sampleSelection (version 0.6-10)

heckitVcov: Heckit Variance Covariance Matrix

Description

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

Usage

heckitVcov( xMat, wMat, vcovProbit, rho, delta, sigma,
   saveMemory = TRUE )

Arguments

xMat

model matrix of the 2nd step estimation.

wMat

model matrix of the 1st step probit estimation.

vcovProbit

variance covariance matrix of the 1st step probit estimation.

rho

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

delta

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

sigma

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

saveMemory

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

Value

• the variance covariance matrix of the coefficients.

Details

The formula implemented in heckitVcov is available, e.g., in Greene (2003), last formula on page 785.

References

Greene, W. H. (2003) Econometric Analysis, Fifth Edition, Prentice Hall.

Lee, L., G. Maddala and R. Trost (1980) Asymetric covariance matrices of two-stage probit and two-stage tobit methods for simultaneous equations models with selectivity. Econometrica, 48, p. 491-503.

See Also

heckit.