The renowned difference-in-differences (DiD) estimator relies on the assumption of 'parallel trends,' which does not hold in many practical applications. To address this issue, the econometrics literature has turned to the triple difference estimator. Both DiD and triple difference are limited to assessing average effects exclusively. An alternative avenue is offered by the changes-in-changes (CiC) estimator, which provides an estimate of the entire counterfactual distribution at the cost of relying on (stronger) distributional assumptions. In this work, we extend the triple difference estimator to accommodate the CiC framework, presenting the `triple changes estimator' and its identification assumptions, thereby expanding the scope of the CiC paradigm. Subsequently, we empirically evaluate the proposed framework and apply it to a study examining the impact of Medicaid expansion on children's preventive care.

翻译：著名的双重差分（DiD）估计量依赖于“平行趋势”假设，但该假设在许多实际应用中并不成立。为解决这一问题，计量经济学文献引入了三重差分估计量。然而，DiD和三重差分均仅限于评估平均效应。变化-变化（CiC）估计量提供了另一种途径，它能估计整个反事实分布，但代价是依赖（更强的）分布假设。本研究将三重差分估计量扩展至CiC框架，提出了“三重变化估计量”及其识别假设，从而拓宽了CiC范式的适用范围。随后，我们对该框架进行了实证评估，并将其应用于一项研究，考察医疗补助扩展对儿童预防性护理的影响。