To comprehensively evaluate a public policy intervention, researchers must consider the effects of the policy not just on the implementing region, but also nearby, indirectly-affected regions. For example, an excise tax on sweetened beverages in Philadelphia was shown to not only be associated with a decrease in volume sales of taxed beverages in Philadelphia, but also an increase in sales in bordering counties not subject to the tax. The latter association may be explained by cross-border shopping behaviors of Philadelphia residents and indicate a causal effect of the tax on nearby regions, which may offset the total effect of the intervention. To estimate causal effects in this setting, we extend difference-in-differences methodology to account for such interference between regions and adjust for potential confounding present in quasi-experimental evaluations. Our doubly robust estimators for the average treatment effect on the treated and neighboring control relax standard assumptions on interference and model specification. We apply these methods to evaluate the change in volume sales of taxed beverages in 231 Philadelphia and bordering county stores due to the Philadelphia beverage tax. We also use our methods to explore the heterogeneity of effects across geographic features.
翻译:为了全面评价公共政策干预,研究人员必须考虑该政策不仅对执行区域,而且对邻近间接受影响的区域的影响。例如,费城对甜饮料征收消费税,不仅表明费城的减税与免税饮料销售量的减少有关,而且与不征税的邻国销售量的增加有关。后者可能由费城居民的跨界购物行为来解释,并表明该税对附近区域的因果关系,这可能会抵消干预的总体影响。为了估计这一环境的因果关系,我们扩大差异方法,以说明区域间的这种干扰,并作出调整,以适应准实验性评估中存在的潜在混杂因素。我们加倍强烈地估计对治疗和邻近控制的平均治疗效果,放松干预和示范规格的标准假设。我们采用这些方法来评价由于费城饮料税在231费城和邻近郡商店销售量的变化。我们还使用我们的方法来探讨不同地理特征影响的多样性。