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Re: st: calculating standard deviation of age at death from period life tables

From   Austin Nichols <>
Subject   Re: st: calculating standard deviation of age at death from period life tables
Date   Tue, 9 Mar 2010 10:57:31 -0500

Johannes Schoder <>:
I would bet that investments in health or technology changes do
immediately translate into longer life expectancy, but that life
expectancy is not measured for the affected cohorts but for a mix of
cohorts, only some of which enjoy the full effect of the
investment/change (life expectancy for a given cohort cannot actually
be measured until everyone in the cohort is dead).  But assuming you
want to assess the short-run effect of changes in X and the long-run
effect of changes in X, you might consider including the first
difference divided by two and the two-period moving average, i.e.
y_it = b ( X_it - X_it-1 )/2 + c  ( X_it + X_it-1 )/2 +e
where if b=c the model is identical to one with only contemporaneous
regressors.  The MA term captures long-run effects and the FD term
captures short-run effects.  For finer structure, you can apply some
kind of filtering; see e.g.
on MA and FD and an extension to multiple terms and see
on those multiple terms, and
on further methods.

On Tue, Mar 9, 2010 at 9:46 AM, Johannes Schoder
<> wrote:
> Dear Statalist users:
> I am trying to find the optimal lag structure of my health production
> function (lags are usually included because e.g. lifestyle effects do not
> immediately translate into longer life expectancy) which looks like that:
> where c=COUNTRY and t=YEAR
> Is there a test implemented in Stata which tells me e.g. whether to include
> GDP lagged 5 years, 10 years or 0 years?
> Thanks a lot for any hint!
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