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Re: st: xtreg fe - skewness and kurtosis in independent variables


From   L_4_U@gmx.de
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: xtreg fe - skewness and kurtosis in independent variables
Date   Sun, 10 Mar 2013 14:41:42 +0100

Dear David,

thank you very much for your fast and extensive answer!

Kind regards


Lothar

-------- Original-Nachricht --------
> Datum: Sun, 10 Mar 2013 08:35:11 -0400
> Von: David Hoaglin <dchoaglin@gmail.com>
> An: statalist@hsphsun2.harvard.edu
> Betreff: Re: st: xtreg fe - skewness and kurtosis in independent variables

> Dear Lothar,
> 
> In a regression model, the predictor variables (a better choice of
> words than "independent variables," because they are seldom
> "independent") are not required to follow a normal distribution, or to
> follow any distribution at all.  Many models involve dichotomous
> predictors ("dummy variables," preferably "indicator variables"),
> which take only 0 and 1 as their values.
> 
> You should, however, check whether the relation between the dependent
> variable and each of the predictor variables is reasonably close to
> linear.  As a start, you can look at the corresponding scatterplots,
> but the choice should ultimately be made in the context of the full
> model.  If those relations are curved, you may be able to straighten
> them by transforming the dependent variable or the predictor variables
> or both.
> 
> David Hoaglin
> 
> On Sun, Mar 10, 2013 at 8:02 AM,  <L_4_U@gmx.de> wrote:
> > Dear statalist,
> >
> > I'm using an unbalanced datapanel (financial data) with 576 observations
> to estimate a fixed effects model with Stata 12.0. Tests indicate first
> order autocorrelation and heteroscedasticity of the error term, therefore I
> use robust standard errors. The command
> >
> > xtreg depv indv1 indv2 indv3 indv4 indv5 indv6 indv7 indv8 indv9 indv10,
> fe vce (ro)
> >
> > can be run without problems and delivers satisfactory results without
> any obvious irregularities.
> >
> > However, the descriptive statistics show above normal skewness and
> kurtosis of the independent variables. I. e. the independent variables INDV1 to
> INDV10 used to estimate the FE model are non-normally distributed:
> >
> > var     obs     mean    std.-   min     max     skewn.  kurtosis
> >                         dev.
> > ----------------------------------------------------------------
> > depv    576     -0.123  0.279   -0.805  0.815   0.322   3.187
> > indv1   576     0.820   0.260   0.171   1.001   -1.261  3.228
> > indv2   576     -0.007  0.757   -14.255 5.389   -11.511 229.900
> > indv3   576     0.000   0.091   -0.310  0.581   0.790   7.727
> > indv4   576     0.669   0.234   0.231   1.100   0.082   1.612
> > indv5   576     0.486   0.236   0.000   3.030   2.301   28.001
> > indv6   576     0.050   0.989   -2.549  1.492   -0.74   2.671
> > indv7   576     0.378   0.621   0.014   7.721   8.651   86.881
> > indv8   576     0.024   0.037   0.002   0.250   3.501   16.339
> > indv9   576     0.041   0.117   0.001   0.570   3.410   13.440
> > indv10  576     2.073   6.638   0.002   63.120  5.555   37.301
> >
> > Questions:
> >
> > - Does xtreg estimate the FE-model correctly, despite non-normality of
> the independent variables?
> >
> > - If not, will I have to normalize the independent variables before
> using xtreg?
> >
> > Any comments are welcome!
> >
> > Thanks,
> > Lothar
> 
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