Researchers using instrumental variables to investigate the effects of ordered treatments (e.g., years of education, months of healthcare coverage) often recode treatment into a binary indicator for any exposure (e.g., any college, any healthcare coverage). The resulting estimand is difficult to interpret unless the instruments only shift compliers from no treatment to some positive quantity and not from some treatment to more -- i.e., there are extensive margin compliers only (EMCO). When EMCO holds, recoded endogenous variables capture a weighted average of treatment effects across complier groups that can be partially unbundled into each group's treated and untreated means. Invoking EMCO along with the standard Local Average Treatment Effect assumptions is equivalent to assuming choices are determined by a simple two-factor selection model in which agents first decide whether to participate in treatment at all and then decide how much. The instruments must only impact relative utility in the first step. Although EMCO constrains unobserved counterfactual choices, it places testable restrictions on the joint distribution of outcomes, treatments, and instruments.
翻译:使用工具变量来调查定购治疗的效果的研究人员(例如,受教育年数、保健覆盖月数)经常将治疗重新编码为任何接触的二元指标(例如,任何大学、任何保健覆盖),由此产生的估计值很难解释,除非仪器仅将遵守者从不治疗转向某种积极数量,而不是从某种治疗转向更多的治疗 -- -- 即,只有广泛的差值遵守者(EMCO),当EMCO持有时,重新编码的内生变量能够捕捉到各遵守者群体之间治疗效果的加权平均值,这些效应可以部分地分解到每个群体的治疗和未处理手段中,援引EMCO和标准地方平均治疗效果假设相当于假设选择由简单的两个因素选择模式确定,在这种模式中,代理者首先决定是否参加治疗,然后决定多少。这些工具只能对第一步的相对效用产生影响。虽然EMCO限制未观测到的反事实选择,但它对结果、治疗和工具的联合分配设置了可检验的限制。