Dear list participants,

I would appreciate clarifications on this point:  Controlling for
variables that are consequences of another regressor in the main
regression (i.e., overcontrolling) is said to lead to bias (right?).
 I wonder, if that is so, how can we tell (assuming theory and common
sense do not help) if a right-hand side variable is a consequence of
another included regressor or just hihgly correlated with it?  If it's
just correlated with that other explanatory variable and correlated
with the dependent variable and we excluded it, it would lead to
ommited variable bias, right?  So how to tell?  When can we safely
leave out a variable so as not to "overcontrol" and not risk ommited
variable bias?

Finally, If we wanted to test (causal) mechanims, would it be fine to
include such a regressor that is a consequence of another?

thanks!
carlos

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