# Re: Rép. : Re: st: Interpretation of -mfx-

 From "Joao Ricardo F. Lima" To statalist@hsphsun2.harvard.edu Subject Re: Rép. : Re: st: Interpretation of -mfx- Date Thu, 19 Jun 2008 19:22:05 -0300

```Maarten,

sorry this simple question.

mfx (marginal effects) are change in probabilities, when we are using
logit, mlogit ...

margeff (partial effects) are change in probabilities too?

Thanks,

Joao Ricardo Lima

2008/6/19, Maarten buis <maartenbuis@yahoo.co.uk>:
> --- Herve STOLOWY <stolowy@hec.fr> wrote:
>> I use the auto file and make a logit regression followed by mfx.
>>
>> sysuse auto
>> logit  foreign mpg weight price
>> mfx
>>
>> Here is my question: in the logit ouput, the coefficients on weight
>> and price are significant. In the mfx output, the corresponding
>> coefficients of dy/dx are NOT significant. How should I interpret
>> this result?
>
> -mfx- summarizes a non-linear relationship using the slope when all
> explanatory variables have their mean value. As can be seen in the
> graph  created in the example below, the slope is steepest (effect is
> highest) on the right, which is also where most of the data is. However
> because the distribution is right skewed, the mean is to to right of
> where most of the data is and where the effect happens to be strongest.
> The log odds ratio also summarizes the slope with a single number, but
> this number is independent of at what value of mpg it is evaluated, so
> it is not subjected to this problem.
>
> An alternative is to compute the marginal effect for each individual,
> and than compute the average of these marginal effects. This is close
> to what is done in Tamas Bartus' -margeff- package, downloadable from
> -ssc-. Except that he uses partial effects instead of marginal effect.
> To quote from his helpfile: "Partial effects are discrete partial
> changes in the quantities of interest as the variable under study
> increases by the unit of measurement.  For dummy variables (variables
> coded 0/1) and count  variables, unit of measurement is 1. This partial
> change approach eases computations, and approximates very well the
> partial changes calculated using the classic marginal effects
> approach."
>
> Hope this helps,
> Maarten
>
> *---------- begin example ----------------
> set more off
> sysuse auto, clear
> logit  foreign mpg weight price
> mfx
> adjust  weight price, by(mpg) pr gen(pr)
> sum mpg if e(sample), meanonly
> twoway line pr mpg, sort       ///
>    xline(`r(mean)')            ///
>    ysca(alt)                   ///
>    xsca(alt range(10 43))      ///
>    saving(pr, replace)
> twoway histogram mpg, fraction ///
>    xlab(10(10)40)              ///
>    ysca(alt reverse)           ///
>    xscale(range(10 44))        ///
>    saving(hy, replace)         ///
>    fysize(25)
> graph combine pr.gph hy.gph,   ///
>    cols(1)                     ///
>    imargin(0 0 0 0)            ///
>    graphregion(margin(l=22 r=22))
> margeff
> *---------- end example ------------------
> (For more on how to use examples I sent to the Statalist, see
> http://home.fsw.vu.nl/m.buis/stata/exampleFAQ.html )
>
> -----------------------------------------
> Maarten L. Buis
> Department of Social Research Methodology
> Vrije Universiteit Amsterdam
> Boelelaan 1081
> 1081 HV Amsterdam
> The Netherlands
>
> Buitenveldertselaan 3 (Metropolitan), room Z434
>
> +31 20 5986715
>
> http://home.fsw.vu.nl/m.buis/
> -----------------------------------------
>
>
>       __________________________________________________________
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>

--
-------------------------------
Joao Ricardo Lima
Professor
UFPB-CCA-DCFS
+553138923914
-------------------------------
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```