effect.ivpml {Rchoice}

Get average marginal effects for IV Probit model.

Description

Obtain the average marginal effects from ivpml class model.

Usage

## S3 method for class 'ivpml'
effect(
  object,
  vcov = NULL,
  asf = TRUE,
  digits = max(3, getOption("digits") - 2),
  ...
)

## S3 method for class 'effect.ivpml'
summary(object, ...)

## S3 method for class 'effect.ivpml'
print(x, ...)

## S3 method for class 'summary.effect.ivpml'
print(x, digits = max(3, getOption("digits") - 3), ...)

Arguments

object

an object of class ivpml and effect.ivpml for summary and print method.

vcov

an estimate of the asymptotic variance-covariance matrix of the parameters for a ivpml object.

asf

if TRUE, the average structural function is used.

digits

the number of digits.

...

further arguments.Ignored.

x

an object of class effect.ivpml.

Details

This function allows to obtain the average marginal effects (not the marginal effects at the mean). The standard errors are computed using Delta Method.

Value

An object of class effect.ivpml.

Author(s)

Mauricio Sarrias.

Examples

 
# Data
library("AER")
data("PSID1976")
PSID1976$lfp  <- as.numeric(PSID1976$participation == "yes")
PSID1976$kids <- with(PSID1976, factor((youngkids + oldkids) > 0,
                                      levels = c(FALSE, TRUE), 
                                      labels = c("no", "yes")))
                                      
# Average marginal effects for IV probit model 
# (nwincome is endogenous and heducation is the additional instrument)
PSID1976$nwincome <- with(PSID1976, (fincome - hours * wage)/1000)
fiml.probit <- ivpml(lfp ~  education + experience + I(experience^2) + age + 
                            youngkids + oldkids + nwincome |
                            education + experience + I(experience^2) + age + 
                            youngkids + oldkids + heducation, 
                     data = PSID1976)
summary(effect(fiml.probit))
summary(effect(fiml.probit, asf = FALSE))