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; we term this natural macro interventions. We also discuss generalizations of this observation.

翻译：在聚合变量中，干预的影响通常定义不明确，因为相同的宏观干预的不同微观实现可能导致下游宏观变量的不同变化。我们证明，这种聚合变量上因果性的定义不明确性，可以取决于相应的微观实现，将无混杂的因果关联转变为有混杂的关联，反之亦然。我们认为，在实践中，要摆脱这种定义不明确性而仅使用聚合因果系统是不可行的。相反，我们必须接受宏观因果关联通常仅参照微观状态来定义。从积极方面来看，我们表明，当宏观干预使得微观状态的分布与观测分布相同时，因果关系可以聚合；我们将此称为自然宏观干预。我们还讨论了这一观察的推广。