Causation and Manipulation IV: Conditional Effects 

 People who read this blog regularly know that few things get authors and commentators as worked up as questions about causal inference, either philosophical ( here ,  here , and here) or technical ( here ,  here ,  here , etc.).  I wouldn't want to miss out on the fun this time around -- and how could I pass up the opportunity to have the IV post on causation and manipulation? 

 Jens and Felix have both discussed whether non-manipulable characteristics such as race or gender ("attributes" for Holland) can be considered causes within the potential outcomes framework.   I agree with them that, at least as far as Holland is concerned, the answer is (almost always) no - no causation without manipulation.  The fact that we are having this discussion 20 years later suggests (to me, at least) that this answer is intuitively unsatisfying.  It is worth remembering a comment made by Clark Glymour in his discussion of the Holland (1986) article: 
 People talk as they will, and if they talk in a way that does not fit some piece of philosophical analysis and seem to understand each other well enough when they do, then there is something going on that the analysis has not caught.  
 


 Identifying perceptions of an attribute (rather than the attribute itself) as the factor subject to manipulation makes a lot of sense in situations where the potential outcomes are to a certain degree out of the control of the individual possessing the attribute, as in the discrimination example.  Extending this idea to situations in which outcomes are generated by the subject possessing the attribute (in which "self-perceptions" would be manipulated) would commit researchers to a very particular understanding of attributes such as race and gender that would hardly be uncontroversial. 

 In these cases, I think that it makes more sense to look at the differences in well-specified Rubin-Holland causal effects (i.e. the results of manipulation) conditional on values of the attribute rather than identifying a causal effect as such.  So, for example, in the gender discrimination example we could think of the manipulation as either applying or not applying for a particular job.  This is clearly something that we could randomize, so the causal effect would be well defined.   We could calculate the average treatment effect separately for men and women and compare those two quantities, giving us the difference in conditional causal effects.  I'm sure that there is a catchy name for this difference out there in the literature, but I haven't run across it. 

 So, is this quantity (the difference in conditional causal effects) of interest to applied researchers in the social sciences?  I would argue that it is, if for nothing else than giving us a more nuanced view of the consequences of something that we can manipulate.  Is it a Rubin-Holland causal effect?  No, but that is a problem only to the extent that we privilege "causal" over other useful forms of inference.