epmrob (version 0.1)

IVProbitRob: Robust Probit Model with Endogeneity

Description

Compute robust two-stage estimates of probit model with endogeneity.

Usage

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

Value

Object of class "epmrob".

Arguments

reduced

formula, the reduced function.

outcome

formula, the outcome function.

data

an optional data fram containing the varaibles in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which IVProbitRob is called.

control

a list of parameters for controlling the fitting process.

Author

Mikhail Zhelonkin, Andre Bik, Andrea Naghi

Details

Compute robust two-step estimates of the endogenous probit model.

References

Naghi, A. A., Varadi, M., & Zhelonkin, M. (2022). Robust Estimation of Probit Models with Endogeneity. Econometrics and Statistics. tools:::Rd_expr_doi("10.1016/j.ecosta.2022.05.001")

See Also

epmrob

Examples

library(mvtnorm)
N <- 2000
M <- 500
cont.frac = 0.01
rho = 0.5
sigma = matrix(c(1, rho, rho, 1), 2, 2)
gamma1 = 1
gamma2 = c(0.6, 0.4) 
alpha1 = c(0.5)
beta1 = 0.5

set.seed(123)
X1 = rnorm(N,0,1)
X2 = rnorm(N,0,1)
X3 = rnorm(N,0,1)
eps = rmvnorm(N, mean =rep(0,2), sigma = sigma)
Y1 = X1*gamma1 + X2*gamma2[1] + X3*gamma2[2]  + eps[,1]
Y2 = ifelse(X1*beta1 + Y1*alpha1 + eps[,2] > 0, 1, 0)

dat.exmpl <- data.frame(Y2, Y1, X1, X2, X3)
names(dat.exmpl) <- c("int", "endo", "exo", "ivrbl", "ivrbl2")
ivp.fit <- IVProbitRob(endo ~ exo + ivrbl + ivrbl2, int ~ endo + exo, data = dat.exmpl, 
                       control = rob.control(weights.x1 = "hat", weights.x2 = "hat"))
ivp.fit