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

From |
bumbuminc <bumbuminc@googlemail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: Mincer wage function as a log function - how can stata calculate the percent values |

Date |
Wed, 29 Oct 2008 19:32:08 +0100 |

Thanks you very much for your help. And yes you are right, i'm only used to -regress- in this context. I will try to get more about the glm command. Boris 2008/10/29, Maarten buis <maartenbuis@yahoo.co.uk>: > --- Maarten buis <maartenbuis@yahoo.co.uk> wrote: >> Another way of thinking about the difference between these two models >> is that you are modeling the geometric mean of wage, while I am >> modelling the arithmatic mean of wage. > > Below you can see that the two models give largely similar results. So, > which one should you choose? There is a trade-off here: > > On the one hand people in your discipline are apperently used to > -regress- in this context, but it is a pain to explain that the > coefficients you report are ratios of geometric means rather than > ratios of means. There is nothing wrong with geometric means and their > ratios other than that a lot of people aren't used to them, and start > getting worried about your analysis when there is no need to be > worried. > > On the other hand, using -glm- will allow you to present your results > in terms of ratios of means, but apperently people in your discipline > aren't used to using -glm- in this contex. There is nothing wrong with > using -glm- in this context other than that a lot of people aren't used > to it, and start getting worried about your analysis when there is no > need to be worried. > > Maybe the easiest way out is to add a paragraph to your methods section > where you discuss the difference between the two models. Say that you > choose one of these and say that you have also used the other model but > that the results where very similar. > > *------------------------- begin example -------------------- > sysuse nlsw88, clear > gen ttl_exp2 = ttl_exp^2 > gen wage_log = ln(wage) > gen cons = 1 > reg wage_log ttl_exp ttl_exp2 grade cons, eform("exp(b)") nocons > glm wage ttl_exp ttl_exp2 grade cons, eform link(log) nocons > *-------------------------- end example ---------------------- > > -- Maarten > > ----------------------------------------- > Maarten L. Buis > Department of Social Research Methodology > Vrije Universiteit Amsterdam > Boelelaan 1081 > 1081 HV Amsterdam > The Netherlands > > visiting address: > Buitenveldertselaan 3 (Metropolitan), room N515 > > +31 20 5986715 > > http://home.fsw.vu.nl/m.buis/ > ----------------------------------------- > > > > * > * 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/ > * * 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**:**Re: st: RE: Mincer wage function as a log function - how can stata calculate the percent values***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**Re: st: RE: Mincer wage function as a log function - how can stata calculate the percent values***From:*Maarten buis <maartenbuis@yahoo.co.uk>

- Prev by Date:
**st: minor bug in -describe-?** - Next by Date:
**Re: st: RE: Syntax problems with maximum likelihood (method lf)** - Previous by thread:
**Re: st: RE: Mincer wage function as a log function - how can stata calculate the percent values** - Next by thread:
**Re: st: Mincer wage function as a log function - how can stata calculate the percent values** - Index(es):

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