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


From   박재민 <[email protected]>
To   "\"Martin Weiss\"" <[email protected]>
Subject   st: Re: AW: Re: AW: treatment effect estimation with an ordinal 1st step and a continuous 2nd step
Date   Sun, 18 Jul 2010 05:58:40 +0900

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" <[email protected]>
To: <[email protected]>
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: [email protected] [mailto:[email protected]] Im Auftrag von ???
Gesendet: Samstag, 17. Juli 2010 22:17
An: "Martin Weiss"
Cc: [email protected]
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" <[email protected]>
To: <[email protected]>
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: [email protected]
[mailto:[email protected]] Im Auftrag von ???
Gesendet: Samstag, 17. Juli 2010 15:29
An: [email protected]
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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