Re: st: Difference-in-Differences and Panel Data - In search of an adequate regression

[Austin Nichols <austinnichols@gmail.com>]

Sjoerd van Bekkum <vanbekkum@ese.eur.nl>:
OP asked about FE, which presumably are collinear with the treatment
dummy and its interaction. You did not include fixed effects in your
model.  As I noted, the cluster-robust SE *do* make sense, but the FE
probably not (unless some FE not collinear with the treatment are
meant).

On Wed, Jan 2, 2013 at 10:09 PM, Sjoerd van Bekkum <vanbekkum@ese.eur.nl> wrote:
> Maybe my post was too brief. I think what Barbara wants to do (and
> what I meant in my previous post) is, assuming two groups and 2
> (pre-/post) periods:
>
> y = a + b*D(treatment=1) + c*D(post=1) + d*D(treatment=1)*D(post=1) + e,
>
> where D are indicator variables. As mentioned in the paper I cited
> above, this leads to the following groups:
>
> E[y|treated, post] =a+b+c+d
> E[y|treated, pre] = a+b
> E[y|not treated,post] = a+c
> E[y|not treated, pre] = a
>
> with the dif-in-dif captured by
>
> DID = {E[y|treated, post]-E[y|treated, pre]} - {E[y|not
> treated,post]-E[y|not treated, pre]}
>       = {a+b+c+d - (a+b)} - {a+c - a}
>       = d
>
> with cluster-robust errors, as Austin mentioned. I don't see any
> collinearity problems here.
>
>
> On 3 January 2013 02:03, Austin Nichols <austinnichols@gmail.com> wrote:
>>
>> Barbara Engels <engels.ba@gmail.com> :
>> You should certainly use cluster-robust SE to account for repeated
>> observations, but how could you include FE and a dummy for treatment
>> group? With a post dummy, and a treatment dummy, and the interaction,
>> there would be a severe perfect collinearity problem.
>>
>> On Wed, Jan 2, 2013 at 3:49 PM, Barbara Engels <engels.ba@gmail.com>
>> wrote:
>> > Dear Stata people,
>> >
>> > I am currently working on a difference-in-differences model in its
>> > simplest form  - treatment and control group, pre- and post-intervention
>> > period.
>> > However, I got a large panel data set and I wonder what is the best way
>> > to estimate the DID in Stata to account for flaws like serial correlation.
>> > Should I go for a simple
>> >
>> > reg y x  incl. interaction term, ROBUST
>> >
>> > Or should I apply clustering?
>> > Or even xtreg with fe?
>> >
>> > Any help is greatly appreciated.
>> >
>> > Thanks a lot, happy 2013!
>> >
>> > Barbara
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