Author: Badi H. Baltagi
Publisher: Emerald Group Publishing
ISBN: 1781903077
Category : Business & Economics
Languages : en
Pages : 576
Book Description
Aims to annually publish original scholarly econometrics papers on designated topics with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics throughout the empirical economic, business and social science literature.
Essays in Honor of Jerry Hausman
Author: Badi H. Baltagi
Publisher: Emerald Group Publishing
ISBN: 1781903077
Category : Business & Economics
Languages : en
Pages : 576
Book Description
Aims to annually publish original scholarly econometrics papers on designated topics with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics throughout the empirical economic, business and social science literature.
Publisher: Emerald Group Publishing
ISBN: 1781903077
Category : Business & Economics
Languages : en
Pages : 576
Book Description
Aims to annually publish original scholarly econometrics papers on designated topics with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics throughout the empirical economic, business and social science literature.
The Oxford Handbook of Panel Data
Author: Badi Hani Baltagi
Publisher:
ISBN: 0199940045
Category : Business & Economics
Languages : en
Pages : 705
Book Description
The Oxford Handbook of Panel Data examines new developments in the theory and applications of panel data. It includes basic topics like non-stationary panels, co-integration in panels, multifactor panel models, panel unit roots, measurement error in panels, incidental parameters and dynamic panels, spatial panels, nonparametric panel data, random coefficients, treatment effects, sample selection, count panel data, limited dependent variable panel models, unbalanced panel models with interactive effects and influential observations in panel data. Contributors to the Handbook explore applications of panel data to a wide range of topics in economics, including health, labor, marketing, trade, productivity, and macro applications in panels. This Handbook is an informative and comprehensive guide for both those who are relatively new to the field and for those wishing to extend their knowledge to the frontier. It is a trusted and definitive source on panel data, having been edited by Professor Badi Baltagi-widely recognized as one of the foremost econometricians in the area of panel data econometrics. Professor Baltagi has successfully recruited an all-star cast of experts for each of the well-chosen topics in the Handbook.
Publisher:
ISBN: 0199940045
Category : Business & Economics
Languages : en
Pages : 705
Book Description
The Oxford Handbook of Panel Data examines new developments in the theory and applications of panel data. It includes basic topics like non-stationary panels, co-integration in panels, multifactor panel models, panel unit roots, measurement error in panels, incidental parameters and dynamic panels, spatial panels, nonparametric panel data, random coefficients, treatment effects, sample selection, count panel data, limited dependent variable panel models, unbalanced panel models with interactive effects and influential observations in panel data. Contributors to the Handbook explore applications of panel data to a wide range of topics in economics, including health, labor, marketing, trade, productivity, and macro applications in panels. This Handbook is an informative and comprehensive guide for both those who are relatively new to the field and for those wishing to extend their knowledge to the frontier. It is a trusted and definitive source on panel data, having been edited by Professor Badi Baltagi-widely recognized as one of the foremost econometricians in the area of panel data econometrics. Professor Baltagi has successfully recruited an all-star cast of experts for each of the well-chosen topics in the Handbook.
Short-Memory Linear Processes and Econometric Applications
Author: Kairat T. Mynbaev
Publisher: John Wiley & Sons
ISBN: 1118007670
Category : Business & Economics
Languages : en
Pages : 361
Book Description
This book serves as a comprehensive source of asymptotic results for econometric models with deterministic exogenous regressors. Such regressors include linear (more generally, piece-wise polynomial) trends, seasonally oscillating functions, and slowly varying functions including logarithmic trends, as well as some specifications of spatial matrices in the theory of spatial models. The book begins with central limit theorems (CLTs) for weighted sums of short memory linear processes. This part contains the analysis of certain operators in Lp spaces and their employment in the derivation of CLTs. The applications of CLTs are to the asymptotic distribution of various estimators for several econometric models. Among the models discussed are static linear models with slowly varying regressors, spatial models, time series autoregressions, and two nonlinear models (binary logit model and nonlinear model whose linearization contains slowly varying regressors). The estimation procedures include ordinary and nonlinear least squares, maximum likelihood, and method of moments. Additional topical coverage includes an introduction to operators, probabilities, and linear models; Lp-approximable sequences of vectors; convergence of linear and quadratic forms; regressions with slowly varying regressors; spatial models; convergence; nonlinear models; and tools for vector autoregressions.
Publisher: John Wiley & Sons
ISBN: 1118007670
Category : Business & Economics
Languages : en
Pages : 361
Book Description
This book serves as a comprehensive source of asymptotic results for econometric models with deterministic exogenous regressors. Such regressors include linear (more generally, piece-wise polynomial) trends, seasonally oscillating functions, and slowly varying functions including logarithmic trends, as well as some specifications of spatial matrices in the theory of spatial models. The book begins with central limit theorems (CLTs) for weighted sums of short memory linear processes. This part contains the analysis of certain operators in Lp spaces and their employment in the derivation of CLTs. The applications of CLTs are to the asymptotic distribution of various estimators for several econometric models. Among the models discussed are static linear models with slowly varying regressors, spatial models, time series autoregressions, and two nonlinear models (binary logit model and nonlinear model whose linearization contains slowly varying regressors). The estimation procedures include ordinary and nonlinear least squares, maximum likelihood, and method of moments. Additional topical coverage includes an introduction to operators, probabilities, and linear models; Lp-approximable sequences of vectors; convergence of linear and quadratic forms; regressions with slowly varying regressors; spatial models; convergence; nonlinear models; and tools for vector autoregressions.
Journal of the American Statistical Association
Author:
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 920
Book Description
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 920
Book Description
Modern Methods for Robust Regression
Author: Robert Andersen
Publisher: SAGE
ISBN: 1412940729
Category : Mathematics
Languages : en
Pages : 129
Book Description
Offering an in-depth treatment of robust and resistant regression, this volume takes an applied approach and offers readers empirical examples to illustrate key concepts.
Publisher: SAGE
ISBN: 1412940729
Category : Mathematics
Languages : en
Pages : 129
Book Description
Offering an in-depth treatment of robust and resistant regression, this volume takes an applied approach and offers readers empirical examples to illustrate key concepts.
Econometrics
Author: Franco Peracchi
Publisher: John Wiley & Sons
ISBN: 0471987646
Category : Business & Economics
Languages : en
Pages : 706
Book Description
In Econometrics the author has provided a text that bridges the gap between classical econometrics (with an emphasis on linear methods such as OLS, GLS and instrumental variables) and some of the key research areas of the last few years, including sampling problems, nonparametric methods and panel data analysis. Designed for advanced undergraduates and postgraduate students of the subject, Econometrics provides rigorous, yet accessible, coverage of the subject. Key features include: * A unified approach to statistical estimation emphasising the analogy (or bootstrap) principle * An introduction to bootstrap and jackknife methods for assessing the accuracy of an estimator * Detailed discussion of nonparametric methods for estimating density and regression of functions * Emphasis on diagnostic procedures and on prediction criteria for evaluating the results fo statistical analysis * An introduction to linear exponential family and generalized linear models * A thorough discussion of robustness in statistical sense
Publisher: John Wiley & Sons
ISBN: 0471987646
Category : Business & Economics
Languages : en
Pages : 706
Book Description
In Econometrics the author has provided a text that bridges the gap between classical econometrics (with an emphasis on linear methods such as OLS, GLS and instrumental variables) and some of the key research areas of the last few years, including sampling problems, nonparametric methods and panel data analysis. Designed for advanced undergraduates and postgraduate students of the subject, Econometrics provides rigorous, yet accessible, coverage of the subject. Key features include: * A unified approach to statistical estimation emphasising the analogy (or bootstrap) principle * An introduction to bootstrap and jackknife methods for assessing the accuracy of an estimator * Detailed discussion of nonparametric methods for estimating density and regression of functions * Emphasis on diagnostic procedures and on prediction criteria for evaluating the results fo statistical analysis * An introduction to linear exponential family and generalized linear models * A thorough discussion of robustness in statistical sense
Information Theory and Statistical Learning
Author: Frank Emmert-Streib
Publisher: Springer Science & Business Media
ISBN: 0387848150
Category : Computers
Languages : en
Pages : 443
Book Description
This interdisciplinary text offers theoretical and practical results of information theoretic methods used in statistical learning. It presents a comprehensive overview of the many different methods that have been developed in numerous contexts.
Publisher: Springer Science & Business Media
ISBN: 0387848150
Category : Computers
Languages : en
Pages : 443
Book Description
This interdisciplinary text offers theoretical and practical results of information theoretic methods used in statistical learning. It presents a comprehensive overview of the many different methods that have been developed in numerous contexts.
Mixed Effects Models for Complex Data
Author: Lang Wu
Publisher: CRC Press
ISBN: 9781420074086
Category : Mathematics
Languages : en
Pages : 431
Book Description
Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.
Publisher: CRC Press
ISBN: 9781420074086
Category : Mathematics
Languages : en
Pages : 431
Book Description
Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.
Journal of Econometrics
Author:
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 860
Book Description
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 860
Book Description
Robust Statistics, Data Analysis, and Computer Intensive Methods
Author: Helmut Rieder
Publisher: Springer
ISBN:
Category : Mathematics
Languages : en
Pages : 454
Book Description
This book gathers together a wide range of contributions on modern techniques which are becoming widely used in statistics. These methods include the bootstrap, nonparametric density estimation, robust regression, and projections and sections.
Publisher: Springer
ISBN:
Category : Mathematics
Languages : en
Pages : 454
Book Description
This book gathers together a wide range of contributions on modern techniques which are becoming widely used in statistics. These methods include the bootstrap, nonparametric density estimation, robust regression, and projections and sections.