Philip and Nick--
What Nick says is quite (American sense) true, but see -ssc install
spautoc- (by Nick Cox) or -findit spatcorr- (by Pisati) and page 20 of
http://csiss.ncgia.ucsb.edu/learning_resources/content/papers/baltchap.pdf
which notes of Moran's I :
The statistic shows a striking similarity
to the familiar Durbin-Watson test.
(and refers to "an extensive discussion" in Anselin, L. and A. Bera
(1998). Spatial dependence in linear regression models with an
introduction to spatial econometrics. In: A. Ullah and D. E. A. Giles,
Eds., Handbook of Applied Economic Statistics, pp. 237–289).
But you may be interested in the cluster option for various regression
commands, which estimates SEs robust to arbitrary intra-cluster
correlations, assuming you have enough clusters (say 50 or more), e.g.
51 states (improperly counting the disenfranchised DC) as clusters in
an analysis of US data.
--Austin
On 11/16/06, Nick Cox <n.j.cox@durham.ac.uk> wrote:
Durbin-Watson tests are for serial autocorrelation.
Serial autocorrelation is defined only for
a time series, or at the broadest for a one-dimensional
spatial series in which influences are propagated in one
direction only (even for rivers or streams this is
difficult to believe). If your data are spatial you need
something else. If you want something else completely,
please tell us what you have in mind.
Nick
n.j.cox@durham.ac.uk
Ruter Philip E Maj AFIT/ENV
> I can find several places in Stata to calculate a Durbin-Watson
> statistic for time series and panel models. Is it possible
> to calculate
> a D-W statistic for cross-sectional data without a time-series
> component? Any Help would be greatly appreciated.
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