Re: Wage regression - use sample weights?

On Tue, 1 Apr 2008 14:39:32 -0700 (PDT), Bob <frotty22@xxxxxxxxx>
wrote:

On Mar 27, 11:18 am, Bob <frott...@xxxxxxxxx> wrote:
Hi,

I am trying to do a wage regression (ln(wage) dependent on several
individual characteristics like age, education, region, etc.) based on
household survey data and now I don't know if and why sample weights
(here: sample inflation factors, multipliers to inflate the sample to
the total population) should be used in the regression and if so, how
this is done.

SPSS, for instance, allows you to specify case-weights
in general, which are then used for (almost) every procedure.

Computer programs for surveys, I think, allow weighting
within the regression program. I don't remember if SPSS
does.

If you want the tests to be useful, at all, then the total
N after weighting is about the same as the total N
before weighting. If the weighting does very much to
distort the actual cell sizes, then the tests will be
screwed up to a corresponding degree.



I saw some references where they discussed the issue but I didn't
really understand why the one way or the other is preferred.

Theoretically, I think one could clone the individual observations
(single household) to equal the respective sample inflation factor and
adding an error term from the distribution of the subgroup sample to
each clone. But practically, the size of the data would not be
manageable.

Can anyone point me to a gentle introduction reference regarding this
issues or give me some clues?

Many thanks,
Bob

No one doing regression analysis on household survey data and knowing
about the sample weight issue?!

--
Rich Ulrich

http://www.pitt.edu/~wpilib/index.html
.

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