Thanks so much, everyone, that answers my question. (And thanks Roger
for pointing me to the helpful package). I have one last question: I
am trying to understand the "elasticity" of a health indicator with
respect to GDP (that is, how does a marginal increase in GDP affect
the health indicator?). If I regress ln(healthindicator) on ln(gdp),
is the coefficient on ln(gdp) an appropriate way of measuring this
elasticity? I realize this is more of an econometrics question than a
Stata question, but everyone has been so helpful I thought I'd might
as well ask.
Thanks again,
Dorothy
On Tue, Sep 8, 2009 at 10:52 AM, Austin Nichols<[email protected]> wrote:
> Dorothy Bridges<[email protected]>:
> The linear model and the log-log model make very different assumptions
> about the data-generating process, so you should not expect to get the
> same estimates from them. -mfx- after a linear model in particular
> will give approximate estimates that are very questionable--note that
> if the true model is
> y=Xb+e
> then the elasticity of y with respect to x (a variable, or column of
> X) will vary as x varies.
>
> On Tue, Sep 8, 2009 at 10:32 AM, Dorothy Bridges<[email protected]> wrote:
> I still
>> don't see, then, how mfx, eyex gives me a value different than the
>> coefficient on lnx in regress lny lnx. Thanks again for all your
>> thoughts.
>>
>>
>> On Tue, Sep 8, 2009 at 10:20 AM, Maarten buis<[email protected]> wrote:
>>> --- On Tue, 8/9/09, Dorothy Bridges wrote:
>>>> But what I don't understand is: the second method
>>>> (using mfx, eyex) gives me a different value than
>>>> the first method (storing the coefficient on x
>>>> from *regress lny lnx*). Why?
>
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