Re: AW: st: RE: How to understand the linear prediction after -heckman-?

 From [email protected] To statalist<[email protected]> Subject Re: AW: st: RE: How to understand the linear prediction after -heckman-? Date Wed, 30 Sep 2009 00:19:14 +0800

```Dear Martin,
I am sorry for my unclear expression.

I want to get a R-squared after -heckman- comparable to the OLS regression.
In the thread http://n2.nabble.com/st-Re-Stata-Heckman-and-Mills-ratio-tt3707672.html#a3707672, Kit refered to  "you can always create an r^2 measure from the squared correlation of
actual and predicted observations used in the estimation",which I have known from Wooldridge's book before.

Following that, I thougt no matter calculate R-squared from prediction after -heckman- or
from prediction after -reg- with mill the results were the same.

However,Previously I found they were different and after your help I knew it was something to do with the "mill". I know the result of -heckman- is equal to the result of calculation manually in which first do -probit- then -reg- with mill. Why their predictions are different? Namely, why not include "mill" in the prediction?

Only understanding the doubt about the prediction can I manually calculate R-squared.

Thank you very much.

Best regards,
Rose.

----- Original Message -----
From: Martin Weiss <[email protected]>
To: <[email protected]>
Subject: AW: st: RE: How to understand the linear prediction after -heckman-?
Date: 2009-9-29 19:14:42

<>

I am not quite sure what the question really is. If you want some
pseudo-r-squared, look at Nick`s
http://www.stata.com/support/faqs/stat/rsquared.html

-predict- after -heckman- is quite comprehensive. What do you want in

Also note the Cameron and Trivedi (2009) book, which deals with -heckman-
quite comprehensively. http://www.stata-press.com/books/mus.html
See chapter 16.6

HTH
Martin

-----Urspr黱gliche Nachricht-----
Von: [email protected]
[mailto:[email protected]] Im Auftrag von [email protected]
Gesendet: Dienstag, 29. September 2009 11:22
An: statalist
Betreff: Re: st: RE: How to understand the linear prediction after
-heckman-?

Dear Martin,

Indeed, after leaving "mill" out of my -regress- prediction, the results are
the same.

However, which one is correct? To add "mill" in the -heckman- prediction or
to leave it out of my -regress- prediction if I need to get the prediction
and R-squared after -heckman-?

Best regards,
Rose

----- Original Message -----
From: Martin Weiss <[email protected]>
To: <[email protected]>
Subject: st: RE: How to understand the linear prediction after -heckman-?
Date: 2009-9-29 03:03:45

<>

You have to leave "mill" out of your -predict-ion...

**************
use http://www.stata-press.com/data/r11/womenwk.dta, clear

heckman wage educ age, /*
*/ select(married children educ age)/*
*/ twostep mills(mill)
predict yheck

reg wage educ age mill
gen yreg=_b[_cons]+_b[educ]*educ + /*
*/ _b[age]*age

su y*
compare yheck yreg
**************

HTH
Martin

-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of [email protected]
Sent: Montag, 28. September 2009 19:38
To: statalist
Subject: st: How to understand the linear prediction after -heckman-?

Dear statalists,
In my mind, the result of -heckman- is the same as the result of -reg- with
lambda as an additional independent variable. However, I found something
different.
I typed the following in the stata, and the related results are as
followings.

. qui heckman wage educ age, select(married children educ age) twostep
mills(mill)

. qui predict double yheck if wage!=.

. qui corr yheck wage if wage!=.

. di r(rho)^2
.2512235

. qui reg wage educ age mill if wage!=.

. qui predict double yreg if wage!=.

. qui corr yreg wage if wage!=.

. di r(rho)^2
.27934983

. su yheck yreg

Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
yheck | 1343 21.96174 3.717985 14.79669 32.88486
yreg | 1343 23.69217 3.332614 16.22861 33.78897

The predicted value should be the same and the R-squared should be the same
too.

Why different?

Hope for any help and thank you very much.

Best regards,

Rose.

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