Quarterly Journal of Economics · 2019 · Rodrigo Adão、Michal Kolesár、Eduardo Morales
中文摘要
我们研究了移位-份额回归设计中的推断问题，例如当地区结果对部门冲击的加权平均进行回归时，使用地区部门份额作为权重。我们进行了一项安慰剂检验，在其中我们估计了由随机生成的部门冲击构建的移位-份额回归因子对美国通勤区实际劳动力市场结果的影响。基于常用标准误且名义显著性水平为5%的检验，在高达55%的安慰剂样本中拒绝了无效应的原假设。我们使用一个简约的经济模型表明，这种过度拒绝问题的产生是因为回归残差在具有相似部门份额的地域之间存在相关，而与其地理位置无关。我们推导了在回归残差存在任意跨地区相关下依然有效的新推断方法。我们使用移位-份额设计的常见应用表明，我们的方法在实践中可能导致置信区间大幅变宽。
Abstract
Abstract We study inference in shift-share regression designs, such as when a regional outcome is regressed on a weighted average of sectoral shocks, using regional sector shares as weights. We conduct a placebo exercise in which we estimate the effect of a shift-share regressor constructed with randomly generated sectoral shocks on actual labor market outcomes across U.S. commuting zones. Tests based on commonly used standard errors with 5% nominal significance level reject the null of no effect in up to 55% of the placebo samples. We use a stylized economic model to show that this overrejection problem arises because regression residuals are correlated across regions with similar sectoral shares, independent of their geographic location. We derive novel inference methods that are valid under arbitrary cross-regional correlation in the regression residuals. We show using popular applications of shift-share designs that our methods may lead to substantially wider confidence intervals in practice.