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RE: Antwort: st: Interpreting marginal effects with a transformed independent variable in a logit using margins


From   Paul GERRANS <[email protected]>
To   "[email protected]" <[email protected]>
Subject   RE: Antwort: st: Interpreting marginal effects with a transformed independent variable in a logit using margins
Date   Fri, 25 Jun 2010 16:21:46 +0800

Thanks very much Johannes
Paul

-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Johannes Geyer
Sent: Wednesday, 23 June 2010 4:17 PM
To: [email protected]
Subject: Antwort: st: Interpreting marginal effects with a transformed independent variable in a logit using margins

> I have a logit regression with wealth as an independent variable,
> which enters the regression in natural log form.  I then estimate
> the marginal effect at means after the logit
> <margins, dydx(*) atmeans>
> My question relates to the interpretation of the marginal effect. In
> the output it indicates the mean value of wealth is 8.9814 (in its
> natural log form) whereas the mean of wealth is $24873 in its
> original form. I appreciate that by taking the log I have changed
> the distribution and hence the mean values won?t directly translate.

If you exponentiate the mean of the log-transformed variable you get the
geometric mean.

> But my question is how best to report the marginal effect?  If the
> marginal effect is 0.03 for the transformed variable can I talk in
> terms of the original level terms? Can I say the probability
> increases by 0.03 if the wealth increases from $7954 to $21622 which
> is a unit change in the transformed variable (8.9814 to 9.9814) .
> Equivalently would it be okay to estimate the marginal effect at 10.
> 1215 (which is the mean level of the untransformed variable) and
> report the marginal effect as the change in probability for a unit
> change in the log of wealth, which would be 10.1215 to 11.1215 or
> $42738 change in untransformed terms?

I guess there is no "best" method to report log-transformed effects in
your model. But
I agree that the default that you get is hard to interpret. You could
calculate the
marginal effect of a 1 or - if the effect is "too" low - a 10 percent
increase in
wealth from the mean. From my experience, people find this a lot easier to
understand
than an one-unit log increase that is equivalent to some large number.

Or what you could also do is to plot the effect over the whole range of
wealth at some
specified values of the other x-variables:

twoway (function y = invlogit(Constant + B_1 * mean(X) + B_2 *
log(wealth))

Hope this helps,

Johannes







> Appreciate any advice, thanks
> Paul
>
>
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