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Re: st: Regression Discontinuity Design


From   Nick Cox <njcoxstata@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Regression Discontinuity Design
Date   Thu, 6 Oct 2011 23:48:29 +0100

You could start by

. findit regression discontinuity

That leads you to a program -rd-, its help and a long paper with a lot
of references

Nichols, Austin. 2007.  Causal Inference with Observational Data.
Stata Journal 7(4): 507-541.

which is freely available at
http://www.stata-journal.com/sjpdf.html?articlenum=st0136

On Thu, Oct 6, 2011 at 11:39 PM, Nyasha Tirivayi <ntirivayi@gmail.com> wrote:
> Hello
>
> I have questions about implementing a regression discontinuity
> approach. I have cross sectional data from 200 households on a social
> program and 200 control households. The program was targeted at two
> levels- geographically and at household level.
>
> The geographic placement of the social program in communities appears
> to have been done based on HIV prevalence rates of more than 20.5% for
> 3 "treated" communities and less than 20.5% for 3 "control
> communities". Two clinics do not follow this cutoff making it a fuzzy
> discontinuity design at community level. After geographic placement,
> households were then selected based on a means tested score. However
> we do not have access to this data. We have data from 200 randomly
> sampled households who are actually in the social program and residing
> in the treated communities and from 200 control households with
> similar household characteristics to the treated households but
> residing in the control communities.
>
> My questions are as follows:
> 1. Would it be valid to use the community level discontinuity for
> impact evaluation? What software can I use in Stata?
> 2. If so would an RD approach based on 8 communities be valid? Is the
> sample of communities too small?
> 3. If RD is no appropriate what other methods besides propensity score
> matching can I use, that can also take care of unobservables even with
> cross sectional data?
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