We describe a formal approach based on graphical causal models to identify the "root causes" of the change in the probability distribution of variables. After factorizing the joint distribution into conditional distributions of each variable, given its parents (the "causal mechanisms"), we attribute the change to changes of these causal mechanisms. This attribution analysis accounts for the fact that mechanisms often change independently and sometimes only some of them change. Through simulations, we study the performance of our distribution change attribution method. We then present a real-world case study identifying the drivers of the difference in the income distribution between men and women.

翻译：我们描述一种基于图形因果模型的正式方法,以确定变数概率分布变化的“根本原因 ” 。 在将共同分布纳入每个变数的有条件分布时,考虑到其父母(“因果机制 ” ), 我们将这种变化归因于这些因果机制的变化。 这种归因分析说明了机制经常独立变化,有时只是部分变化的事实。 我们通过模拟研究我们分配变化归属方法的绩效。 然后我们提出一个真实世界的案例研究,找出男女收入分布差异的驱动因素。