st: RE: two-way clustering advice

["Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>]

Dmitry,

Have you tried using the partial() option to partial out anything that
isn't of interest?  Maybe your dcid* dummies?  This can reduce the
dimensions of the matrices -ivreg2- is working with quite a lot, and
that would speed things up as well as improve the numerical accuracy.

HTH,
Mark

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-
> statalist@hsphsun2.harvard.edu] On Behalf Of Dimitriy V. Masterov
> Sent: 30 August 2012 00:08
> To: Statalist
> Subject: st: two-way clustering advice
> 
> I am estimating a twelfth-difference panel data equation. My panels
are US
> counties (N=3101) and the variables are measured every month for 2008-
> 2012 (T=53).
> 
> The specification is -ivreg2 S12.(lny L1.x) dcid*, cluster(state
dateym)-. The
> intercept in this model gives me a national trend and the coefficients
on the
> dcid dummies estimate the county trends.
> 
> I would like to cluster at the state level (S=48) and for time, and I
was hoping
> to use the user-written ivreg2. This has been running more than ten
times
> longer than it takes to cluster on state or time alone, so I am not
sure why it's
> taking so long. My understanding is that Stata actually calculates the
variance
> covariance matrix as
> Cov(cluster(state)) + Cov(cluster(time)-Cov(cluster(state*time))), so
there
> are 3 separate regressions that are estimated, but this seems fairly
doable.
> Toy models seem to work very well. Any advice about how I can figure
out
> where the bottleneck is?
> 
> I have not tried cluster2 (from
> http://www.kellogg.northwestern.edu/faculty/petersen/htm/papers/se/se
> _programming.htm)
> yet, since it does not have as rich a set of diagnostics.
> 
> DVM
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