heckitVcov

model matrix of the 2nd step estimation.

xMat

model matrix of the 1st step probit estimation.

wMat

variance covariance matrix of the 1st step
 probit estimation.

vcovProbit

the estimated \(\rho\), see Greene (2003, p. 784).

the estimated \(\delta\)s, see Greene (2003, p. 784).

delta

the estimated \(\sigma\), see Greene (2003, p. 784).

sigma

logical. Save memory by using a different implementation
 of the formula? (this should not influence the results).

saveMemory

Calculate the asymptotic covariance matrix
 for the coefficients of a Heckit estimation

models

Two-step
and maximum likelihood estimation
of Heckman-type sample selection models:
standard sample selection models (Tobit-2),
endogenous switching regression models (Tobit-5),
sample selection models with binary dependent outcome variable,
interval regression with sample selection (only ML estimation),
and endogenous treatment effects models.
These methods are described in the three vignettes
that are included in this package
and in econometric textbooks such as
Greene (2011, Econometric Analysis, 7th edition, Pearson).

heckitVcov: Heckit Variance Covariance Matrix

Description

Usage

Arguments

Value

Details

References

See Also