To further elaborate on my question, assume that I have a time series dataset of Tax X and Tax Y, where in Tax X is paid by 100% of the sample while Tax Y is paid by 75%. Both taxes differ with regards to how they are implemented and collected, but are ultimately based on business revenues. Now if I am trying to figure out the relationship between Tax Y and Tax X to estimate Tax Y for the 25% of the sample for which there is no Tax Y data, is it kosher to regress Tax Y on Tax X? It is clear to see that Tax X is not causing Tax Y and that both taxes are being determined by individual business revenues, which is not known.
There can be a linear relationship between variables with no causal relation directly involved. It's fair to check if the linear model is a good fit in order to make estimations.
I personally don't know any single model which needs something like "direct causality assumption".