HeckmanCL {ssmodels}R Documentation

Classic Heckman Model Fit Function

Description

Fits the classical Heckman sample selection model using Maximum Likelihood Estimation (MLE). Initial parameter estimates are obtained via the two-step method.

Usage

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

Arguments

selection

A formula specifying the selection equation.

outcome

A formula 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

This function estimates the parameters of the classical Heckman sample selection model via MLE, accounting for potential sample selection bias. It uses the optim function with the BFGS method to find the parameter estimates that maximize the log-likelihood function. The initial values for optimization are obtained using the two-step Heckman method.

The function returns a rich set of results, including:

Value

A list containing:

References

James J Heckman (1979). “Sample selection bias as a specification error.” Econometrica: Journal of the econometric society, 153–161.

Examples

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


[Package ssmodels version 2.0.1 Index]