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Re: st: Heckman Selection Rule


From   Seema Bhatia <[email protected]>
To   [email protected]
Subject   Re: st: Heckman Selection Rule
Date   Fri, 31 Aug 2007 13:39:34 +0100

Hi Georg

Thanks for the insight. there is so ,much confusion around on this and 
someone told m that really it depends upon who is examining the thesis - if 
its a purist they would opt for the former, if not, the latter would do. I 
am trying to be as non subjective as possible.

Hope all is well with you

regards

Seema
----- Original Message ----- 
From: "georg wernicke" <[email protected]>
To: <[email protected]>
Sent: Friday, August 31, 2007 1:31 PM
Subject: Re: st: Heckman Selection Rule


> Dear Seema,
>
> Verbeek(2000) argues that the selection equation should at least
> contain all the variables the structural equation contains. however,
> Linder and de Groot (2006) argue that the variables of the two parts
> can be different.
>
> the unique variable the selection process should contain is probably a
> dummy which is used as the selection identifier. lets say you data for
> workers, some work some are unemployed. then create a dummy whether
> the worker has work or not and use this in the selection equation as
> the identifier.
>
>
>
> hope it helps
>
> georg
>
> On 8/29/07, Seema Bhatia <[email protected]> wrote:
>> Dear All
>>
>> Are there any rules relating to the difference in the number of variables 
>> in
>> the selection equation and the structural equation when estimating the 
>> two
>> stage Heckman model?
>>
>> The stata help files do suggest that the selection equation must have
>> atleast one variable that is not in the outcome equation - does this
>> necessarily mean that the number of variables in the selection equation 
>> are
>> always higher than in the outcome equation?
>>
>> Also, how does one verify that this 'identifying' variable that seperates
>> the two equations is valid in the sense that it determines whether that 
>> case
>> is selected or not but does not determine the LHS in the second step?
>>
>> Any insights would be much appreciated
>>
>> Many thanks
>>
>> Seema
>>
>>
>>
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