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Re: st: interpreting cofficient on interaction of two logged variables
From
David Greenberg <[email protected]>
To
[email protected], [email protected]
Subject
Re: st: interpreting cofficient on interaction of two logged variables
Date
Tue, 21 Aug 2012 15:40:22 -0400
The log of a product of two variables is equal to the sum of the logs
of the individual variables. If those are already in your model,
adding the log of the product will add nothing more, but will produce
perfect multicollinearity. David Greenberg, Sociology Department, New
York University
On Tue, Aug 21, 2012 at 8:40 AM, D'Souza, Anna - ERS
<[email protected]> wrote:
> Hello,
>
> I am interested in estimating the following model: log y = b0 + b1 log x1 + b2 log x2 + b3 (log x1 * log x2) + e
>
> Question 1: Does anyone have a reference that describes the interaction of logged variables? I am looking for a justification as to why to use "log x1 * log x2" vs. log (x1 * x2).
>
> Question 2: What is the best way to calculate the (i) average marginal effect on x1, and (ii) the marginal effect of x1 evaluated at the mean of x2 in STATA?
>
> Thank you,
>
> Anna
>
>
>
>
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