LEADER 05355nam 2200649 a 450 001 9910457762403321 005 20200520144314.0 010 $a1-283-35486-1 010 $a9786613354860 010 $a1-78052-525-7 035 $a(CKB)2550000000075820 035 $a(EBL)823633 035 $a(OCoLC)769342567 035 $a(SSID)ssj0000613356 035 $a(PQKBManifestationID)11386648 035 $a(PQKBTitleCode)TC0000613356 035 $a(PQKBWorkID)10585123 035 $a(PQKB)10716881 035 $a(MiAaPQ)EBC823633 035 $a(Au-PeEL)EBL823633 035 $a(CaPaEBR)ebr10520749 035 $a(CaONFJC)MIL335486 035 $a(EXLCZ)992550000000075820 100 $a20120110d2011 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aMissing data methods$b[electronic resource] $ecross-sectional methods and applications /$fedited by David M. Drukker 205 $a1st ed. 210 $aBingley [England] $cEmerald Group Pub.$d2011 215 $a1 online resource (352 p.) 225 1 $aAdvances in econometrics,$x0731-9053 ;$vv. 27 300 $aDescription based upon print version of record. 311 $a1-78052-524-9 320 $aIncludes bibliographical references. 327 $aFront 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 327 $aRecent 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 327 $aIntroductionModel, 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 327 $aNotesAcknowledgment; 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 327 $aSimulationsEmpirical 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 327 $aEstimating the average treatment effect based on direct estimation of the conditional treatment effect 330 $aVolume 27 of Advances in Econometrics, entitled Missing Data Methods, contains 16 chapters authored by specialists in the field, covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; Consistent Estimation and Orthogonality; and Likelihood-Based Estimators for Endogenous or Truncated Samples in Standard Stratified Sampling. 410 0$aAdvances in econometrics ;$vv. 27. 606 $aMissing observations (Statistics) 608 $aElectronic books. 615 0$aMissing observations (Statistics) 676 $a330.015195 701 $aDrukker$b David M$0965149 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910457762403321 996 $aMissing data methods$92189718 997 $aUNINA