Partial effects in probit and logit models with a triple dummy-variable interaction term
Thomas Cornelißen
University College London
Centre for Research and Analysis of
Migration
Department of Economics
t.cornelissen@ucl.ac.uk
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Katja Sonderhof
Leibniz Universität
Hannover
Institute of Labour Economics
sonderhof@aoek.uni-hannover.de
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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 empirical
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.
View all articles by these authors:
Thomas Cornelißen, Katja Sonderhof
View all articles with these keywords:
inteff3, probit model, dummy variables, interaction terms, partial effects, Stata, labor-market participation
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