The idea that race can be a cause is not without dispute.
In a 1986 JASA article, Paul Holland discussed how he and Don Rubin coined the expression, “no causation without manipulation”.
The idea here is that causal inference requires a strict definition of a cause that identifies an intervention that hypothetically could be implemented -- even if that manipulation is not physically possible or ethically feasible.
So what is a hypothetical intervention that would change someone's race? Perhaps a genetic manipulation? But there is no "race" gene that can be flipped like a digital bit. It is hard to imagine there is some way of changing all the genes that contribute to the phenotypes that define race, while keeping all other phenotypes constant. Perhaps instead a cosmetic procedure could make a white person pass as black or vice versa?
Both of these lines of reasoning lead one to think about how race is defined by how other people perceive an individual. So then is "race" what the researcher is looking for? Perhaps it is racial discrimination? Or a persons professed ethnic identity?
If you talk to Miguel A. Hernán and James M. Robins, authors of the causal inference book cited below, they would tell you race is not a valid cause and that only thinking more deeply about what people actually mean when they talk about race as a cause will lead to better inferences.
On the other hand, some, including Judea Pearl, take issue with position.
Here is a quote (from Twitter) by Hernan:
Pearl believes that any causal effect we can name must also exist. To
him, the meaning of “the causal effect of A on death” is self-evident.
He says we can quantify, say, the causal effect of race or the causal
effect of obesity. I don't think we can.
We cannot estimate "the causal effect of obesity" because we don't
know what that means. For the causal effect of A to be well defined,
we need a common understanding of the interventions that we would use
to change A. Otherwise, the effect is undefined.
If by now you are thinking that this is just another academic debate
on the sex of the angels, think again: you beliefs about this issue
determine your beliefs about the limits of science and about how to
conduct data analyses.
Pearl addresses the issue here.
Hernán MA, Robins JM (2018). Causal Inference. Boca Raton: Chapman & Hall/CRC, forthcoming.”