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Re: st: AW: mfx-Elasticity for a dummy variable
From
Nyasha Tirivayi <[email protected]>
To
[email protected]
Subject
Re: st: AW: mfx-Elasticity for a dummy variable
Date
Wed, 9 Jun 2010 17:15:06 +0200
Dear Antonis and Martin
Thanks for your reply. If you recall my model is as follows:
ln(y) = a + b ln(x) + T + D Z
I intend to calculate elasticity for T at T=1 and at means of ln(x)
and ln(Y). And if I do that the elasticity is the same as the
coefficient of T.
Should I proceed with that as the answer?
Kindly advise
Nyasha Tirivayi
Maastricht University
On Tue, Jun 8, 2010 at 1:27 PM, A Loumiotis <[email protected]> wrote:
> Yes I agree... although one can compute it at the mean point of T
> which is different from 0 or 1. But as I said in my first response
> elasticities with respect to dummy variables have no meaningful
> interpretation.
>
> On Tue, Jun 8, 2010 at 2:18 PM, Martin Weiss <[email protected]> wrote:
>>
>> <>
>>
>> " ...will be the coefficient of the dummy
>> variable T divided by the dummy variable itself."
>>
>>
>> I do not get this sentence. The dummy is either 0 or 1, as you said.
>> Dividing by zero is not permissible, and dividing by one does not change
>> anything, does it?
>>
>>
>>
>> HTH
>> Martin
>>
>> -----Ursprüngliche Nachricht-----
>> Von: [email protected]
>> [mailto:[email protected]] Im Auftrag von A Loumiotis
>> Gesendet: Dienstag, 8. Juni 2010 13:15
>> An: [email protected]
>> Betreff: Re: st: AW: mfx-Elasticity for a dummy variable
>>
>> The elasticity of y with respect to the dummy variable in the way that
>> you have defined your regression will be the coefficient of the dummy
>> variable T divided by the dummy variable itself.
>>
>> On Tue, Jun 8, 2010 at 2:05 PM, A Loumiotis <[email protected]>
>> wrote:
>>> Nyasha,
>>>
>>> The elasticity of y with respect to the dummy variable in the way that
>>> you have defined your regression will be the coefficient of the dummy
>>> variable T times the dummy variable itself. If you calculate it at
>>> the mean point of T then it will be different from the coefficient of
>>> the dummy variable. If you calculate it at T=1, it will be the same.
>>>
>>> However elasticities with respect to dummy variables have no
>>> meaningful interpretation because the dummy variable changes in a
>>> discrete fashion (from 0 to 1).
>>>
>>> Antonis Loumiotis
>>>
>>> On Mon, Jun 7, 2010 at 6:24 PM, Nyasha Tirivayi <[email protected]>
>> wrote:
>>>> Dear Martin
>>>>
>>>> Thanks for the code. Now the results are different. I was using the
>>>> wrong code i.e mfx , dyex at(mean) instead of mfx compute,
>>>> varlist(logweight) dyex at(mean).
>>>>
>>>> Regards
>>>>
>>>> Nyasha Tirivayi
>>>> Maastricht University
>>>>
>>>>
>>>>
>>>> On Mon, Jun 7, 2010 at 9:16 AM, Martin Weiss <[email protected]>
>> wrote:
>>>>>
>>>>> <>
>>>>>
>>>>> What is the difference of your example to this one - where the marginal
>>>>> effects do seem to change:
>>>>>
>>>>>
>>>>> *************
>>>>> sysuse auto, clear
>>>>> gen logprice=log(price)
>>>>> gen logweight=log(weight)
>>>>> reg logprice length logweight foreign
>>>>> mfx compute, varlist(logweight) dydx at(mean)
>>>>> mfx compute, varlist(logweight) eyex at(mean)
>>>>> mfx compute, varlist(logweight) dyex at(mean)
>>>>> mfx compute, varlist(logweight) eydx at(mean)
>>>>> *************
>>>>>
>>>>>
>>>>>
>>>>> HTH
>>>>> Martin
>>>>>
>>>>> -----Ursprüngliche Nachricht-----
>>>>> Von: [email protected]
>>>>> [mailto:[email protected]] Im Auftrag von Nyasha
>> Tirivayi
>>>>> Gesendet: Montag, 7. Juni 2010 02:50
>>>>> An: [email protected]
>>>>> Betreff: st: mfx-Elasticity for a dummy variable
>>>>>
>>>>> Dear All
>>>>>
>>>>> I am trying to estimate elasticity for a dummy explanatory variable in
>>>>> the following model
>>>>>
>>>>> ln(y) = a + b ln(x) + T + D Z
>>>>>
>>>>>
>>>>>
>>>>> I am interested in calculating the elasticity for T a dummy variable
>>>>> for a "treatment". What is the formula in stata? Is it mfx,dy/dx or
>>>>> mfx,dyex?
>>>>>
>>>>>
>>>>>
>>>>> I have done mfx,dyex and the result still remains the coefficient for
>>>>> T. Could it be that simple? Or there is another way ?
>>>>>
>>>>>
>>>>>
>>>>> Kindly advise
>>>>>
>>>>>
>>>>>
>>>>> Nyasha Tirivayi
>>>>>
>>>>> Maastricht University
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>
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