HeckmanSK {ssmodels}R Documentation

Skew-Normal Sample Selection Model Fit Function

Description

Fits a sample selection model based on the Skew-Normal distribution using Maximum Likelihood Estimation (MLE). This model allows for asymmetry in the distribution of the outcome variable's error term, addressing potential skewness.

Usage

HeckmanSK(
  selection,
  outcome,
  data = sys.frame(sys.parent()),
  lambda,
  start = NULL
)

Arguments

selection

A formula specifying the selection equation.

outcome

A formula specifying the outcome equation.

data

A data frame containing the variables.

lambda

Initial start value for the skewness parameter (lambda).

start

Optional numeric vector of initial parameter values.

Details

The function implements MLE for a sample selection model where the outcome equation's errors follow a Skew-Normal distribution, as proposed in Ogundimu and Hutton (2016). The optimization is performed via the BFGS algorithm.

The results include estimates for:

Value

A list containing:

References

Emmanuel O Ogundimu, Jane L Hutton (2016). “A Sample Selection Model with Skew-normal Distribution.” Scandinavian Journal of Statistics, 43(1), 172–190.

Examples

data("Mroz87")
attach(Mroz87)
selectEq <- lfp ~ huswage + kids5 + mtr + fatheduc + educ + city
outcomeEq <- log(wage) ~ educ + city
HeckmanSK(selectEq, outcomeEq, data = Mroz87, lambda = -1.5)


[Package ssmodels version 2.0.1 Index]