HeckmanBS {ssmodels}R Documentation

Heckman-BS Model Fit Function

Description

Fits the Heckman Sample Selection Model based on the Birnbaum-Saunders (BS) bivariate distribution. This function implements the maximum likelihood estimation of the model parameters.

Usage

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

Arguments

selection

A formula object specifying the selection equation.

outcome

A formula object specifying the primary outcome equation.

data

A data frame containing the variables in the model.

start

An optional numeric vector of initial parameter values. If not provided, default values are used.

Details

The function estimates the parameters of the Heckman-BS model, which extends the classical Heckman model by assuming that the error terms follow a bivariate Birnbaum-Saunders distribution. The model has the same number of parameters as the classical Heckman model, including the correlation coefficient between the error terms. The optimization is performed using the optim function with the BFGS method.

The estimated quantities include:

Additional outputs include measures of model fit, standard errors (approximated by the square root of the diagonal of the inverse Fisher information matrix), and diagnostic information.

Value

A list containing:

References

There are no references for Rd macro ⁠\insertAllCites⁠ on this help page.

Examples

data(MEPS2001)
attach(MEPS2001)
selectEq <- dambexp ~ age + female + educ + blhisp + totchr + ins + income
outcomeBS <- ambexp ~ age + female + educ + blhisp + totchr + ins
HeckmanBS(selectEq, outcomeBS, data = MEPS2001)


[Package ssmodels version 2.0.1 Index]