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Methods for Estimation and Inference in Modern Econometrics

Author: Stanislav Anatolyev

Publisher: CRC Press

Published: 2011-06-07

Total Pages: 230

ISBN-13: 1439838267

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This book covers important topics in econometrics. It discusses methods for efficient estimation in models defined by unconditional and conditional moment restrictions, inference in misspecified models, generalized empirical likelihood estimators, and alternative asymptotic approximations. The first chapter provides a general overview of established nonparametric and parametric approaches to estimation and conventional frameworks for statistical inference. The next several chapters focus on the estimation of models based on moment restrictions implied by economic theory. The final chapters cover nonconventional asymptotic tools that lead to improved finite-sample inference.

Book Synopsis Methods for Estimation and Inference in Modern Econometrics by : Stanislav Anatolyev

Download or read book Methods for Estimation and Inference in Modern Econometrics written by Stanislav Anatolyev and published by CRC Press. This book was released on 2011-06-07 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers important topics in econometrics. It discusses methods for efficient estimation in models defined by unconditional and conditional moment restrictions, inference in misspecified models, generalized empirical likelihood estimators, and alternative asymptotic approximations. The first chapter provides a general overview of established nonparametric and parametric approaches to estimation and conventional frameworks for statistical inference. The next several chapters focus on the estimation of models based on moment restrictions implied by economic theory. The final chapters cover nonconventional asymptotic tools that lead to improved finite-sample inference.

Estimation and Inference in Econometrics

Author: Russell Davidson

Publisher:

Published: 1993

Total Pages: 906

ISBN-13:

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Offering students a unifying theoretical perspective, this innovative text emphasizes nonlinear techniques of estimation, including nonlinear least squares, nonlinear instrumental variables, maximum likelihood and the generalized method of moments, but nevertheless relies heavily on simple geometrical arguments to develop intuition. One theme of the book is the use of artificial regressions for estimation, inference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, series correlation, heteroskedasticity and other types of misspecification. Other topics include the linear simultaneous equations model, non-nested hypothesis tests, influential observations and leverage, transformations of the dependent variable, binary response models, models for time-series/cross-section data, multivariate models, seasonality, unit roots and cointegration, and Monte Carlo methods, always with an emphasis on problems that arise in applied work.Explaining throughout how estimates can be obtained and tests can be carried out, the text goes beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. A comprehensive and coherent guide to the most vital topics in econometrics today, this text is indispensable for all levels of students of econometrics, economics, and statistics on regression and related topics.

Book Synopsis Estimation and Inference in Econometrics by : Russell Davidson

Download or read book Estimation and Inference in Econometrics written by Russell Davidson and published by . This book was released on 1993 with total page 906 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering students a unifying theoretical perspective, this innovative text emphasizes nonlinear techniques of estimation, including nonlinear least squares, nonlinear instrumental variables, maximum likelihood and the generalized method of moments, but nevertheless relies heavily on simple geometrical arguments to develop intuition. One theme of the book is the use of artificial regressions for estimation, inference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, series correlation, heteroskedasticity and other types of misspecification. Other topics include the linear simultaneous equations model, non-nested hypothesis tests, influential observations and leverage, transformations of the dependent variable, binary response models, models for time-series/cross-section data, multivariate models, seasonality, unit roots and cointegration, and Monte Carlo methods, always with an emphasis on problems that arise in applied work.Explaining throughout how estimates can be obtained and tests can be carried out, the text goes beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. A comprehensive and coherent guide to the most vital topics in econometrics today, this text is indispensable for all levels of students of econometrics, economics, and statistics on regression and related topics.

Estimation, Inference and Specification Analysis

Author: Halbert White

Publisher: Cambridge University Press

Published: 1996-06-28

Total Pages: 396

ISBN-13: 9780521574464

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This book examines the consequences of misspecifications for the interpretation of likelihood-based methods of statistical estimation and interference. The analysis concludes with an examination of methods by which the possibility of misspecification can be empirically investigated.

Book Synopsis Estimation, Inference and Specification Analysis by : Halbert White

Download or read book Estimation, Inference and Specification Analysis written by Halbert White and published by Cambridge University Press. This book was released on 1996-06-28 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the consequences of misspecifications for the interpretation of likelihood-based methods of statistical estimation and interference. The analysis concludes with an examination of methods by which the possibility of misspecification can be empirically investigated.

Simulation-based Inference in Econometrics

Author: Roberto Mariano

Publisher: Cambridge University Press

Published: 2000-07-20

Total Pages: 488

ISBN-13: 9780521591126

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This substantial volume has two principal objectives. First it provides an overview of the statistical foundations of Simulation-based inference. This includes the summary and synthesis of the many concepts and results extant in the theoretical literature, the different classes of problems and estimators, the asymptotic properties of these estimators, as well as descriptions of the different simulators in use. Second, the volume provides empirical and operational examples of SBI methods. Often what is missing, even in existing applied papers, are operational issues. Which simulator works best for which problem and why? This volume will explicitly address the important numerical and computational issues in SBI which are not covered comprehensively in the existing literature. Examples of such issues are: comparisons with existing tractable methods, number of replications needed for robust results, choice of instruments, simulation noise and bias as well as efficiency loss in practice.

Book Synopsis Simulation-based Inference in Econometrics by : Roberto Mariano

Download or read book Simulation-based Inference in Econometrics written by Roberto Mariano and published by Cambridge University Press. This book was released on 2000-07-20 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: This substantial volume has two principal objectives. First it provides an overview of the statistical foundations of Simulation-based inference. This includes the summary and synthesis of the many concepts and results extant in the theoretical literature, the different classes of problems and estimators, the asymptotic properties of these estimators, as well as descriptions of the different simulators in use. Second, the volume provides empirical and operational examples of SBI methods. Often what is missing, even in existing applied papers, are operational issues. Which simulator works best for which problem and why? This volume will explicitly address the important numerical and computational issues in SBI which are not covered comprehensively in the existing literature. Examples of such issues are: comparisons with existing tractable methods, number of replications needed for robust results, choice of instruments, simulation noise and bias as well as efficiency loss in practice.

Maximum Likelihood Estimation and Inference

Author: Russell B. Millar

Publisher: John Wiley & Sons

Published: 2011-07-26

Total Pages: 286

ISBN-13: 1119977711

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This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodology, including general latent variable models and new material for the practical implementation of integrated likelihood using the free ADMB software. Fundamental issues of statistical inference are also examined, with a presentation of some of the philosophical debates underlying the choice of statistical paradigm. Key features: Provides an accessible introduction to pragmatic maximum likelihood modelling. Covers more advanced topics, including general forms of latent variable models (including non-linear and non-normal mixed-effects and state-space models) and the use of maximum likelihood variants, such as estimating equations, conditional likelihood, restricted likelihood and integrated likelihood. Adopts a practical approach, with a focus on providing the relevant tools required by researchers and practitioners who collect and analyze real data. Presents numerous examples and case studies across a wide range of applications including medicine, biology and ecology. Features applications from a range of disciplines, with implementation in R, SAS and/or ADMB. Provides all program code and software extensions on a supporting website. Confines supporting theory to the final chapters to maintain a readable and pragmatic focus of the preceding chapters. This book is not just an accessible and practical text about maximum likelihood, it is a comprehensive guide to modern maximum likelihood estimation and inference. It will be of interest to readers of all levels, from novice to expert. It will be of great benefit to researchers, and to students of statistics from senior undergraduate to graduate level. For use as a course text, exercises are provided at the end of each chapter.

Book Synopsis Maximum Likelihood Estimation and Inference by : Russell B. Millar

Download or read book Maximum Likelihood Estimation and Inference written by Russell B. Millar and published by John Wiley & Sons. This book was released on 2011-07-26 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodology, including general latent variable models and new material for the practical implementation of integrated likelihood using the free ADMB software. Fundamental issues of statistical inference are also examined, with a presentation of some of the philosophical debates underlying the choice of statistical paradigm. Key features: Provides an accessible introduction to pragmatic maximum likelihood modelling. Covers more advanced topics, including general forms of latent variable models (including non-linear and non-normal mixed-effects and state-space models) and the use of maximum likelihood variants, such as estimating equations, conditional likelihood, restricted likelihood and integrated likelihood. Adopts a practical approach, with a focus on providing the relevant tools required by researchers and practitioners who collect and analyze real data. Presents numerous examples and case studies across a wide range of applications including medicine, biology and ecology. Features applications from a range of disciplines, with implementation in R, SAS and/or ADMB. Provides all program code and software extensions on a supporting website. Confines supporting theory to the final chapters to maintain a readable and pragmatic focus of the preceding chapters. This book is not just an accessible and practical text about maximum likelihood, it is a comprehensive guide to modern maximum likelihood estimation and inference. It will be of interest to readers of all levels, from novice to expert. It will be of great benefit to researchers, and to students of statistics from senior undergraduate to graduate level. For use as a course text, exercises are provided at the end of each chapter.

Identification and Inference for Econometric Models

Author: Donald W. K. Andrews

Publisher: Cambridge University Press

Published: 2005-06-17

Total Pages: 606

ISBN-13: 9780521844413

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This 2005 collection pushed forward the research frontier in four areas of theoretical econometrics.

Book Synopsis Identification and Inference for Econometric Models by : Donald W. K. Andrews

Download or read book Identification and Inference for Econometric Models written by Donald W. K. Andrews and published by Cambridge University Press. This book was released on 2005-06-17 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 2005 collection pushed forward the research frontier in four areas of theoretical econometrics.

Econometric Foundations Pack with CD-ROM

Author: Ron Mittelhammer (Prof.)

Publisher: Cambridge University Press

Published: 2000-07-28

Total Pages: 794

ISBN-13: 9780521623940

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The text and accompanying CD-ROM develop step by step a modern approach to econometric problems. They are aimed at talented upper-level undergraduates, graduate students, and professionals wishing to acquaint themselves with the pinciples and procedures for information processing and recovery from samples of economic data. The text fully provides an operational understanding of a rich set of estimation and inference tools, including tradional likelihood based and non-traditional non-likelihood based procedures, that can be used in conjuction with the computer to address economic problems.

Book Synopsis Econometric Foundations Pack with CD-ROM by : Ron Mittelhammer (Prof.)

Download or read book Econometric Foundations Pack with CD-ROM written by Ron Mittelhammer (Prof.) and published by Cambridge University Press. This book was released on 2000-07-28 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text and accompanying CD-ROM develop step by step a modern approach to econometric problems. They are aimed at talented upper-level undergraduates, graduate students, and professionals wishing to acquaint themselves with the pinciples and procedures for information processing and recovery from samples of economic data. The text fully provides an operational understanding of a rich set of estimation and inference tools, including tradional likelihood based and non-traditional non-likelihood based procedures, that can be used in conjuction with the computer to address economic problems.

Econometric Analysis of Cross Section and Panel Data, second edition

Author: Jeffrey M. Wooldridge

Publisher: MIT Press

Published: 2010-10-01

Total Pages: 1095

ISBN-13: 0262232588

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The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.

Book Synopsis Econometric Analysis of Cross Section and Panel Data, second edition by : Jeffrey M. Wooldridge

Download or read book Econometric Analysis of Cross Section and Panel Data, second edition written by Jeffrey M. Wooldridge and published by MIT Press. This book was released on 2010-10-01 with total page 1095 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.

Estimation and Inference in Two-step Econometric Models

Author: Kevin M. Murphy

Publisher:

Published: 1984

Total Pages:

ISBN-13:

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Book Synopsis Estimation and Inference in Two-step Econometric Models by : Kevin M. Murphy

Download or read book Estimation and Inference in Two-step Econometric Models written by Kevin M. Murphy and published by . This book was released on 1984 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Causal Inference in Econometrics

Author: Van-Nam Huynh

Publisher: Springer

Published: 2015-12-28

Total Pages: 626

ISBN-13: 3319272845

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This book is devoted to the analysis of causal inference which is one of the most difficult tasks in data analysis: when two phenomena are observed to be related, it is often difficult to decide whether one of them causally influences the other one, or whether these two phenomena have a common cause. This analysis is the main focus of this volume. To get a good understanding of the causal inference, it is important to have models of economic phenomena which are as accurate as possible. Because of this need, this volume also contains papers that use non-traditional economic models, such as fuzzy models and models obtained by using neural networks and data mining techniques. It also contains papers that apply different econometric models to analyze real-life economic dependencies.

Book Synopsis Causal Inference in Econometrics by : Van-Nam Huynh

Download or read book Causal Inference in Econometrics written by Van-Nam Huynh and published by Springer. This book was released on 2015-12-28 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to the analysis of causal inference which is one of the most difficult tasks in data analysis: when two phenomena are observed to be related, it is often difficult to decide whether one of them causally influences the other one, or whether these two phenomena have a common cause. This analysis is the main focus of this volume. To get a good understanding of the causal inference, it is important to have models of economic phenomena which are as accurate as possible. Because of this need, this volume also contains papers that use non-traditional economic models, such as fuzzy models and models obtained by using neural networks and data mining techniques. It also contains papers that apply different econometric models to analyze real-life economic dependencies.