In aggregated variables the impact of interventions is typically ill-defined because different micro-realizations of the same macro-intervention can result in different changes of downstream macro-variables. We show that this ill-definedness of causality on aggregated variables can turn unconfounded causal relations into confounded ones and vice versa, depending on the respective micro-realization. We argue that it is practically infeasible to only use aggregated causal systems when we are free from this ill-definedness. Instead, we need to accept that macro causal relations are typically defined only with reference to the micro states. On the positive side, we show that cause-effect relations can be aggregated when the macro interventions are such that the distribution of micro states is the same as in the observational distribution and also discuss generalizations of this observation.

翻译：在聚合变量中，干预的影响通常缺乏明确定义，因为相同宏观干预的不同微观实现在下游宏观变量上会导致不同的变化。我们证明，这种聚合变量上的因果定义模糊性可以使无混杂的因果关系变为有混杂，反之亦然，具体取决于相应的微观实现。我们认为，在实际中，仅使用聚合因果系统而避免这种定义模糊性是不可行的。相反，我们需要接受宏观因果关系通常仅在参考微观状态时才有明确定义。从积极方面来看，我们证明，当宏观干预使得微观状态的分布与观测分布相同时，因果效应可以实现聚合，并进一步讨论了这一观察的推广。