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Re: st: Iv reg estimates are too large in stnd errors

From   Austin Nichols <[email protected]>
To   [email protected]
Subject   Re: st: Iv reg estimates are too large in stnd errors
Date   Fri, 20 Nov 2009 10:08:04 -0500

I second Maarten: the large SE reflects the large variance inherent in
IV.  Note that indicates the
effect of sex mix on subsequent fertility is about .02 to .04 so you
will not be using a lot of the variation in your endog var.

However: note two other points--if you have survey data, you should
not use [aw= but instead [pw= and you should cluster to get more
correct SEs.
Also, you have a binary RHS endog var and binary outcome so you may
prefer another estimator, e.g. -biprobit- or -cmp- (on SSC).

Also, why not consider boyfirst an excluded instrument?  Is the worry
that some families who observe the sex before birth choose not to have
a girl first?

On Fri, Nov 20, 2009 at 8:13 AM, Maarten buis <[email protected]> wrote:
> --- On Fri, 20/11/09, Shruti Kapoor wrote:
>> I am using ivreg for the first time and am not sure if i
>> can do anything to improve my results. The biggest problem
>> i am facing is that the stnd errors on my endogenous variable
>> (morethan2children, even when instrumented) is quite high.
>> Which makes them insignificant.
> In general, large standard errors are not a problem, they are
> a finding. We may or may not like that finding, but that is
> irrelevant.
> Specifically with instrumental variables, I am not surprised
> that you find large standard errors. Instrumental variables can
> potentially provide you with a very strong argument that the
> effect you found is likely to be causal, but there is always a
> price to be paid: in the case of instrumental variable the
> price is low power (i.e. large standard errors). As the
> economists say: there is no such thing as a free lunch.
> -- Maarten
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