heckitVcov {sampleSelection} | R Documentation |
Calculate the asymptotic covariance matrix for the coefficients of a Heckit estimation
heckitVcov( xMat, wMat, vcovProbit, rho, delta, sigma, saveMemory = TRUE )
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). |
The formula implemented in heckitVcov
is available,
e.g., in Greene (2003), last formula on page 785.
the variance covariance matrix of the coefficients.
Arne Henningsen ahenningsen@agric-econ.uni-kiel.de
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.