twostep: Two-Step Estimation of the Classic Heckman Model

In ssmodels: Sample Selection Models

Two-Step Estimation of the Classic Heckman Model

Description

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

Usage

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

Arguments

selection	A formula for the selection equation.
outcome	A formula for the outcome equation.
data	A data frame containing the variables.

Details

The two-step method first estimates a Probit model for the selection equation, then fits an outcome equation that includes the Inverse Mills Ratio (IMR) as an additional regressor to correct for sample selection bias.

Value

A numeric vector containing:

• Estimated coefficients of the selection equation (Probit model),

• Estimated coefficients of the outcome equation (excluding IMR),

• Estimated standard deviation of the outcome errors (phi),

• Estimated correlation between the error terms (cor).

References

\insertAllCited

For details, see \insertCiteheckman1979sample;textualssmodels.

Examples

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

ssmodels documentation built on June 8, 2025, 10:49 a.m.