@TechReport{dp-504,
  author        = {Schwiebert, Jörg},
  astring       = {Jörg Schwiebert},
  title         = {Semiparametric Estimation of a Sample Selection Model in
                  the Presence of Endogeneity},
  month         = {October},
  year          = {2012},
  pages         = {36},
  size          = {302},
  number        = {504},
  language      = {en},
  keywords      = {Sample selection model, semiparametric estimation,
                  endogenous covariates, control function approach, quantile
                  regression},
  jelclass      = {C21, C24, C26},
  abstract      = {In this paper, we derive a semiparametric estimation
                  procedure for the sample selection model when some
                  covariates are endogenous. Our approach is to augment the
                  main equation of interest with a control function which
                  accounts for sample selectivity as well as endogeneity of
                  covariates. In contrast to existing methods proposed in the
                  literature, our approach allows that the same endogenous
                  covariates may enter the main and the selection equation.
                  We show that our proposed estimator is \sqrt{n}-consistent
                  and derive its asymptotic distribution. We provide Monte
                  Carlo evidence on the small sample behavior of our
                  estimator and present an empirical application. Finally, we
                  brie y consider an extension of our model to quantile
                  regression settings and provide guidelines for estimation.}
}