Robust Estimation and Inference in Sample Selection Models
Extract Coefficients from Robust Endogenous Treatment Model Fit
Extract Coefficients from Robust Sample Selection Model Fit
Extract Coefficients from Robust Sample Selection Model Fit
Inverse Mills Ratio Derivative
Inverse Mills Ratio Derivative
Variance Covariance Matrix
Robust Fit of Endogenous Treatment Model
Fitted values of endogenous treatment model
Fitted values of robust sample selection model
Fitted values of robust sample selection model
Variance Covariance Matrix
Variance Covariance Matrix
Robust Heckit Fit: Switching Regressions
Auxiliary for Controlling Robust Fitting
Robust Heckit Fit
M Matrix
Design Matrix of Endogenous Treatment Model
Design Matrix of Switching Regression Model
Design Matrix of Sample Selection Model
Number of Observations
Print a etregrob Object
Print a heckit5rob Object
Print a heckitrob Object
Print Function for summary.etregrob
Print Function for summary.heckit5rob
Print Function for summary.heckitrob
Score Function of the Mallows M-Estimator
Residuals of Robust Endogenous Treatment Model Fit
Residuals of Robust Sample Selection Model Fit
Residuals of Robust Sample Selection Model Fit
Robust Estimation and Inference in Sample Selection Models
Robust Sample Selection Model
Summarizing Robust Fits of Endogenous Treatment Models
Summarizing Robust Fits of Sample Selection Models
Summarizing Robust Fits of Sample Selection Models
Extract Asymptotic Variance Covariance Matrix
Extract Asymptotic Variance Covariance Matrix
Extract Asymptotic Variance Covariance Matrix
Robustness Weights
Robustness Weights
Package provides a set of tools for robust estimation and inference for models with sample selectivity and endogenous treatment model. For details, see Zhelonkin and Ronchetti (2021) <doi:10.18637/jss.v099.i04>.