HCinitial {ssmodels}R Documentation

Two-Step Method for Parameter Estimation of the Classical Heckman Model

Description

Estimates the parameters of the classical Heckman sample selection model using the two-step estimation method.

Usage

HCinitial(selection, outcome, data = sys.frame(sys.parent()))

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.

Details

This function implements the two-step approach proposed by Heckman (1979) to estimate the parameters of the classic sample selection model. It is particularly useful for obtaining initial values for maximum likelihood estimation (MLE).

In the first step, a probit model is fitted to the selection equation to estimate the probability of selection. The second step involves estimating a linear regression of the outcome equation for the observed (selected) data, incorporating the inverse Mills ratio (IMR) as an additional regressor to correct for sample selection bias.

The function also estimates:

Value

A named numeric vector 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
HCinitial(selectEq, outcomeEq, data = MEPS2001)


[Package ssmodels version 2.0.1 Index]