st: comparing logit (& mlogit?) coefficients with different dependent variables

[M Hollis <m73hollis_stata@yahoo.com>]

I've been looking at various sources including the Statalist archive and I've found a number of discussions of the challenges of comparing logit coefficients across different groups. I'm wondering, through, about the feasibility of comparing coefficients between models with the same samples and the same independent variables but different dependent variables. I can't find much on this question so any advice would be appreciated.

Taking it a step further, could one compare coefficients across different multinomial logit models, again with the same sample and same independent variables. The dependent variables in this case would also have the same structure (same number and types of possible outcomes). 

To be more concrete, I'm looking at predictors of whether an individual saw a change in occupational characteristics using three different measures of characteristics (cognitive skill, physical demands, social skill). In the logit case I would just be marking whether the person moved to a different skill level (dependent variable 1), moved to a job with a different physical demand level (dependent 2), or social skill level (dependent 3). I'd want to compare the coefficients of the independent variables in each of these three models.

In the multinomial logit case, for each of the three types of characteristics I would look at three outcomes: an decline in the measure (e.g. cognitive skill requirements), no change (baseline group), or an increase. I realize these three outcomes could be considered ordinal, but I believe that the factors predicting each of the outcomes will be different and therefore the outcomes should have separate sets coefficients. I would, though, like to be able to compare the coefficients in these models across the three different mlogit estimates. Is this a bad idea?

Thank you for your help,

Matissa Hollister

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