st: RE: Re: AW: Re: AW: treatment effect estimation with an ordinal 1st step and a continuous 2nd step

["Martin Weiss" <martin.weiss1@gmx.de>]

<>

Let`s cc him on this message. Given that an official example does not work, I would say this step is warranted...


HTH
Martin

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of ???
Sent: Samstag, 17. Juli 2010 22:59
To: "Martin Weiss"
Cc: statalist@hsphsun2.harvard.edu
Subject: st: Re: AW: Re: AW: treatment effect estimation with an ordinal 1st step and a continuous 2nd step

Dear Martin,

Yes, you are right.

It gives the exactly identical outcome.

Thanks much, and it hleps me much anyway.

Do you think it would be better to send an inquiry to Dr. Rooman at the 
Center for Global Development.

Jaemin



----- Original Message ----- 
From: "Martin Weiss" <martin.weiss1@gmx.de>
To: <statalist@hsphsun2.harvard.edu>
Sent: Sunday, July 18, 2010 5:38 AM
Subject: st: AW: Re: AW: treatment effect estimation with an ordinal 1st 
step and a continuous 2nd step


>
> <>
>
>
> The official example seems to run into the same problem:
>
>
> *************
> cmp setup
> webuse womenwk, clear
> gen selectvar = wage<.
> gen wage3 = (wage > 10)+(wage > 30) if wage < .
> cmp (wage3 = education age) (selectvar = married children education age), 
> ind(selectvar*$cmp_oprobit $cmp_probit) qui
> *************
>
>
>
> HTH
> Martin
>
> -----Ursprüngliche Nachricht-----
> Von: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von ???
> Gesendet: Samstag, 17. Juli 2010 22:17
> An: "Martin Weiss"
> Cc: statalist@hsphsun2.harvard.edu
> Betreff: st: Re: AW: treatment effect estimation with an ordinal 1st step 
> and a continuous 2nd step
>
> Dear Martin,
>
> Thanks for your comment.
> It was helpful.
>
> However, the following syntax
>
> xi: cmp (y1  = x1) (y2 = x2 y1), ind(5 1)
>
> where y1 = ordinal numbers like 1, 2, 3, 4
>          y2 = continuous
>
> gives an error sign  like "matrix___00000B not found"
>
> And the program shows (y1 = x1) result only, which is exactly identical to
> the outcome from an (oprobit y1 x1) regression.
>
> Thanks in advance.
>
> Jaemin
>
>
>
>
>
> ----- Original Message ----- 
> From: "Martin Weiss" <martin.weiss1@gmx.de>
> To: <statalist@hsphsun2.harvard.edu>
> Sent: Saturday, July 17, 2010 10:45 PM
> Subject: st: AW: treatment effect estimation with an ordinal 1st step and 
> a
> continuous 2nd step
>
>
>>
>> <>
>>
>> Try
>>
>> *************
>> ssc d cmp
>> *************
>>
>>
>>
>> HTH
>> Martin
>>
>> -----Ursprüngliche Nachricht-----
>> Von: owner-statalist@hsphsun2.harvard.edu
>> [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von ???
>> Gesendet: Samstag, 17. Juli 2010 15:29
>> An: statalist@hsphsun2.harvard.edu
>> Betreff: st: treatment effect estimation with an ordinal 1st step and a
>> continuous 2nd step
>>
>> Hi all!
>>
>> I want to run a treatment effects model.
>>
>> In my case, the 1st step dependent var. is ordinal (for exmaple,
>> "perfectly
>> not matched", "not matched", "matched", and "perfectly matched"), and the
>> 2nd step dependent var. is continuous (for example, wage in log).
>> I have run the similar model using "treatreg" command if the 1st step
>> depednat is binary.
>>
>> Is there any command working in this case.
>>
>> I found "mtreatreg" is available if
>> (1) 1st step dependent var. is multivariate and
>> (2) 2nd step DV is continuous
>>
>> Of course, 1st step ordinal treatment variable should be shown in the 2nd
>> step equation as an independent variable explicitly.
>>
>> P.S.: I don't think running "oprobit" as the 1st step, and insertting IMR
>> from it as independent variable into the 2nd step OLS regression is 
>> valid.
>>
>> Thanks,
>> jaemin
>>
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