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[null,"1.","Record Nr.",null,"UNINA9910457762403321"]
[null,null,"Titolo",null,"Missing data methods [[electronic resource] ] : cross-sectional methods and applications / / edited by David M. Drukker"]
[null,null,"Pubbl/distr/stampa",null,"Bingley [England], : Emerald Group Pub., 2011"]
[null,null,"ISBN",null,"1-283-35486-1"]
[{"$nulls":4},"9786613354860"]
[{"$nulls":4},"1-78052-525-7"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (352 p.)"]
[null,null,"Collana",null,"Advances in econometrics, , 0731-9053 ; ; v. 27"]
[null,null,"Disciplina",null,"330.015195"]
[null,null,"Soggetti",null,"Missing observations (Statistics)"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,null,"Nota di contenuto",null,"Front Cover; Missing Data Methods: Cross-sectional Methods and Applications; Copyright Page; Contents; List of contributors; Introduction; Cross-sectional methods and applications; Acknowledgments; References; The elephant in the corner: a cautionary tale about measurement error in treatment effects models; Introduction; Consequences of measurement error; Evidence of measurement error; Causal inference under conditional independence; Estimation in the Absence of Measurement Error; Monte carlo study; Results; Conclusion; Notes; Acknowledgments; References"]
[{"$nulls":4},"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"]
[{"$nulls":4},"IntroductionModel, identification, and estimator; Large sample results; Simulations; Extensions and final remarks; Notes; Acknowledgments; References; Average derivative estimation with missing responses; Introduction; The model and estimator; Asymptotic results; Monte carlo experiments; Acknowledgments; References; Auxiliary Notation and "]
[{"$nulls":4},"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"]
[{"$nulls":4},"NotesAcknowledgment; References; Orthogonality in the single index model; On the estimation of selection models when participation is endogenous and misclassified; Introduction; The model and estimator; Sampling algorithm; Simulated data example; Summary and conclusions; Notes; Acknowledgments; References; summary tables for additional simulations; Process for simulating non--normal errors; Efficient probit estimation with partially missing covariates; Introduction; Model Specification; Efficient estimators and variances; Testing assumptions and possible modifications; Other models"]
[{"$nulls":4},"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"]
[{"$nulls":4},"Estimating the average treatment effect based on direct estimation of the conditional treatment effect"]
[null,null,null,"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."]