heckitVcov {sampleSelection}R Documentation

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 deltas, see Greene (2003, p. 784).
sigma the estimated σ, see Greene (2003, p. 784).
saveMemory logical. Save memory by using a different implementation of the formula? (this should not influence the results).

Details

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

Value

the variance covariance matrix of the coefficients.

Author(s)

Arne Henningsen

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.


[Package sampleSelection version 0.6-4 Index]