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From |
David Hoaglin <dchoaglin@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Sun, 10 Mar 2013 08:35:11 -0400 |

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/

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

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

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