Re: st: RE: Difference-in-difference, serial correlation, and robust standard errors

[Glenn Landers <landers.glenn@gmail.com>]

Thanks Mark. That answers my question.

Glenn

On Mon, Sep 3, 2012 at 1:24 PM, Schaffer, Mark E <M.E.Schaffer@hw.ac.uk> wrote:
> Glenn,
>
> In general, the use of the -robust- option in Stata addresses
> heteroskedasticity only.  -cluster-, on the other hand, gives you SEs
> that are robust to both heteroskedasticity and within-group correlation,
> and the latter, in the panel data context, would normally mean
> within-panel serial correlation.
>
> In the case of -xtreg-, however, -robust- automatically triggers the use
> of cluster-robust SEs.
>
> One thing worth checking - are your fixed effects at the state or county
> level?  The problem is that the asymptotics behind the cluster-robust
> covariance estimator rely on the number of groups going off to infinity.
> If your FEs are at the county level, and you use cluster-robust SEs,
> there's no problem in your case - you have 840 counties.  But if your
> FEs are at the state level, then you have a problem - you have only 17
> states, and 17 isn't very far on the way to infinity.
>
> HTH,
> Mark
>
>> -----Original Message-----
>> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-
>> statalist@hsphsun2.harvard.edu] On Behalf Of Glenn Landers
>> Sent: 02 September 2012 14:28
>> To: statalist@hsphsun2.harvard.edu
>> Subject: st: Difference-in-difference, serial correlation, and robust
> standard
>> errors
>>
>> I am a novice. I am using StataIC V11.
>>
>> Does the robust option correct for serial correlation as well as
>> heteroskedasticity? Wooldridge seems to say so in his Introductory
>> Econometrics 4th ed. text (although his comment is specific to robust
>> standard errors and not specifically Stata), and I have seen a few
> references
>> here.
>>
>> I am running an OLS difference in difference. I am testing state and
> county
>> laws at the county level with quarterly data for three years for each
>> state/county. I have 17 states, 840 counties, and 12 periods per
> county =
>> 10,800 observations. I am trying to be conscious of serial
> correlation, as
>> Bertrand et al (2000) as well as others point out, but I am also aware
> my data
>> seem to fit the case Bertrand describes where laws are not all
> implemented
>> at the same time, and the serial correlation problem goes away.
>> My data range from 2002 to 2009, but I have three years for each
>> state/county, so the laws are implemented at varying times across
> those
>> eight years. Still, I would like to run a test for serial correlation
> just to be sure.
>>
>> Colleagues have suggested xtreg, and I have implemented that and
> xtserial,
>> but it seems in arraying the 840 counties in panels of 12 periods each
>> (1-12) and bringing the implementation dates of the laws more into
>> alignment, I am imposing the serial correlation problem on the data
> that I am
>> trying to test for. In fact, the data demonstrate serial correlation
> when
>> implementing xtserial.
>>
>> I know the data are heteroskedastic. Does implementing the the robust
>> option also correct for any serial correlation that might be present,
> short of
>> having a test for serial correlation that does not implementing xtreg
> or
>> xtserial?
>>
>> Thank you.
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