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Re: st: ICE and instrumental variables

From   Stas Kolenikov <>
To   "" <>
Subject   Re: st: ICE and instrumental variables
Date   Fri, 18 Oct 2013 09:06:23 -0500

Nope, this approach won't make sense, as it will bias both the point
estimates and the standard errors. And if you think it does, you just
need to read more to understand WHY multiple imputation works.
Essentially, what you have proposed is the (conditional) mean
imputation, which squeezes variability... which of course is great if
you want to raise your reported R^2 from 0.1 to 0.6, right?

What you need to do is to follow the mainstream workflow of multiple
imputation: impute a bunch of data sets (M=5 is a funny number that is
only good for estimation of the means; computer power is not a scarce
resource it was in 1970s when Don Rubin introduced multiple
imputation), run -ivregress 2sls- on each, and combine them with -mi
estimate, cmdok-.

There is little research about the properties of IV estimates under
multiple imputations, as economists basically don't trust this heavily
model driven method, and the clash with a less heavily parametric
IV/GMM paradigm is inevitable, but assuming that multiple imputation
captures the first two moments of the full distribution of the data
properly, you should still have the asymptotic properties of IV to
hold. Of course, the tests like weak instruments would require another
scratch on the forehead.

-- Stas Kolenikov, PhD, PStat (ASA, SSC)
-- Senior Survey Statistician, Abt SRBI
-- Opinions stated in this email are mine only, and do not reflect the
position of my employer

On Fri, Oct 18, 2013 at 8:46 AM, James Bernard <> wrote:
> Hi all,
> I am newbie to imputation. I have been trying -ice- for imputation.
> What I realized is that -ice- is just the imputation part. The imputed
> part them can be used for estimation with -mi- (count models, etc).
> I browsed through the list server and found out that people were
> confused if they can use -mi-estimation for instrumental variables
> (2SLS).
> It would be good if we can use ivreg with -mi-.
> If not, would this approach make any sense:
> 1- impute the data using ice (e.g., M=5)
> 2-take the average of the imputed cells and replace the missing with
> that average.
> 3- use the dataset with usual "ivreg"/2SLS commands
> Thanks in advance,
> James
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