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Econometric Modeling and Inference, Jean-Pierre Florens



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Автор: Jean-Pierre Florens
Название:  Econometric Modeling and Inference
Перевод названия: Жан-Пьер Флоран: Экономическое моделирование и выводы из него
ISBN: 9780521700061
Издательство: Cambridge Academ
Классификация:
ISBN-10: 052170006X
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
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Поставляется из: Англии
Описание: For over 20 years, James Herriot has captivated millions of readers and viewers with his tales of the triumphs, disasters, pride and heartache that filled his life as a vet in the Yorkshire Dales. Once again the storytelling magic shines through in this long-awaited addition to the series. A major lead title backed by advertising in four major daily newspapers and colour ads in Radio Times and selected magazines. BA CATALOGUE.



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: 7128 р.
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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.

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: 14083 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 Modelling with Time Series

Автор: Martin
Название: Econometric Modelling with Time Series
ISBN: 0521196604 ISBN-13(EAN): 9780521196604
Издательство: Cambridge Academ
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Цена: 15838 р.
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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, generalised method of moments estimation, nonparametric estimation and estimation by simulation.

Econometric Modelling with Time Series

Автор: Martin
Название: Econometric Modelling with Time Series
ISBN: 0521139813 ISBN-13(EAN): 9780521139816
Издательство: Cambridge Academ
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Цена: 11245 р.
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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, generalised method of moments estimation, nonparametric estimation and estimation by simulation.

Applied Nonparametric Econometrics

Автор: Henderson
Название: Applied Nonparametric Econometrics
ISBN: 0521279682 ISBN-13(EAN): 9780521279680
Издательство: Cambridge Academ
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Цена: 6334 р.
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Описание: The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignore the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians, discussing basic to advanced nonparametric methods with applications.

A Guide to Modern Econometrics

Автор: Verbeek M
Название: A Guide to Modern Econometrics
ISBN: 1119951674 ISBN-13(EAN): 9781119951674
Издательство: Wiley
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Цена: 7918 р.
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Описание: This highly successful text serves as a guide to alternative techniques in econometrics with an emphasis on the practical application of these approaches. The 4th Edition features: Coverage of a wide range of topics, including time series analysis, cointegration, limited dependent variables, panel data analysis and the generalized method of moments. Intuitive presentation and discussion, with a focus on implementation and practical relevance. A large number of empirical illustrations taken from a wide variety of fields, including international economics, finance, labour economics and macroeconomics. Increased focus on robust inference and small sample properties. End-of-chapter exercises, both theoretical and empirical, reviewing key concepts. Updated and expanded coverage, on various topics such as missing data, outliers, forecast evaluation, the estimation of treatment effects and panel unit root tests. Supplementary material, including PowerPoint slides for lecturers, data sets of the empirical illustrations and exercises, and solutions to selected exercises in each chapter, available at www.wileyeurope.com/college/verbeek

An Introduction to Modern Econometrics Using Stata

Автор: Baum
Название: An Introduction to Modern Econometrics Using Stata
ISBN: 1597180130 ISBN-13(EAN): 9781597180139
Издательство: Taylor&Francis
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Цена: 12631 р.
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Описание:

Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, An Introduction to Modern Econometrics Using Stata focuses on the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how the theories are applied to real data sets using Stata.

As an expert in Stata, the author successfully guides readers from the basic elements of Stata to the core econometric topics. He first describes the fundamental components needed to effectively use Stata. The book then covers the multiple linear regression model, linear and nonlinear Wald tests, constrained least-squares estimation, Lagrange multiplier tests, and hypothesis testing of nonnested models. Subsequent chapters center on the consequences of failures of the linear regression model's assumptions. The book also examines indicator variables, interaction effects, weak instruments, underidentification, and generalized method-of-moments estimation. The final chapters introduce panel-data analysis and discrete- and limited-dependent variables and the two appendices discuss how to import data into Stata and Stata programming.

Presenting many of the econometric theories used in modern empirical research, this introduction illustrates how to apply these concepts using Stata. The book serves both as a supplementary text for undergraduate and graduate students and as a clear guide for economists and financial analysts.

Simulation-based Inference in Econometrics

Автор: Mariano, Roberto S.
Название: Simulation-based Inference in Econometrics
ISBN: 052108802X ISBN-13(EAN): 9780521088022
Издательство: Cambridge Academ
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Цена: 6651 р.
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Описание: Simulation-based inference (SBI) is the fastest growing area of research in modern econometrics. This substantial international volume provides an overview of the applications and techniques at the cutting edge of the subject as well as providing a comprehensive survey of the existing literature.

Econometric Analysis of Panel Data

Автор: Baltagi Badi H
Название: Econometric Analysis of Panel Data
ISBN: 1118672321 ISBN-13(EAN): 9781118672327
Издательство: Wiley
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Цена: 8077 р.
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Описание: Panel data econometrics has evolved rapidly over the last decade. Micro and Macro panels are increasing in numbers and availability and methods to deal with these data are in high demand from practitioners.

Introductory Econometrics for Finance

Автор: Brooks
Название: Introductory Econometrics for Finance
ISBN: 1107661455 ISBN-13(EAN): 9781107661455
Издательство: Cambridge Academ
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Цена: 7918 р.
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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.


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