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Partial effects in probit and logit models with a triple dummy-variable interaction term

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  • Thomas Cornelissen

    (University College London)

  • Katja Sonderhof

    (Institute of Labour Economics, Leibniz Universität Hannover)

Abstract

In nonlinear regression models, such as probit or logit models, coefficients cannot be interpreted as partial effects. The partial effects are usually nonlinear combinations of all regressors and regression coefficients of the model. We derive the partial effects in such models with a triple dummy-variable interaction term. The formulas derived here are implemented in the Stata inteff3 command. The command also applies the delta method to compute the standard errors of the partial effects. We illustrate the use of the command with an em- pirical application, analyzing how the gender gap in labor-market participation is affected by the presence of children and a university degree. We find that the presence of children increases the gender gap in labor-market participation but that this increase is smaller for more highly educated individuals. Copyright 2009 by StataCorp LP.

Suggested Citation

  • Thomas Cornelissen & Katja Sonderhof, 2009. "Partial effects in probit and logit models with a triple dummy-variable interaction term," Stata Journal, StataCorp LP, vol. 9(4), pages 571-583, December.
    • Handle: RePEc:tsj:stataj:v:9:y:2009:i:4:p:571-583
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    References listed on IDEAS

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    2. Jonathan Gruber & James M. Poterba, 1993. "Tax Incentives and the Decision to Purchase Health Insurance: Evidence from the Self-Employed," NBER Working Papers 4435, National Bureau of Economic Research, Inc.
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    4. Jonathan Gruber & James Poterba, 1994. "Tax Incentives and the Decision to Purchase Health Insurance: Evidence from the Self-Employed," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 109(3), pages 701-733.
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