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st: Fixed effects with a 'future-lagged' variable


From   Anna Reimondos <areimondos@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: Fixed effects with a 'future-lagged' variable
Date   Fri, 13 Feb 2009 15:15:18 +1100

Hello,
I have fixed effects question I was hoping I could get some help with.
I am estimating a model that looks at changes in attitudes within
individuals over time. I am focusing on individuals who have never had
a child, and I am interested in seeing how attitudes (measured on a
scale from 0 -10 ) change after the birth of a child.

e.g xtreg attitude child etc, fe

 I except that attitudes increase slightly after the birth of the
first child, but looking at the data I see that the year the child is
actually born, attitudes fall quite dramatically, but they  do pick up
once the child gets past the first year of age surpassing what they
were before the birth. An example would be (with the data in long
format):

ID   Year       Child   Child (f-lagged)  Attitude
1     2001        0          0                     8
1     2002        0          0                     7
1     2003        1          0                     2
1     2004        1          1                     9
1     2005        1          1                    10


In my model I would like to exclude the first year from entering into
the estimation of the effect of having a child because this makes the
coefficient for the dummy variable describing whether there is a child
negative.  I tried to this by having a 'future lagged' variable which
is only equal to 1 if it is at least one year after the birth of the
child (to avoid including the dramatic drop just around the birth of
the child). (see example).

As I understand fixed effects models, they work by de-meaning the
data, so the mean of all the predictors and the dependent variable is
worked out for each individuals and then at each time point the
observed value is compared with the mean. I am worried that by doing
this, i.e by using the future-lagged variable instead of the normal
child variable, I am pushing the low value just around childbirth
(value of 2 in year 2003) in this case to the wrong side of the dummy
variable artificially making it look like there is a greater positive
change after childbirth than before.
Would it be better to just drop the year out of the analysis
completely? I am worried about  doing this since then I will lose
possible variation in other time-varying variables I am interested in.
Would a dummy variable, which is only equal to 1 for the year the
child was born make more sense instead?

I hope this question makes sense.
Any advice would be greatly appreciated.

Anna
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