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

• Pubblicazione: Bingley [England], : Emerald Group Pub., 2011
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (352 p.)
• Disciplina: 330.015195
• Soggetto topico: Missing observations (Statistics)
• Soggetto genere / forma: Electronic books.
• Altri autori: DrukkerDavid M
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: Front Cover; Missing Data Methods: Cross-sectional Methods and Applications; Copyright Page; Contents; List of contributors; Introduction; Cross-sectional methods and applications; Acknowledgments; References; The elephant in the corner: a cautionary tale about measurement error in treatment effects models; Introduction; Consequences of measurement error; Evidence of measurement error; Causal inference under conditional independence; Estimation in the Absence of Measurement Error; Monte carlo study; Results; Conclusion; Notes; Acknowledgments; References ; Recent developments in semiparametric and nonparametric estimation of panel data models with incomplete information: A selected reviewIntroduction; Models with incomplete data; Measurement Error; Concluding remarks; Notes; References; Likelihood-based estimators for endogenous or truncated samples in standard stratified sampling; Introduction; Four types of estimators; A simulation study; Conclusions; ACKNOWLEDGMENTS; References; Taking into Account FX-FX for Asymptotic Variance; Efficient estimation of the dose-response function under ignorability using subclassification on the covariates ; IntroductionModel, identification, and estimator; Large sample results; Simulations; Extensions and final remarks; Notes; Acknowledgments; References; Average derivative estimation with missing responses; Introduction; The model and estimator; Asymptotic results; Monte carlo experiments; Acknowledgments; References; Auxiliary Notation and Results; Main Proofs; Consistent estimation and orthogonality; Introduction; Preliminaries and notation; The likelihood function: three orthogonality concepts; Inference based on the score; Inconsistency of the integrated likelihood estimator; Conclusion ; NotesAcknowledgment; References; Orthogonality in the single index model; On the estimation of selection models when participation is endogenous and misclassified; Introduction; The model and estimator; Sampling algorithm; Simulated data example; Summary and conclusions; Notes; Acknowledgments; References; summary tables for additional simulations; Process for simulating non--normal errors; Efficient probit estimation with partially missing covariates; Introduction; Model Specification; Efficient estimators and variances; Testing assumptions and possible modifications; Other models ; SimulationsEmpirical application to portfolio allocation; Conclusion; Notes; Acknowledgment; References; Efficient estimators of Bx and Bw; Variances of Bx and Bw; The case of observed Y; Nonlinear difference-in-difference treatment effect estimation: A distributional analysis; Introduction; Methodology; Monte Carlo simulation; Empirical application; Conclusion; Notes; Acknowledgment; References; Bayesian analysis of multivariate sample selection models using gaussian copulas; Introduction; Copulas; Model; Estimation; Applications; Concluding remarks; Acknowledgments; References ; Estimating the average treatment effect based on direct estimation of the conditional treatment effect
• Sommario/riassunto: 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.
• Titolo autorizzato: Missing data methods
• ISBN: 1-283-35486-1; 9786613354860; 1-78052-525-7
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910457762403321
• Lo trovi qui: Univ. Federico II
• Serie: Advances in econometrics ; ; v. 27.