Dear Stata users
I have a model in which the relationship between a predictor “x” and an
outcome “y” is mediated by three factors (“r”, “s” and “t”). I am only able
to test whether one of the predictors (“r”) mediates the relationship
between “x” and “y” (I only have data on this mediating variable and I
cannot get data on the other two). I would like to implement Baron and Kenny
(1986)’s test for mediation. At least, this involves estimating the
following system:
Y=a1+b*r+c*x+epsilon1
r=a2+d*x+epsilon2
Given that the errors of the two equations are potentially correlated, it
has been suggested that a 2SLS approach should be used. I have seen that
this could be done with ivregress, provided that I can find data on at least
one variable that affects “r” and does not affect “y”. My doubts are the
following:
1) Given that I have a triangular system, do I have to use the
traditional approach implemented by ivregress or the “modified” proposed in
http://www.stata.com/support/faqs/stat/ivr_faq.html ? Are both valid?
2) How do I test for the hypothesis that the errors are correlated? I
have seen that the use of a Hausman test is suggested in the literature, but
I do not know how to implement this in Stata (specially in the case I use
the “modified” approach)
3) Given that I have panel data, could I take advantage of the panel
structure of my data to correct for the fact that I do not have information
on two of the mediating variables (“s” and “t”)? Is there a procedure in
Stata for that?
Thanks a lot
Jaime Gómez
Universidad de Zaragoza
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