[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
"Nick Cox" <n.j.cox@durham.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: RE: Goodness of fit measure akin to R-squared for 0-constant or noconstant |

Date |
Fri, 24 Apr 2009 15:23:29 +0100 |

If I were your boss, I would be alarmed about removal of outliers on what appear to be ad hoc grounds. Even in your context, it is not clear that ignoring awkward facets of your data will necessarily lead to better predictions. Nick n.j.cox@durham.ac.uk Bas de Goei Ow, I understand both points made, and I agree that a country could perfectly have demand with a still standing standing economy. The economic ground is that jewellery is supposedly a luxury good, making people spend as much on it as they are able given other constraints, i.e. food etc. If you have less GDP growth, you should therefore also have less jewellery demand growth. Well, the point you made Martin, shows a very interesting aspect of India, which is its incredibly strong class society. The top class, which apparently makes up almost all jewellery demand appears unaffected by the state of the economy. Not in any other analysed country was this the case. Because of simplification, and simply because my boss would not understand / want this sophistication (also because of time constraints), I decided that having a 0 intercept would be better justifiable and this was backed up by the fact that the intercept had become insignificant after removing some outliers. Also the resulting forecast fitted better with my boss' expectations - as you might have guessed I am not exactly in an academic environment at the moment. So I'm sorry if some things appear illogical, but I have to work under some constraints. Well, the only thing I'd really wanted was to calculate an R-squared for this thing, so I'd be done with it. I think I have found my solution in Kvalseths method, and I made it work (as far as I understand) with a GLS regression as well by adjusting the OLS regression with the rho from the stata output (though I had to calculate it manually in excel). * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Goodness of fit measure akin to R-squared for 0-constant or noconstant***From:*Bas de Goei <bas.degoei@gmail.com>

**st: RE: Goodness of fit measure akin to R-squared for 0-constant or noconstant***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**Re: st: RE: Goodness of fit measure akin to R-squared for 0-constant or noconstant***From:*Bas de Goei <bas.degoei@gmail.com>

**Re: st: RE: Goodness of fit measure akin to R-squared for 0-constant or noconstant***From:*Bas de Goei <bas.degoei@gmail.com>

- Prev by Date:
**Re: st: RE: Goodness of fit measure akin to R-squared for 0-constant or noconstant** - Next by Date:
**st: First difference in multidimensional panel** - Previous by thread:
**Re: st: RE: Goodness of fit measure akin to R-squared for 0-constant or noconstant** - Next by thread:
**st: Kvalseth R-squared for 0-constant or noconstant** - Index(es):

© Copyright 1996–2016 StataCorp LP | Terms of use | Privacy | Contact us | What's new | Site index |