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Simplified Marginal Effects in Discrete Choice Models


  • Anderson, Soren T.
  • Newell, Richard G.


We show that after a simple normalization of explanatory variables so that they equal zero at some desired reference point, marginal effects for continuous variables in probit and logit models simplify dramatically, becoming a function of only the estimated constant term. We present similar simplifications for computation of the asymptotic variance of marginal effects, as well as for the effects of dummy variables on predicted probabilities. We provide a simple table, which in combination with raw probit or logit estimates, is all one needs to compute the desired effects.

Suggested Citation

  • Anderson, Soren T. & Newell, Richard G., 2003. "Simplified Marginal Effects in Discrete Choice Models," Discussion Papers 10631, Resources for the Future.
  • Handle: RePEc:ags:rffdps:10631
    DOI: 10.22004/ag.econ.10631

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    19. Wang, L., 2018. "Willingness to Pay for Certified Fresh Fruits in China: A Double-Hurdle Approach," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277413, International Association of Agricultural Economists.
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    23. Eberechukwu Onukwugha & Jason Bergtold & Rahul Jain, 2015. "A Primer on Marginal Effects—Part I: Theory and Formulae," PharmacoEconomics, Springer, vol. 33(1), pages 25-30, January.

    More about this item


    Research Methods/ Statistical Methods;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access


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