Simplified Marginal Effects in Discrete Choice Models
AbstractWe 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.
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Bibliographic InfoPaper provided by Resources For the Future in its series Discussion Papers with number dp-03-38.
Date of creation: 01 Dec 2003
Date of revision:
logit; probit; discrete choice; binary choice; marginal effect; data normalization;
Other versions of this item:
- Anderson, Soren & Newell, Richard G., 2003. "Simplified marginal effects in discrete choice models," Economics Letters, Elsevier, vol. 81(3), pages 321-326, December.
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- 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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