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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 > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/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/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**st: xtreg fe - skewness and kurtosis in independent variables***From:*L_4_U@gmx.de

**Re: st: xtreg fe - skewness and kurtosis in independent variables***From:*David Hoaglin <dchoaglin@gmail.com>

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