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Re: st: mlogit coefs


From   David Hoaglin <dchoaglin@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: mlogit coefs
Date   Tue, 17 Apr 2012 11:36:14 -0400

Dear Chiara,

I have a comment, much more minor than Maarten's, but still useful.

If the contribution of age is nonlinear, it may not be satisfactory to
assume that the nonlinearity is quadratic (in practice it often is
not).  You did not mention the number of observations; but since you
have the entire labor force, you may have enough data to approach the
functional form of age empirically.  One strategy would separate the
values of age into disjoint intervals (as narrow as the data will
support), include in the model a dummy variable for each interval
except one, and plot the fitted coefficients of those dummy variables
against the midpoints of the intervals.  If that plot looks quadratic,
fine.  But it may suggest that a linear spline would be a better
summary of the contribution of age (taking into account the other
variables in the model).

David Hoaglin

On Tue, Apr 17, 2012 at 10:00 AM, Chiara Mussida <cmussida@gmail.com> wrote:
> Dear All,
> I run a mlogit model for 9 labour market outcomes (transitions between
> the three states of employment unemployment and inactivity, therefore
> 6 transitions and 3 permanences), like:
>
> mlogit transition male_unmarried female_married female_unmarried age
> agesq ncomp child northw northe centre Ubenef edu1 edu2 health
> qu1nolav qu3nolav qu2nolav nopersincnolav noothersineq qu1ot qu2ot
> qu3ot if age>=15 & age<=64, b(3)
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