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Re: st: model specification


From   William Buchanan <william@williambuchanan.net>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: model specification
Date   Mon, 14 Nov 2011 07:56:07 -0800

I agree with Cameron.  However, if you have data on how much aid was offered to students that may provide more useful, compared to the amount of aid that students accepted and/or used. One of the other issues I could see are differences in financial aid that is made available based on the students major, which may impact the career field that they enter after graduation.  

- Billy

Sent from my iPhone

On Nov 14, 2011, at 7:38, Jet <lsj555@gmail.com> wrote:

> Thanks, Cam. Did you ever see any similar issues with some empirical
> research? Would you mind giving some examples?
> 
> How about opinions from others on this listserv?
> 
> On Sun, Nov 13, 2011 at 11:31 PM, Cameron McIntosh <cnm100@hotmail.com> wrote:
>> Endogeneity or a tautology? :) I would only use predictors not used to compute the outcome. Cam
>> 
>>> Date: Sun, 13 Nov 2011 12:24:27 -0500
>>> Subject: st: model specification
>>> From: lsj555@gmail.com
>>> To: statalist@hsphsun2.harvard.edu
>>> 
>>> Hello, we have a model specification question and would appreciate any
>>> suggestions. If the outcome measures the college graduates' debt
>>> burden (ratio of monthly loan payment to monthly income), and we'd
>>> like to see what factors predict their debt burden a couple of years
>>> after graduation. Does it make sense to include financial aid
>>> variables (grants, merit aid, loans they received during undergrad) as
>>> predictors, given that they are a part of the outcome?  Would it raise
>>> any endogeneity issue?
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