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.

该研究讨论了聚合变量的影响，特别是针对不同微观表现会对下游宏观变量产生不同变化的问题，进而讲述了因果关系在聚合变量中的局限性，只有参考微观物态才能确定宏观因果关系，并探讨了宏观干预和微观状态分布的关系。