Re: st: Mediating variables

[John Antonakis <John.Antonakis@unil.ch>]

If I understand your question correctly (from your first sentence), x 
predicts three mediators, which in term predict y.

This system is not identified for 2sls or 3sls analysis (you need at 
least as many IVs as you have mediators).

You could estimate it using mvreg or sureg (and then request whether 
errors are correlated like this):

sureg (y = r s t ) (r s t = x), corr

note: corr will give you a Breusch-Pagan test of independence (for the 
residuals)--a Hausman test will not help you here.

However, the above is not a strong test.

I am not following what you state regarding the panel structure.

HTH,
John.

____________________________________________________

Prof. John Antonakis
Associate Dean 
Faculty of Business and Economics
University of Lausanne
Internef #618
CH-1015 Lausanne-Dorigny
Switzerland

Tel ++41 (0)21 692-3438
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____________________________________________________



Jaime Gómez wrote:

> 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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