We Just Created More Than 1,000 Synthetic Controls To Study California's $20 Fast Food Minimum Wage
我们刚刚创建了超过1,000个合成控制组来研究加州20美元快餐最低工资
Abstract
Synthetic control methods hold the promise of identifying a credible counterfactual by closely reproducing pretreatment outcome paths. Their reliability, however, depends in part on how effectively they constrain researchers’ less-visible degrees of freedom. We explore these methods’ sensitivity by constructing 1440 plausibly defensible specifications to estimate the employment effect of California’s $20 fast-food minimum wage. While over 96 percent of the estimated employment effects are negative, the range is vast, illustrating that synthetic control methods are sensitive to specification choice. Estimates from simpler and far more transparent difference-in-differences methods lie near the centers of the comparable distributions of synthetic control estimates. The labor market effects of California's AB 1228 are also analyzed, with varied conclusions, in both the initial and revised version of NBER working paper 34033 and in working paper 35171 .
中文摘要
合成控制方法有望通过紧密再现处理前结果路径来识别可信的反事实。然而,其可靠性部分取决于它们如何有效地约束研究人员不太可见的自由度。我们通过构建1440个看似合理的可辩护设定来估计加州20美元快餐最低工资的就业效应,从而探索这些方法的敏感性。虽然超过96%的估计就业效应为负,但范围巨大,说明合成控制方法对设定选择敏感。来自更简单且透明得多的双重差分方法的估计值位于合成控制估计值可比分布的中心附近。加州AB 1228的劳动力市场效应也在NBER工作论文34033的初始版本和修订版本以及工作论文35171中进行了分析,结论各异。