是什么导致了风险性阿片类药物处方使用? 来自人口迁移的证据

Quarterly Journal of Economics · 2025 · [{"name": "Amy Finkelstein", "affiliation": ["National Bureau of Economic Research"]}, {"name": "Matthew Gentzkow", "affiliation": ["National Bureau of Economic Research", "Stanford University"]}, {"name": "Dean Li", "affiliation": ["Massachusetts Institute of Technology"]}]

中文摘要

我们构建并估计了一个关于有风险的处方阿片类药物使用的动态模型，该模型使我们能够拆解阿片类药物流行中个人特定与地点特定驱动因素的作用，并评估各州阿片类药物政策的影响。事件研究表明，在2006年至2019年间领取联邦残疾保险的成年人中，迁往有风险使用率更高的州会使有风险使用的概率立即跃升，随后在其后数年内进一步逐渐上升。利用潜在结果框架，我们展示了这些结果如何映射到模型中的个人特定与地点特定因素。模型估计表明，地点对个体转向成瘾的可能性以及处方阿片类药物的可得性均有较大影响；估计还表明，当各州颁布限制疼痛诊所的法律时，这些地点效应会发生显著变化。将所有地点效应减少一个标准差，会使我们研究期间内的有风险使用减少约40%。地点效应的一个特定来源——疼痛诊所法律——使有风险使用减少了5%，但若其更早颁布，本可使之减少30%，而这种放大效应在很大程度上是通过成瘾的动态过程发挥作用的。

Abstract

We develop and estimate a dynamic model of risky prescription opioid use that allows us to unpack the role of person- and place-specific drivers of the opioid epidemic and to assess the impact of state opioid policies. Event studies indicate that, among adults receiving federal disability insurance from 2006 to 2019, moves to states with higher rates of risky use produce an immediate jump in the probability of risky use, followed by an additional gradual increase for the next several years. Using a potential outcomes framework, we show how these results map to the person- and place-specific factors in the model. Model estimates imply large effects of place on both the likelihood of transitioning to addiction and the availability of prescription opioids; they also indicate that these place effects change significantly when state laws restricting pain clinics are enacted. A one standard deviation reduction in all place effects would have reduced risky use by about 40 percent over our study period. One particular source of place effects, pain clinic laws, reduced risky use by 5 percent, but could have reduced it by 30 percent if they had been enacted earlier, with much of this magnification operating through the dynamics of addiction.