epmrob: Robust Fit of Probit Model with Endogeneity

In epmrob: Robust Estimation of Probit Models with Endogeneity

Robust Fit of Probit Model with Endogeneity

Description

Fits the endogenous probit model using a robust two-stage estimator.

Usage

epmrob(reduced, outcome, data, control = rob.control())

Arguments

reduced	formula, the reduced equation.
outcome	formula, the outcome equation.
data	an optional data frame containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which epmrob is called.
control	a list of parameterse for controlling the fitting process.

Details

Compute robust two-step estimates of the endogenous probit model. The robust linear regression is fitted in the first stage. In the second stage a Mallows-type M-estimator is used instead of the probit MLE. The values of the tuning constants and the robustness weights can be modified in rob.control.

Value

Object of class "epmrob".

coefficients	a named vector of coefficients
stage1	object of class rlm that contains first stage robust fit
stage2	object of class glmrob that contains second stage robust probit fit. Note that the standard errors in this object are biased, since they are not corrected for the uncertainty in the first estimation step. Use vcov below
vcov	variance matrix of the second stage
call	the matched call

Author(s)

Mikhail Zhelonkin, Andre Bik, Andrea Naghi

References

Naghi, A. A., Varadi, M., and Zhelonkin, M. (2022). Robust Estimation of Probit Models with Endogeneity. Econometrics and Statistics. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.ecosta.2022.05.001")}

See Also

rlm, rob.control

epmrob documentation built on July 9, 2023, 6:19 p.m.