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Re: st: cross-sectional time series data


From   David Greenberg <dg4@nyu.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: cross-sectional time series data
Date   Sat, 06 Sep 2003 19:17:12 -0400

Some of the methods Bob Yaffee is discussing are only valid asymptotically, as the number of objects in the data set becomes large. Nathaniel Beck has shown that these methods can produce extremely misleading results when applied to panel data with a small number of objects. He has shown that OLS estimation, with panel-corrected standard errors, performs much better in such circumstances. This can be done in Stata with xtpcse. David Greenberg, Sociology Department, New York University

----- Original Message -----
From: Robert A Yaffee <bob.yaffee@nyu.edu>
Date: Saturday, September 6, 2003 5:36 pm
Subject: Re: st: cross-sectional time series data

> Kimberly,
>  Panel data analysis and cross-sectional time series are 
> essentially the same. You will need to run a Hausman test to 
> ascertain whether your random error is correlated with the 
> individual effects. If they are, you will have to use the fixed 
> effects model. In that event, you need to be concerned that you 
> don't have too many cross-sections and dummy variables to test 
> your effects.  You want to run your LSDV model against the pooled 
> regression to determine whether there is a significant improvement 
> in the rsquare.  In this way you can test your group or cross-
> sectional effects.  You will need to also determine whether there 
> is autocorrelation in the model as well. 
>  As for the estimation procedure,  xtgls allows for correlation 
> across the cross-sections, ar(1) within the panels, and 
> heteroskedasticity and no cross-panel correlation.  Xtgee allows 
> for a richer designation of within panel correlation as long as 
> that correlation applies to all panels.
>  See Stata Press, "Cross Sectional Time Series, p. 86" for this 
> reference.  - Bob Yaffee
> 
> 
> Robert A. Yaffee, Ph.D.
> Senior Research/Statistical Consultant
> Statistics and Social Science Group
> Information Technology Services
> Academic Computing Services
> New York University
> 251 Mercer Street
> New York, New York, 10012
> phone: (1)212-998-3402
> fax: (1)212-995-4120
> e-mail: yaffee@nyu.edu
>        ray1@nyu.edu 
> Office location: 75 Third Avenue
>                           Level C-3
>                           New York, NY 10003
> 
> ----- Original Message -----
> From: Kimberley Tran <ktran2@dal.ca>
> Date: Saturday, September 6, 2003 11:14 am
> Subject: st: cross-sectional time series data
> 
> > Greetings all,
> > 
> > I would like to get suggestions concerning cross-sectional time 
> > series data.
> > My estimation model consists of 10 individual units, each 
> sharing 
> > the same 
> > variables and for the same 19-year time period. Where I am 
> > confused is whether 
> > to consider this as Panel data or cross-sectional time series 
> > data. Certain 
> > literature treats Panel and cross-sectional time series as one 
> in 
> > the same, 
> > while others indicate that they are not.
> > Further complication is knowing which Stata commands to use.
> > Initially I ran this command 
> > . xtreg y x1 x2 x3 x4 x5 x6 x7, re
> > to test to see whether GLS is necessary or simple OLS will do 
> for 
> > the 
> > estimation.
> > 
> > Secondly I ran 
> > . xttest0  
> > to discriminate against eitehr the Pool Model and the Random 
> > Effects Model and 
> > the results indicated pooled model was not appropriate.
> > 
> > I then ran the Hausman test in order to determine betweem the 
> > Random Effect 
> > Model or Fixed effects model:
> > . xthaus
> > 
> > The results indicated that the Fixed effects is appropriate.
> > 
> > Are these the right steps and commands to apply to cross-
> sectional 
> > time series 
> > data? Or should I use the xtgls or the xtgee commands?
> > 
> > I would greatly appreciate your suggestions in clarifying this 
> > confusion.
> > Thank you,
> > Kimberley
> > 
> > *
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> > *   http://www.stata.com/support/statalist/faq
> > *   http://www.ats.ucla.edu/stat/stata/
> > 
> 
> *
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> 

*
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