Sample Selection Models
Extract Model Components for Selection Models
Two-Step Method for Parameter Estimation of the Classical Heckman Mode...
Heckman-BS Model Fit Function
Classic Heckman Model Fit Function
Generalized Heckman Model Estimation
Skew-Normal Sample Selection Model Fit Function
Heckman-t Model Fit Function
Inverse Mills Ratio (IMR) Calculation
Post-process Parameter Vector for Generalized Heckman Models
ssmodels: Sample Selection Models in R
Heckman's Two-Step Method
Summary of Birnbaum-Saunders Heckman Model
Summary of Classic Heckman Model
Summary of Generalized Heckman Model
Summary of Skew-Normal Heckman Model
Summary of Heckman-t Model
Two-Step Estimation of the Classic Heckman Model
In order to facilitate the adjustment of the sample selection models existing in the literature, we created the 'ssmodels' package. Our package allows the adjustment of the classic Heckman model (Heckman (1976), Heckman (1979) <doi:10.2307/1912352>), and the estimation of the parameters of this model via the maximum likelihood method and two-step method, in addition to the adjustment of the Heckman-t models introduced in the literature by Marchenko and Genton (2012) <doi:10.1080/01621459.2012.656011> and the Heckman-Skew model introduced in the literature by Ogundimu and Hutton (2016) <doi:10.1111/sjos.12171>. We also implemented functions to adjust the generalized version of the Heckman model, introduced by Bastos, Barreto-Souza, and Genton (2021) <doi:10.5705/ss.202021.0068>, that allows the inclusion of covariables to the dispersion and correlation parameters, and a function to adjust the Heckman-BS model introduced by Bastos and Barreto-Souza (2020) <doi:10.1080/02664763.2020.1780570> that uses the Birnbaum-Saunders distribution as a joint distribution of the selection and primary regression variables. This package extends and complements existing R packages such as 'sampleSelection' (Toomet and Henningsen, 2008) and 'ssmrob' (Zhelonkin et al., 2016), providing additional robust and flexible sample selection models.