Some EM-Type Estimation Methods for the Heckman Selection Model
Getting Coefficients of EM type Sample Selection Model Fits
Getting Confidence Intervals for Parameters of EM type Sample Selectio...
EM type Estimation Methods for the Heckman's Sample Selection Model
Summarizing EM type Sample Selection Model Fits
Getting Variance-Covariance Matrix for Parameters of EM type Sample Se...
Some EM-type algorithms to estimate parameters for the well-known Heckman selection model are provided in the package. Such algorithms are as follow: ECM(Expectation/Conditional Maximization), ECM(NR)(the Newton-Raphson method is adapted to the ECM) and ECME(Expectation/Conditional Maximization Either). Since the algorithms are based on the EM algorithm, they also have EM’s main advantages, namely, stability and ease of implementation. Further details and explanations of the algorithms can be found in Zhao et al. (2020) <doi: 10.1016/j.csda.2020.106930>.