etreg2steprobVcov: Variance Covariance Matrix

Description Usage Arguments Details Value Author(s) References

View source: R/etreg2steprobVcov.R

Description

Computation of the asymptotic variance matrix of the robust Heckman's two-stage estimator for endogenous treatment model.

Usage

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etreg2steprobVcov(y1vec, y2vec, x1Matr, x2Matr, eststage1, eststage2, eststage2sigma, 
				  weights = rep(1, nrow(y1vec)), t.c = 1.345)

Arguments

y1vec

vector of endogenous variables of the selection stage

y2vec

vector of endogenous variables of the outcome stage

x1Matr

matrix of exogenous variables of the selection stage

x2Matr

matrix of exogenous variables of the outcome stage

eststage1

object of class "glmrob", corresponding to the robust probit fit

eststage2

vector of the coefficients of the outcome stage

eststage2sigma

the robust scale estimate of the second stage regression

weights

robustness weights

t.c

tuning constant of the second stage

Details

The computation is made using the Huber (1967) - White (1980) sandwich estimator. In the computation of leverage weights the lambda's are assumed to be fixed.

Value

Variance covariance matrix of the second stage estimator

Author(s)

Mikhail Zhelonkin

References

Huber, P.J. (1967) The Behavior of Maximum Likelihood Estimates under Nonstandard Conditions. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability; L.M. LeCam, J. Neyman (Eds.), Berkeley: University of California Press, p. 221-233.

White, H.J. (1980) A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity. Econometrica, 48, p. 817-838.


ssmrob documentation built on April 2, 2020, 5:07 p.m.