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Econometric Modeling and Inference, Jean-Pierre Florens



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Автор: Jean-Pierre Florens
Название:  Econometric Modeling and Inference   (Жан-Пьер Флоран: Экономическое моделирование и выводы из него)
Издательство: Cambridge Academ
Классификация:
Эконометрика

ISBN: 052170006X
ISBN-13(EAN): 9780521700061
ISBN: 0-521-70006-X
ISBN-13(EAN): 978-0-521-70006-1
Обложка/Формат: Paperback
Страницы: 384
Вес: 0.702 кг.
Дата издания: 02.07.2007
Серия: Themes in Modern Econometrics
Язык: English
Размер: 229 x 152 x 29
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Англии
Описание: Presents the main statistical tools of econometrics, focusing specifically on modern econometric methodology. The authors unify the approach by using a small number of estimation techniques, mainly generalized method of moments (GMM) estimation and kernel smoothing. The choice of GMM is explained by its relevance in structural econometrics and its preeminent position in econometrics overall. Split into four parts, Part I explains general methods. Part II studies statistical models that are best suited for microeconomic data. Part III deals with dynamic models that are designed for macroeconomic and financial applications. In Part IV the authors synthesize a set of problems that are specific to statistical methods in structural econometrics, namely identification and over-identification, simultaneity, and unobservability. Many theoretical examples illustrate the discussion and can be treated as application exercises. Nobel Laureate James A. Heckman offers a foreword to the work.
Дополнительное описание: Part I. Statistical Methods: 1. Statistical models; 2. Sequential models and asymptotics; 3. Estimation by maximization and by the method of moments; 4. Asymptotic tests; 5. Nonparametric methods; 6. Simulation methods; Part II. Regression Models: 7. Cond




Mostly harmless econometrics

Автор: Angrist, J.d. Pischke, Jorn-steffen
Название: Mostly harmless econometrics
ISBN: 0691120358 ISBN-13(EAN): 9780691120355
Издательство: Wiley
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Цена: 4389 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Shows how the basic tools of applied econometrics allow the data to speak. This book covers regression-discontinuity designs and quantile regression - as well as how to get standard errors right. It is suitable for various areas in contemporary social science.

Introductory Econometrics for Finance

Автор: Brooks
Название: Introductory Econometrics for Finance
ISBN: 1107661455 ISBN-13(EAN): 9781107661455
Издательство: Cambridge Academ
Рейтинг:
Цена: 5751 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This bestselling and thoroughly classroom-tested textbook is a complete resource for finance students. A comprehensive and illustrated discussion of the most common empirical approaches in finance prepares students for using econometrics in practice, while detailed case studies help them understand how the techniques are used in relevant financial contexts. Worked examples from the latest version of the popular statistical software EViews guide students to implement their own models and interpret results. Learning outcomes, key concepts and end-of-chapter review questions (with full solutions online) highlight the main chapter takeaways and allow students to self-assess their understanding. Building on the successful data- and problem-driven approach of previous editions, this third edition has been updated with new data, extensive examples and additional introductory material on mathematics, making the book more accessible to students encountering econometrics for the first time. A companion website, with numerous student and instructor resources, completes the learning package.

Methods for estimation and inference in modern econometrics

Автор: Anatolyev, Stanislav Gospodinov, Nikolay
Название: Methods for estimation and inference in modern econometrics
ISBN: 1439838240 ISBN-13(EAN): 9781439838242
Издательство: Taylor&Francis
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Цена: 9123 р.
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Описание:

Methods for Estimation and Inference in Modern Econometrics provides a comprehensive introduction to a wide range of emerging topics, such as generalized empirical likelihood estimation and alternative asymptotics under drifting parameterizations, which have not been discussed in detail outside of highly technical research papers. The book also addresses several problems often arising in the analysis of economic data, including weak identification, model misspecification, and possible nonstationarity. The book's appendix provides a review of some basic concepts and results from linear algebra, probability theory, and statistics that are used throughout the book.





Topics covered include:







  • Well-established nonparametric and parametric approaches to estimation and conventional (asymptotic and bootstrap) frameworks for statistical inference


  • Estimation of models based on moment restrictions implied by economic theory, including various method-of-moments estimators for unconditional and conditional moment restriction models, and asymptotic theory for correctly specified and misspecified models


  • Non-conventional asymptotic tools that lead to improved finite sample inference, such as higher-order asymptotic analysis that allows for more accurate approximations via various asymptotic expansions, and asymptotic approximations based on drifting parameter sequences






Offering a unified approach to studying econometric problems, Methods for Estimation and Inference in Modern Econometrics links most of the existing estimation and inference methods in a general framework to help readers synthesize all aspects of modern econometric theory. Various theoretical exercises and suggested solutions are included to facilitate understanding.

Econometric Modeling and Inference

Автор: Jean-Pierre Florens
Название: Econometric Modeling and Inference
ISBN: 0521876400 ISBN-13(EAN): 9780521876407
Издательство: Cambridge Academ
Рейтинг:
Цена: 9087 р.
Наличие на складе: Поставка под заказ.

Описание: Presents the main statistical tools of econometrics, focusing specifically on modern econometric methodology. The authors unify the approach by using a small number of estimation techniques, mainly generalized method of moments (GMM) estimation and kernel smoothing. The choice of GMM is explained by its relevance in structural econometrics and its preeminent position in econometrics overall. Split into four parts, Part I explains general methods. Part II studies statistical models that are best suited for microeconomic data. Part III deals with dynamic models that are designed for macroeconomic and financial applications. In Part IV the authors synthesize a set of problems that are specific to statistical methods in structural econometrics, namely identification and over-identification, simultaneity, and unobservability. Many theoretical examples illustrate the discussion and can be treated as application exercises. Nobel Laureate James A. Heckman offers a foreword to the work.

Identification and Inference for Econometric Models

Автор: Edited by Donald W. K. Andrews
Название: Identification and Inference for Econometric Models
ISBN: 052184441X ISBN-13(EAN): 9780521844413
Издательство: Cambridge Academ
Рейтинг:
Цена: 9433 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This volume contains the papers presented in honor of the lifelong achievements of Thomas J. Rothenberg on the occasion of his retirement. The authors of the chapters include many of the leading econometricians of our day, and the chapters address topics of current research significance in econometric theory. The chapters cover four themes: identification and efficient estimation in econometrics, asymptotic approximations to the distributions of econometric estimators and tests, inference involving potentially nonstationary time series, such as processes that might have a unit autoregressive root, and nonparametric and semiparametric inference. Several of the chapters provide overviews and treatments of basic conceptual issues, while others advance our understanding of the properties of existing econometric procedures and/or propose new ones. Specific topics include identification in nonlinear models, inference with weak instruments, tests for nonstationary in time series and panel data, generalized empirical likelihood estimation, and the bootstrap.

Identification and Inference for Econometric Models

Автор: Andrews
Название: Identification and Inference for Econometric Models
ISBN: 052115474X ISBN-13(EAN): 9780521154741
Издательство: Cambridge Academ
Рейтинг:
Цена: 4945 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This 2005 volume contains the papers presented in honor of the lifelong achievements of Thomas J. Rothenberg on the occasion of his retirement. The authors of the chapters include many of the leading econometricians of our day, and the chapters address topics of current research significance in econometric theory. The chapters cover four themes: identification and efficient estimation in econometrics, asymptotic approximations to the distributions of econometric estimators and tests, inference involving potentially nonstationary time series, such as processes that might have a unit autoregressive root, and nonparametric and semiparametric inference. Several of the chapters provide overviews and treatments of basic conceptual issues, while others advance our understanding of the properties of existing econometric procedures and/or propose others. Specific topics include identification in nonlinear models, inference with weak instruments, tests for nonstationary in time series and panel data, generalized empirical likelihood estimation, and the bootstrap.

Simulation-based Inference in Econometrics

Автор: Edited by Roberto Mariano
Название: Simulation-based Inference in Econometrics
ISBN: 0521591120 ISBN-13(EAN): 9780521591126
Издательство: Cambridge Academ
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Цена: 10699 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: 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.

Dynamic Econometric Modeling

Автор: Edited by William A. Barnett
Название: Dynamic Econometric Modeling
ISBN: 0521023408 ISBN-13(EAN): 9780521023405
Издательство: Cambridge Academ
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Цена: 4600 р.
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Описание: This book brings together presentations of some of the fundamental new research that has begun to appear in the areas of dynamic structural modeling, nonlinear structural modeling, time series modeling, nonparametric inference, and chaotic attractor inference. The contents of this volume comprise the proceedings of the third of a conference series entitled International Symposia in Economic Theory and Econometrics. This conference was held at the IC;s2 (Innovation, Creativity and Capital) Institute at the University of Texas at Austin on May 22-23, l986.

Econometric Modelling with Time Series

Автор: Martin
Название: Econometric Modelling with Time Series
ISBN: 0521196604 ISBN-13(EAN): 9780521196604
Издательство: Cambridge Academ
Рейтинг:
Цена: 12539 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book provides a general framework for specifying, estimating and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalized method of moments estimation, nonparametric estimation and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.

Econometric Modelling with Time Series

Автор: Martin
Название: Econometric Modelling with Time Series
ISBN: 0521139813 ISBN-13(EAN): 9780521139816
Издательство: Cambridge Academ
Рейтинг:
Цена: 7246 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book provides a general framework for specifying, estimating and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalized method of moments estimation, nonparametric estimation and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.

Nonlinear Econometric Modeling in Time Series

Автор: Edited by William A. Barnett
Название: Nonlinear Econometric Modeling in Time Series
ISBN: 052102868X ISBN-13(EAN): 9780521028684
Издательство: Cambridge Academ
Рейтинг:
Цена: 4140 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Nonlinear Econometric Modeling in Time Series presents the more recent literature on nonlinear time series. Specific topics covered with respect to nonlinearity include cointegration tests, risk-related asymmetries, structural breaks and outliers, Bayesian analysis with a threshold, consistency and asymptotic normality, asymptotic inference and error-correction models. With a world-class panel of contributors, this volume addresses topics with major applications for fields such as foreign-exchange markets and interest rate analysis. Eleventh in this series of international symposia, this volume is also part of the European Conference Series in Quantitative Economics and Econometrics (EC)2.

Bayesian Inference in Dynamic Econometric Models

Автор: Bauwens, Luc;Lubrano, Michel;Richard, Jean-Francoi
Название: Bayesian Inference in Dynamic Econometric Models
ISBN: 0198773129 ISBN-13(EAN): 9780198773122
Издательство: Oxford Academ
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Цена: 17256 р.
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Описание: This work contains an up-to-date coverage of the last 20 years' advances in Bayesian inference in econometrics, with an emphasis on dynamic models. Several examples illustrate the methods.


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