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re: Re: Re: st: Regression discontinuity with interrupted time series


From   "Ariel Linden. DrPH" <ariel.linden@gmail.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   re: Re: Re: st: Regression discontinuity with interrupted time series
Date   Fri, 8 Mar 2013 14:27:31 -0800

Hi Austin,

This is very nice simulation you put together here. I am still having
problems conceptualizing how the two approaches can be combined in a
meaningful way, but I suppose we can wait and see how the grantees write up
their findings...

Ariel  

Date: Thu, 7 Mar 2013 16:03:08 -0500
From: Austin Nichols <austinnichols@gmail.com>
Subject: Re: Re: st: Regression discontinuity with interrupted time series

Ariel <ariel.linden@gmail.com>:
I would not go that far.  I suggested one way forward that I thought
would be easy to interpret, and one that was harder to interpret, but
there are others.  The OP seems to want a packaged solution marrying
RD and ITS, based on e.g.
 http://ies.ed.gov/funding/grantsearch/details.asp?ID=754
but I suspect a more nuanced approach will be easier to swallow both
for the applied researcher and his readers.

Another way forward is to note the connection of a trend difference to
the "regression kink" design.

My concern was that the OP has one instrument and may want to estimate
two impacts: a difference in level at time t and a difference in trend
for time>=t. One can adopt a control function approach or use the
interaction of the instrument A (for "above the cutoff") with t as a
second instrument, which was my second suggestion for a way forward.
The key there is that At is zero for all time before the intervention,
and is used as an instrument for Tt, so that term is picking up the
change in trend (the discontinuous jump in dy/dt, not the
discontinuous jump in y).


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