margEff.censReg: Marginal Effects in Censored Regression Models

Description

The margEff method computes the marginal effects of the explanatory variables on the expected value of the dependent variable evaluated at the mean values of the explanatory variables. Please note that this functionality is currently not available for panel data models.

Usage

## S3 method for class 'censReg':
margEff( object, calcVCov = TRUE, returnJacobian = FALSE, ... )
## S3 method for class 'margEff.censReg':
summary( object, ... )

Arguments

object

argument object of the margEff method must be an object of class "censReg" (returned by censReg); argument object of the summary

calcVCov

logical. If TRUE, 
     the approximate variance covariance matrices of the marginal effects 
     is calculated and returned as an attribute (see below).

returnJacobian

logical. If TRUE, 
      the Jacobian of the marginal effects with respect to the coefficients 
      is returned as an attribute (see below).

...

currently not used.

`Value`

margEff.censReg returns an object of class "margEff.censReg",
   which is a vector of the marginal effects of the explanatory variables
   on the expected value of the dependent variable evaluated
   at the mean values of the explanatory variables.
   The returned object has an attribute df.residual, 
   which is equal to the degrees of freedom of the residuals. 
   
   If argument calcVCov is TRUE, 
   the object returned by margEff.censReg has an attribute vcov, 
   which is a the approximate variance covariance matrices 
   of the marginal effects calculated
   with the Delta method.
   
   If argument returnJacobian is TRUE, 
   the object returned by margEff.censReghas an attribute jacobian, 
   which is the Jacobian of the marginal effects 
   with respect to the coefficients.
   summary.margEff.censReg returns 
   an object of class "summary.margEff.censReg",
   which is a matrix with four columns,
   where the first column contains the marginal effects,
   the second column contains the standard errors of the marginal effects,
   the third column contains the corresponding t-values,
   and the fourth columns contains the corresponding P values.

`See Also`

censReg, coef.censReg, 
   and summary.censReg

`Examples`

Run this code## Kleiber & Zeileis ( 2008 ), page 142
data( "Affairs", package = "AER" )
estResult <- censReg( affairs ~ age + yearsmarried + religiousness +
   occupation + rating, data = Affairs )
margEff( estResult )
summary( margEff( estResult ) )
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