A Two-Step Estimator for Missing Values in Probit Model Covariates - Thomas Laitila; Lisha Wang (Örebro University School of Business, 2015)
This paper includes a simulation study on the bias and MSE properties of a two-step probit model estimator for handling missing values in covariates by conditional imputation. In one smaller simulation it is compared with an asymptotically efficient estimator and in one larger it is compared with the probit ML on complete cases after listwise deletion. Simulation results obtained favors the use of the two-step probit estimator and motivates further developments of the methodology.
Keywords: C01; C35; 330; binary variable; imputation; OLS; heteroskedasticity