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From |
"Elizabeth Dhuey" <elizabeth.dhuey@utoronto.ca> |

To |
<statalist@hsphsun2.harvard.edu> |

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

Date |
Wed, 29 Sep 2010 11:37:54 -0400 |

Due to the length of my time period, I have some concern regarding correlated errors over time. I have plotted the residuals and see some evidence of correlation over time. However, my attempt to find a formal test that produces a p-value is based on a request from a journal referee. My main issue is that I can't seem to find any formal test that is appropriate for pooled cross sectional data. My current thought is to calculate a durbin-watson statistic for each state and report the distribution of the statistic. However, I suspect that someone has already formalized a produce for this kind of data structure. Elizabeth -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nick Cox Sent: September-29-10 6:09 AM To: 'statalist@hsphsun2.harvard.edu' Subject: st: RE: RE: RE: Autocorrelation test for pooled cross section data A minimal but presumably useful check is to calculate some flavour of residuals and plot them against cohort identifier and also space. As a non-economist -- and in one very strained sense an ex-economist -- I don't have to sign up to the notion that every check should be matched by a formal test producing a P-value. I don't know off-hand how worried you should be relatively about correlation in time and in space for your kind of data, but in principle both could be a concern. Nick n.j.cox@durham.ac.uk Elizabeth Dhuey 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. Nick Cox 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? 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) * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Autocorrelation test for pooled cross section data***From:*"Elizabeth Dhuey" <elizabeth.dhuey@utoronto.ca>

**st: RE: Autocorrelation test for pooled cross section data***From:*Nick Cox <n.j.cox@durham.ac.uk>

**st: RE: RE: Autocorrelation test for pooled cross section data***From:*"Elizabeth Dhuey" <elizabeth.dhuey@utoronto.ca>

**st: RE: RE: RE: Autocorrelation test for pooled cross section data***From:*Nick Cox <n.j.cox@durham.ac.uk>

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