterogeneous effects across time.
本研究利用最新可用数据和 Callaway 和 Sant'Anna(2021 年)提出的差分差异估计方法的最新进展,考察了零售休闲大麻合法化对交通死亡的影响。
使用改良后的差分(CS-DID)来估计休闲大麻合法化对 Fatality Analysis Reporting System(FARS)中报告的交通死亡的影响。在州-年的水平上运行差分回归模型,使用 2007 年至 2020 年的数据,并与传统的双向固定效应(TWFE)模型的估计值进行比较。
与过去的研究一致,传统 TWFE 的结果表明,在休闲大麻零售开始后,每十亿车辆行驶英里(BVMT)的交通死亡人数增加 1.2 人。然而,使用 CS-DID 模型,我们发现平均总治疗效果略大(每 BVMT 约 2.2 人死亡)。此外,效应的大小随时间而变化,较早“治疗”的队列增加幅度明显高于最近合法化的队列。
零售合法化后,每十亿英里行驶的交通死亡人数增加 2.2 人,这可能导致每年多达 1400 人死于交通事故。较早合法化的州经历了更大的交通死亡人数增加。TWFE 方法不适合政策评估,也无法捕捉随时间变化的异质效应。