HeckmantS {ssmodels}R Documentation

Heckman-t Model Fit Function

Description

Fits a sample selection model based on the Student's t-distribution, extending the classical Heckman model to account for heavy-tailed error terms. The estimation is performed via Maximum Likelihood using the BFGS algorithm.

Usage

HeckmantS(selection, outcome, data = sys.frame(sys.parent()), df, start = NULL)

Arguments

selection

A formula specifying the selection equation.

outcome

A formula specifying the outcome equation.

data

A data frame containing the variables in the model.

df

Initial value for the degrees of freedom parameter of the t-distribution.

start

Optional numeric vector of initial parameter values.

Details

The function implements the Heckman sample selection model using the Student's t-distribution for the error terms, as proposed by Marchenko and Genton (2012). This extension allows for robustness against outliers and heavy-tailed distributions. Initial parameter values can be specified by the user or default to standard starting values.

Value

A list containing:

References

Yulia V Marchenko, Marc G Genton (2012). “A Heckman selection-t model.” Journal of the American Statistical Association, 107(497), 304–317.

Examples

data(MEPS2001)
attach(MEPS2001)
selectEq <- dambexp ~ age + female + educ + blhisp + totchr + ins + income
outcomeEq <- lnambx ~ age + female + educ + blhisp + totchr + ins
HeckmantS(selectEq, outcomeEq, data = MEPS2001, df = 12)


[Package ssmodels version 2.0.1 Index]