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Re: st: Using suest after mfx2 or margeff - error r(322)
From
Amanda Fu <[email protected]>
To
[email protected]
Subject
Re: st: Using suest after mfx2 or margeff - error r(322)
Date
Sun, 29 Apr 2012 21:31:03 -0400
Thank you!
On Sun, Apr 29, 2012 at 9:07 PM, Jorge Eduardo Pérez Pérez
<[email protected]> wrote:
> See Example 10 of the reference manual entry for -margins-
> _______________________
> Jorge Eduardo Pérez Pérez
>
>
> On Sun, Apr 29, 2012 at 7:23 PM, Amanda Fu <[email protected]> wrote:
>> Hi all,
>>
>> I would like to test the difference of the marginal effects (not
>> coefficients) for a variable across probit regressions. When checking
>> previous discussion, I find my question is exactly the same with the
>> following early one, but no one answered it.
>>
>> I think there must be something wrong with my question. Would someone
>> please give me some hints? Thanks!
>> ---------------------------------
>> probit y a1 a2 a3 if male==1
>> mfx compute
>> est store MALE
>>
>> probit y a1 a2 a3 if female==1
>> mfx compute
>> est store FEMALE
>> suest MALE FEMALE
>> test [MALE_mean]a1=[FEMALE_mean]a1
>> ----------------------------------------
>> Amanda
>>
>> On Sun, Nov 21, 2010 at 9:10 AM, <[email protected]> wrote:
>>> Hello STATA users,
>>>
>>> I try to use the suest command after estimating two different sets of marginal effects at the mean with mfx2 or margeff from two different probit regressions. I intend to compare the differences between the marginal effects betwenn the two probit regressions whether they differ significantly with Wald tests. For this I first want to use suest to have one set of marginal effects from both probit regressions. Unfortunately the stored marginal effects, as if mfx2 or margeff were estimation commands, provide the following error message
>>>
>>>
>>> . suest unadvised non_bulge_bracket
>>> unable to generate scores for model unadvised
>>> suest requires that predict allow the score option
>>> r(322);
>>>
>>> "unadvised" and "non_bulge_bracket" are the names I gave to the stored marginal effects:
>>>
>>> probit follow_on_bid industry_experience_deals_A ... if advisory_choice==1
>>> margeff, at(mean) replace
>>> estimates store unadvised
>>>
>>> probit follow_on_bid industry_experience_deals_A ... if advisory_choice==2
>>> margeff, at(mean) replace
>>> estimates store non_bulge_bracket
>>>
>>> suest unadvised non_bulge_bracket
>>>
>>> test [unadvised=non_bulge_bracket], common
>>>
>>> test [unadvised]industry_experience_deals_A=[non_bulge_bracket]industry_experience_deals_A
>>> . ..
>>>
>>> With regular probit regression coefficients it works perfectly, but not with the stored marginal effects. Do you have an idea how I can proceed?
>>>
>>> Kind regards and thanks for your help
>>>
>>> Pascal
>>>
>>>
>>>
>>>
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>>
>> *
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>>
>
>
> *
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