Missing data methods [electronic resource] : cross-sectional methods and applications / edited by David M. Drukker.

Introduction / David M. Drukker -- The elephant in the corner : a cautionary tale about measurement error in treatment effects models / Daniel L. Millimet -- Recent developments in semiparametric and nonparametric estimation of panel data models with incomplete information : a selected review / Yu Yvette Zhang, Qi Li, Dong Li -- Likelihood-based estimators for endogenous or truncated samples in standard stratified sampling / Myoung-jae Lee, Sanghyeok Lee -- Efficient estimation of the dose-response function under ignorability using subclassification on the covariates / Matias D. Cattaneo, Max H. Farrell -- Average derivative estimation with missing responses / Francesco Bravo, Kim P. Huynh, David T. Jacho-Chávez -- Consistent estimation and orthogonality / Tiemen Woutersen -- On the estimation of selection models when participation is endogenous and misclassified / Ian M. McCarthy, Rusty Tchernis -- Efficient probit estimation with partially missing covariates / Denis Conniffe, Donal O'Neill -- Nonlinear difference-in-difference treatment effect estimation : a distributional analysis / Kim P. Huynh, David T. Jacho-Chávez, Marcel C. Voia -- Bayesian analysis of multivariate sample selection models using Gaussian copulas / Phillip Li, Mohammad Arshad Rahman -- Estimating the average treatment effect based on direct estimation of the conditional treatment effect / Jingping Gu, Juan Lin, Dandan Liu -- A missing variable imputation methodology with an empirical application / Gayaneh Kyureghian, Oral Capps, Rodolfo M. Nayga.

Volume 27 of Advances in Econometrics, entitled Missing Data Methods, contains 16 chapters authored by specialists in the field, covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; Consistent Estimation and Orthogonality; and Likelihood-Based Estimators for Endogenous or Truncated Samples in Standard Stratified Sampling.