I have seen several references to "impure heteroscedasticity" online as heteroscedasticity caused by omitted variable bias. However, I once saw an Internet reference, as I recall, which reminds me of a phenomenon where data that should be modeled separately are modeled together, causing an appearance of increased heteroscedasticity. I think there was a youtube video. That seems like another example of "impure" heteroscedasticity to me. Think of a simple linear regression, say with zero intercept, where the slope, b, for one group/subpopulation/population is slightly larger than another, but those two populations are erroneously modeled together, with a compromise b. The increase in variance of y for larger cases of x would be at least partially due to this modeling problem. (I'm not sure that "model specification error" covers this case where one model is used instead of the two - or more - models needed.)
I have not found that reference online again. Has anyone seen it?
I am interested in any reference to heteroscedasticity mimicry. I'd like to include such a reference in the background/introduction to a paper on analysis of heteroscedasticity which, in contrast, is only from the error structure for an appropriate model, with attention to unequal 'size' members of a population. This would then delineate what my paper is about, in contrast to 'heteroscedasticity' caused by other factors.
Thank you.