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Re: st: RE: IV with incomplete data on endog var

From   Roger Harbord <[email protected]>
To   [email protected]
Subject   Re: st: RE: IV with incomplete data on endog var
Date   Thu, 21 Jul 2005 22:06:51 +0100

Many thanks, Dann and Scott. I had a quick look at the Angrist paper in JBES and it's clearly related but i'd need to work through all their algebra to work out exactly how my case differs, so Dann's idea of bootstrapping sounds attractive at the moment...

I'd be a little surprised if no-one's come across my situation before though - in some situations it seems to me that as long as you have enough info on the endogeneous variable to avoid problems of weak instruments then its the instrument-outcome association that mainly determines the power (particularly for dichotomous outcomes) and hence collecting data on the instrument and outcome only for most individuals becomes attractive (esp. if the endogenous variable is the most difficult/expensive to collect...) Of course need to be sure those with data on the endogenous variable are representative of those without.


--On 20 July 2005 15:14 -0500 [email protected] wrote:

I believe the paper is:

Angrist, Joshua D. and Alan B. Krueger (1995). "Split-Sample
Instrumental Variables
Estimates of the Returns to Schooling." Journal of Business and
Economic Statistics 13:2, 225-235.

The working paper version can be obtained at:


----- Original Message -----
From: "Millimet, Daniel" <[email protected]>
Date: Wednesday, July 20, 2005 11:40 am
Subject: st: RE: IV with incomplete data on endog var

it seems that a two-step procedure where you form out of sample
predictions of the endogenous var and then do the 2nd stage with
the predicted regressor would yield valid estimates and that a
bootstrap procedure would yield valid inference.  this sounds
related to some papers by angrist on a procedure called split-
sample IV.  i think the paper i am thinking of was published in
journal of applied econometrics.  if you can't track it down, feel
free to email me and i can look for it.

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