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 |
delta |
the estimated |
sigma |
the estimated |
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.