Stata The Stata listserver
[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

Re: st: RE: Quadratic term validity


From   Rozilee Asid <rozilee@streamyx.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: Quadratic term validity
Date   Thu, 11 Nov 2004 06:06:47 +0800

Thanks Nick and SamL.

At first, I've tried not to include the Ln term and found that the model
suffer with the misspecification problem when I invoke linktest and ovtest
command and the single and quadratic term of age shows the same sign as
model 2 just now.

That come my idea to modified the variable into ln form. Off course my model
more likely to test the human capital theory from the perspectives of
non-technical workers in the industrial sectors.

Anyway thank for your comment and advice. I'll take it seriously.

Thanks guys


Rozilee


On 11/11/04 5:37 AM, "SamL" <saml@demog.berkeley.edu> wrote:

> Well, um, actually, there is an economic theoretic reason for the
> quadratic term in age, drawn from (among other sources) human capital
> theory--declining returns to _________________ (experience, prior
> training, fill in the blank with what you mean age to signify).  So, I'm
> not sure I'd drop the linear term, as the theory does not imply only
> curving returns.
> 
> There may be other economic theories that justify the quadratic and the
> linear term.
> 
> Finally, statistically, removng the linear term implies no main effect.
> Does that make sense?  It might help to graph the results.  I think no
> linear term would be a major problem, but maybe not.
> 
> HTH.
> Sam
> 
> On Wed, 10 Nov 2004, Nick Cox wrote:
> 
>> Are you really dealing with age or ln age?
>> 
>> "Valid" or not depends on your criteria of
>> validity, which are not explicit. From what
>> I gather people like using quadratics in income
>> versus age because they often fit fairly well,
>> and there isn't a economic theory reason
>> for the functional form. So you could make
>> a case for dropping the linear term
>> if it doesn't to seem to help with the fit.
>> 
>> On the other hand, there are several grounds
>> for being more circumspect:
>> 
>> 1. Just because the linear term looks
>> insignificant does not mean that the
>> model with quadratic term alone is necessarly
>> better, all things considered.
>> 
>> 2. The P-value is just one indicator. You
>> don't say anything about the change in R^2
>> or RMS error or (probably most important of
>> all) where there is clear structure
>> if you plot
>> 
>> residuals from model with quadratic
>> term alone
>> 
>> versus
>> 
>> age.
>> 
>> 3. Inferences are surely complicated by
>> the correlation between age and age^2.
>> 
>> 4. There are good discussions of related
>> issues in McCullagh and Nelder's book
>> on generalised linear models and in
>> Nelder's paper in American Statistician
>> November 1998. Loosely, there are
>> grounds for treating polynomial terms
>> as yoked together like a team, although Nelder
>> puts it better than that.
>> 
>> Nick
>> n.j.cox@durham.ac.uk
>> 
>> Rozilee Asid
>> 
>>> My wage model consists of several variables and model. One of my model
>>> consists of quadratic term of age, example
>>> Ln-wage = alpha0 + alpha1.ln_age + alpha2.ln_exp (model 1)
>>> Ln_wage = alpha0 + alpha1.ln_age + alpha2.ln_exp +
>>> alpha3.ln_age^2 (model 2)
>>> 
>>> My main attention is to identified whether age play its
>>> significant role in
>>> the model. When I regress the model I found that alpha1 coefficient is
>>> negative and insignificant and alpha3 is positive and significant. My
>>> question is before I include the quadratic term of age
>>> variable (model 1),
>>> the alpha1 coefficient is positive and significant.
>>> 
>>> Is it valid for me to report the finding from model 2
>>> equations, especially
>>> when alpha1 is negative in the model.
>> 
>> *
>> *   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/
>> 
> *
> *   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/


*
*   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/



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