| This thesis raises objections to the use of causal reasoning with equilibrium models. I consider two operators that are used to transform models: the Do operator for modeling manipulation and the Equilibration operator for modeling a system that has achieved equilibrium. I introduce a property of a causal model called the EMC Property that is true iff the Do operator commutes with the Equilibration operator. I prove that not all models obey the EMC property, and I demonstrate empirically that when inferring a causal model from data, the learned model will not support causal reasoning if the EMC property is not obeyed. I find sufficient conditions for models to violate and not to violate the EMC property. In addition, I show that there exists a class of models that violate EMC and possess a set of variables whose manipulation will cause an instability in the system. All dynamic models in this class possess feedback, although I do not prove that feedback is a necessary or a sufficient condition for EMC violation. I define the Structural Stability Principle which provides a necessary graphical criterion for stability in causal models. I will argue that the models in this class are quite common given typical assumptions about causal relations. |
