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st: RE: instruments in ivreg2


From   "Steven Stillman" <steven@thestillmans.org>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: instruments in ivreg2
Date   Sun, 22 Oct 2006 19:37:08 +1300

Hi Bidisha.

As Kit points out, it is fine to use a time-invariant variable as an
excluded instrument for a time-variant endogenous variable, but you are
quite likely to end up with a weak instrument problem.

Depending on your data, you might be able to create slightly more
informative time-variant instruments such as the number of cumulative years
of each parent's current marriage or number of years since being married if
not-married, cumulative number of marriages for each parent, average length
of each parents marriages, etc.  If your data allows you to create more than
one instrument of this flavour, you could then run an overidentification
test.  You would still need to carefully test that none of these instruments
was weak.

Cheers,
Steve

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of Kit Baum
Sent: Sunday, October 22, 2006 1:59 PM
To: statalist@hsphsun2.harvard.edu
Subject: st: instruments in ivreg2


Bidisha said

d(mental health) = a1 + d(marital status) + d(income) + e1

You realize that the presence of the constant in this equation
implies that there is a trend in mental health status? Although many
of us may feel that way, I wonder if you really mean that. Same issue
arises for the second equation.

As to your question -- whether you can use parents' marital status
(presumably still married v. divorced or widowed) as an instrument
for the change in marital status observed in your sample... Surely
you will observe some changes in your sample. For parents' status to
be a valid instrument, it must be correlated with the endogenous
measure ( d(mar.status)) and independently distributed of the error
e1. The latter is reasonable, given that parental status is
predetermined; but I wonder how well correlated it will be to the
included measure. Look at the first stage regression results closely.

As you have written them, both of these equations appear exactly
identified, so that you cannot carry out any overid tests.

Kit Baum, Boston College Economics
http://ideas.repec.org/e/pba1.html
An Introduction to Modern Econometrics Using Stata:
http://www.stata-press.com/books/imeus.html


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