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Simplified Marginal Effects in Discrete Choice Models

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  • Newell, Richard

    (Resources for the Future)

  • Anderson, Soren

Abstract

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

  • Newell, Richard & Anderson, Soren, 2003. "Simplified Marginal Effects in Discrete Choice Models," RFF Working Paper Series dp-03-38, Resources for the Future.
    • Handle: RePEc:rff:dpaper:dp-03-38
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    File URL: http://www.rff.org/RFF/documents/RFF-DP-03-38.pdf
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    10. Elias Katsikas & Theologos Dergiades, 2012. "Revising higher education policy in Greece: filling the Danaids’ Jar," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 39(3), pages 279-292, August.
    11. Pambo, Kennedy Otieno & Otieno, David Jakinda & Okello, Julius Juma, 2014. "Prospects for Biofortification Reducing Micronutrient Deficiency in Kenya: Lessons from Sugar Fortification Programmes," 18th ICABR Conference, June 17-20, 2014, Nairobi, Kenya 174531, International Consortium on Applied Bioeconomy Research (ICABR).
    12. Carlevaro, Fabrizio & Senegas, Marc-Alexandre, 2006. "Simplified marginal effects in discrete choice models: A correction," Economics Letters, Elsevier, vol. 92(1), pages 44-46, July.
    13. Lijia Wang & Jianhua Wang & Xuexi Huo, 2019. "Consumer’s Willingness to Pay a Premium for Organic Fruits in China: A Double-Hurdle Analysis," IJERPH, MDPI, vol. 16(1), pages 1-14, January.
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    18. Minghui Yin & Balekouzou Augustin & Chang Shu & Tingting Qin & Ping Yin, 2016. "Probit Models to Investigate Prevalence of Total Diagnosed and Undiagnosed Diabetes among Aged 45 Years or Older Adults in China," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-13, October.
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    21. 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.
    22. Joonmo Cho & Jaeseong Lee & Taehee Kwon, 2013. "Gender exclusion in social security protection: evidence from Korea," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 27(1), pages 62-78, May.
    23. Elias Katsikas & Theologos Dergiades, 2009. "Higher Education Policy in Greece: Filling the Danaids' Jar," Discussion Paper Series 2009_16, Department of Economics, University of Macedonia, revised Nov 2009.
    24. 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

    Keywords

    logit; probit; discrete choice; binary choice; marginal effect; data normalization;
    All these keywords.

    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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