Abstract

:The most basic question one can ask of a model is ‘What is the effect on variable y2 of variable y1?’ Causation is ‘implementation neutral’ when all interventions on external variables that lead to a given change in y1 have the same effect on y2, so that the effect of y1 on y2 is defined unambiguously. Familiar ideas of causal analysis do not apply when causation is implementation neutral. For example, a cause variable cannot be linked to an effect variable by both a direct path and a distinct indirect path. Discussion of empirical aspects of implementation neutrality leads to further unexpected results, such as that if one variable causes another the coefficient representing that causal link is always identified.