Nonrandom Exposure to Exogenous Shocks
提出新方法，利用已知公式组合多种变异来源估计因果效应，通过设定反事实冲击并调整非随机暴露的汇总度量来避免遗漏变量偏误，并应用于中国高铁建设对市场准入增长与就业影响的估计。
We develop a new approach to estimating the causal effects of treatments or instruments that combine multiple sources of variation according to a known formula. Examples include treatments capturing spillovers in social or transportation networks and simulated instruments for policy eligibility. We show how exogenous shocks to some—but not all—determinants of such variables can be leveraged while avoiding omitted variables bias. Our solution involves specifying counterfactual shocks that may as well have been realized and adjusting for a summary measure of nonrandomness in shock exposure: the average treatment (or instrument) across shock counterfactuals. We use this approach to address bias when estimating employment effects of market access growth from Chinese high‐speed rail construction.