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  • Endogenous Explanatory Variable in a Multinomial Logit Estimation

    Hi Statalist

    I am wondering what are the possible options for modelling endogeneity in a multinomial logit model?

    My mode is described below:

    y1=a+by2+cX

    where y1 is a categorical variable with 3 categories (1,2 and 3)

    y2 is the endogenous explanatory variable which can take values 0 or 1

    and X is the list of exogenous explanatory variables

    As a first step, i have used Multinomial Logit and reported results as Average Marginal Effects.

    Given that y2 is endogenous I have identified an IV z1 (also a binary vairable which takes values 0 or 1) which can be used in its place (The endogeneity may result from y1 and y2 being determined simultaneously and self selection)

    One possible model I have identified is
    Control Functions Methods (Jeffrey M. Wooldridge Journal of Human Resources, Volume 50, Number 2, Spring 2015, pp. 420-445)

    My questions are:
    1. Can i use Control Function Methods to model this, I am a bit unsure about this as both the IV and EEV are binary variables but the dependent variable is a choice variable?

    I have used the following code:

    reg y2 z1 X
    predict y2_res, residuals
    mlogit y1 y2 z1 X, base (2)

    2. Will the margins calculated after the above code be interpreted in the same way as from a usual mlogit estimation?
    margins, dydx(*) predict(outcome(1))
    margins, dydx(*) predict(outcome(2))
    margins, dydx(*) predict(outcome(3))

    3. What possible alternate models could i use?

    Thanks
    Utterly confused and then a bit more
    Mehwish



  • #2
    Hi Statalist

    Jusst rephrasing my original question incase it is too large, can I use control function method (Woolridhe 2014) in a multinomial setting when I have a binary EEV and binary IV?
    My code is
    reg y2 z1 X
    predict y2_res, residuals
    mlogit y1 y2 y2_res X, base (2)

    Many thanks
    Mehwish
    Last edited by Mehwish Ali; 16 Nov 2020, 20:24.

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    • #3
      gsem allows multiple equations, endogenity, multinomial estimation all together. That sounds like what you are looking for, That would be my best guess....

      Comment


      • #4
        Thanks Oscar

        I had a look at GSEM, but havent seen anyone apply them in the litreture relevant to my thesis. But I will have a closer look at them with a fresh mind

        Mehwish

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        • #5
          Hi@Mehwish,
          Please how did you go about this problem eventually...can you share?

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