Marginal effects in the probit model with a triple dummy variable interaction term
In non-linear regression models, such as the probit model, coefficients cannot be interpreted as marginal effects. The marginal effects are usually non-linear combinations of all regressors and regression coefficients of the model. This paper derives the marginal effects in a probit model with a triple dummy variable interaction term. A frequent application of this model is the regression-based difference-in-difference-in-differences estimator with a binary outcome variable. The formulae derived here are implemented in a Stata program called inteff3 which applies the delta method in order to compute also the standard errors of the marginal effects.
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- Edward C. Norton & Hua Wang & Chunrong Ai, 2004. "Computing interaction effects and standard errors in logit and probit models," Stata Journal, StataCorp LP, vol. 4(2), pages 154-167, June.
- Jonathan Gruber & James M. Poterba, 1993.
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- Gruber, Jonathan, 1994. "The Incidence of Mandated Maternity Benefits," American Economic Review, American Economic Association, vol. 84(3), pages 622-641, June.
- Ai, Chunrong & Norton, Edward C., 2003. "Interaction terms in logit and probit models," Economics Letters, Elsevier, vol. 80(1), pages 123-129, July.
- Thomas Cornelissen & Katja Sonderhof, 2008. "INTEFF3: Stata module to compute partial effects in a probit or logit model with a triple dummy variable interaction term," Statistical Software Components S456903, Boston College Department of Economics, revised 09 Jul 2009.
- Jonathan Gruber & James Poterba, 1994. "Tax Incentives and the Decision to Purchase Health Insurance: Evidence from the Self-Employed," The Quarterly Journal of Economics, Oxford University Press, vol. 109(3), pages 701-733. Full references (including those not matched with items on IDEAS)
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