This might be a basic question, but I want to be sure that what I'm doing is right. I have a model that suggests that variable X causes both Y and Z. When I regress Y on X, or Z on X, I get positive and significant coefficients as expected.
Now, when I regress Z on Y, I still get a positive significant coefficient.
Question 1: is this an omitted variable bias?
Question 2: is it legitimate to regress Z on Y and X to test whether the relationship between Z and Y is spurious?
Question 3: if it is legitimate and if I get positive significant coefficients on both Y and X what does that mean? Does it mean "X causes Y and Z, but Y still has marginal explanatory power on Z"?
Many thanks, Dave