[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

From |
Stas Kolenikov <skolenik@email.unc.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Re: log of variables in xtreg |

Date |
Tue, 22 Oct 2002 10:09:56 -0400 (EDT) |

The "significance" of the coefficient can only tell you something when the model is correctly specified. If you have a nonlinear effect not captured by your regresssors and / or transformation of your variables, then your model simply fails to capture the way the data behaves. Here's an example (quick and dirty, so it might not be as convincing as it should :) ): ==== clear set obs 100 set seed 99999 g lx = uniform() g ly = -.3*lx + invnorm(uniform()) g y = exp(ly) g x = exp(lx) gr y x reg y x exit ==== The regression gives a positive and insignificant coefficient of x, although from the way the data were generated, the logged variables have a reasonably strong negative dependence. The idea is that without logs, the model is not very well specified. The error distribution would be heavily skewed, and I am not sure you would get very impressive results with this distribution. The mean structure is also likely to be nonlinear, so the errors would also have conditional bias. A pretty good way to get rid of at least some problems with skewness and nonlinearity would be to try Box-Cox transformations, see -help boxcox-. In my example, boxcox y x , model(lambda) restores the original lx and ly variables by saying that the preferred transformation parameter is 0. I was not quite sure though what is the regression related to the transformed model based on the output of -boxcox-. --- Stas Kolenikov -- Ph.D. student in Statistics at UNC-Chapel Hill - http://www.komkon.org/~tacik/ -- Stas.Kolenikov@unc.edu * This e-mail and all attachments to it are not intended to provide any * reasonable point of view and was transmitted to you in error. It * should be immediately deleted by all recepients unless they really * enjoy communicating with the author :). Other restrictions apply. * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

- Prev by Date:
**st: RE: RE: multiple response question (correction)** - Next by Date:
**st: RE: multiple response question** - Previous by thread:
**st: Re: robust st. errors and fixed effects** - Next by thread:
**st: RE: multiple response question** - Index(es):

© Copyright 1996–2014 StataCorp LP | Terms of use | Privacy | Contact us | What's new | Site index |