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Missing Data Methods : Cross-Sectional Methods and Applications.
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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Bradford :
Emerald Group Publishing Limited,
2011.
|
| Colección: | Advances in Econometrics, 27.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Drukker, David M. | |
| 245 | 1 | 0 | |a Missing Data Methods : |b Cross-Sectional Methods and Applications. |
| 260 | |a Bradford : |b Emerald Group Publishing Limited, |c 2011. | ||
| 300 | |a 1 online resource (352 pages) | ||
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| 490 | 1 | |a Advances in Econometrics, 27 | |
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 500 | |a Estimating the average treatment effect based on direct estimation of the conditional treatment effect. | ||
| 520 | |a 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. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Missing observations (Statistics) | |
| 650 | 0 | |a Economics |x Statistical methods. | |
| 650 | 6 | |a Observations manquantes (Statistique) | |
| 650 | 6 | |a Économie politique |x Méthodes statistiques. | |
| 650 | 7 | |a Economics |x Statistical methods |2 fast | |
| 650 | 7 | |a Missing observations (Statistics) |2 fast | |
| 758 | |i has work: |a Cross-sectional methods and applications Missing data methods (Text) |1 https://id.oclc.org/worldcat/entity/E39PCFCFQ8M4XhxwHhxCP9Wr4m |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Drukker, David M. |t Missing Data Methods : Cross-Sectional Methods and Applications. |d Bradford : Emerald Group Publishing Limited, ©2011 |z 9781780525242 |
| 830 | 0 | |a Advances in Econometrics, 27. | |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=823633 |z Texto completo |
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