Marginal effects for distributions such as probit and logit can be computed with PROC QLIM by using the MARGINAL option in the OUTPUT statement. Hence, they generally cannot be inferred directly from parameter estimates. The marginal effects are nonlinear functions of the parameter estimates and levels of the explanatory variables. Where is the density function that corresponds to the cumulative function. They are obtained by computing the derivative of the conditional mean function with respect to given by Marginal effect is a measure of the instantaneous effect that a change in a particular explanatory variable has on the predicted probability of, when the other covariates are kept fixed. Where denotes a cumulative distribution function and denotes the parameters. The conditional mean function is given by Where is the conditional mean function, is the vector of explanatory variables, and is the error term. The dependent variable is modeled as follows:
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