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Re: st: ICE and instrumental variables

 From Richard Williams <[email protected]> To [email protected], [email protected] Subject Re: st: ICE and instrumental variables Date Fri, 18 Oct 2013 10:28:08 -0500

This may or may not not include the answers to your specific questions, but an excellent online resource for learning about multiple imputation is at
```
http://www.ssc.wisc.edu/sscc/pubs/stata_mi_intro.htm

At 09:17 AM 10/18/2013, James Bernard wrote:
```
```Thanks Stas,

Then, may I ask even a more basic question:

The more rudimentary method is to replace the missing values with
average.And, then to use Ivreg/2SLS etc.

Is this also too problematic?

As you said, the use of ivreg with imputation is problematic. Would
the mean-substitution make it worse.

Given all these costs, woudl it be better to forget imputation and
mean-replacement altogether?

Thanks again,

James

On Fri, Oct 18, 2013 at 10:06 PM, Stas Kolenikov <[email protected]> wrote:
> 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
>
> -- 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
> -- http://stas.kolenikov.name
>
>
>
```
> On Fri, Oct 18, 2013 at 8:46 AM, James Bernard <[email protected]> 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
>>
>>
>> James
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