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st: RE: RE: Autocorrelation test for pooled cross section data


From   "Elizabeth Dhuey" <elizabeth.dhuey@utoronto.ca>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: RE: Autocorrelation test for pooled cross section data
Date   Tue, 28 Sep 2010 17:19:19 -0400

I apologize if I don't understand your questions but here is my best shot at
answering them. 

I'm trying to test whether my errors are correlated across time (i.e. across
cohorts). I have a problem because I have 50 different states so I can't use
a simple Durbin-Watson statistic because I could only use that if I had only
one state. 

I only include dummy variables for the states and do not take into account
the location or any spatial data regarding the states. I only allow for an
intercept change for each state. 

Regards, Elizabeth


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nick Cox
Sent: September-28-10 5:08 PM
To: 'statalist@hsphsun2.harvard.edu'
Subject: st: RE: Autocorrelation test for pooled cross section data

I am unclear on what you want, but as I understand it Durbin-Watson tests
apply only to time series. 

If you have data on 50 U.S. states and are treating them as spatial series,
which of your variables encode information of the location, contiguity,
whatever, of those states? If it is -birthstate- as a categorical variable,
how is that spatial? 

Nick 
n.j.cox@durham.ac.uk 

Elizabeth Dhuey

I'm trying to figure out what is the most appropriate test to use is when
working with pooled cross sectional data. In particular, I have aggregated
individual level measures to state level averages for different cohorts from
the U.S. Census. 

I can't use estat dwatson because I have multiple panels and I don't believe
that I can use xtserial because I don't have a true panel.  

I am running the following regression:

xi: reg Y X i.birthstate i.cohort [pw=wgt], robust cluster(birthstate)


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