@TechReport{dp-483,
  author        = {Schwiebert, Jörg },
  astring       = {Jörg Schwiebert},
  title         = {A Full InformationMaximum Likelihood Approach to
                  Estimating the Sample Selection Model with Endogenous
                  Covariates},
  month         = {November},
  year          = {2011},
  pages         = {21},
  size          = {100},
  number        = {483},
  language      = {en},
  keywords      = {Sample Selection Model; Endogeneity; Maximum Likelihood
                  Estimation; Female Labor Supply},
  jelclass      = {C31, C34, C36},
  abstract      = {In this paper we establish a full information maximum
                  likelihood approach to estimating the sample selection
                  model with endogenous covariates. We also provide a test
                  for exogeneity which indicates whether endogeneity is in
                  fact a matter or not. In contrast to other methods proposed
                  in the literature which deal with sample selection and
                  endogeneity, our approach is computationally simple and
                  provides exact asymptotic standard errors derived from
                  common maximum likelihood theory. A Monte Carlo study and
                  an empirical example are presented which indicate that not
                  accounting for endogeneity in sample selection models may
                  lead to severely biased parameter estimates.}
}