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  • Ordered probit / multinomial probit models, marginal effects difference

    Hello everyone,

    I'm working with National Longitudinal Survey of Youth (NLSY79 and NLSY97), which include two datasets, with the same variables, about students surveyed in 1979 and 1997.

    I created as output a categorical variable, schooling_status, which assumes values:
    - 1 corresponding to "college participants"
    - 2 corresponding to "high school drop-outs"
    - 3 corresponding to "high school graduates"
    - 4 corresponding to "year college graduates".

    I've run on both datasest firstly a multinomial probit and, secondly, an ordered probit including a set of regressors as controls and one variable indicating the family income. Consequently, to interpret the effect of income on the 4th outcome (year college graduates) I computed the marginal effects.

    For the multinomial probit I had: NSLY79 --> ME_income = .0004999; NLSY97 --> ME_income = 0.0005007.
    For the ordered probit I had: NSLY79 --> ME_income = 0.0000599; NLSY97 --> ME_income = 0.0001765.

    As you may notice, while for the multinomial logit the marginal impact of the var income does not vary throughout times (only a 0.16% variation), with the oredered probit I have a huge variation in the marginal effect of income between 1979 and 1997... In the 2nd period te impact is 195% higher!

    Can someone kindly explain me the reason of this big difference between the two models?

    Thanks a lot!


  • #2
    There is a nice paper by Crawford, Pollak and Vella on this topic, albeit their focus is on -mlogit- vs -ologit:

    David L. Crawford, Robert A. Pollak & Francis Vella (1998) Simple inference in multinomial and ordered logit, Econometric Reviews, 17:3, 289-299, DOI: 10.1080/07474939808800417

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