Econometric Modeling and Inference, Jean-Pierre Florens

Автор: Angrist, J.d. Pischke, Jorn-steffen
Название: Mostly harmless econometrics
ISBN: 0691120358 ISBN-13(EAN): 9780691120355
Издательство: Wiley
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Цена: 4813 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.

Автор: Brooks
Название: Introductory Econometrics for Finance
ISBN: 1107661455 ISBN-13(EAN): 9781107661455
Издательство: Cambridge Academ
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Цена: 6846 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.

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: 11686 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.

Автор: Edited by Donald W. K. Andrews
Название: Identification and Inference for Econometric Models
ISBN: 052184441X ISBN-13(EAN): 9780521844413
Издательство: Cambridge Academ
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Цена: 12461 р.
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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.

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: 21570 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.

Автор: Verbeek M
Название: A Guide to Modern Econometrics
ISBN: 1119951674 ISBN-13(EAN): 9781119951674
Издательство: Wiley
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Цена: 6874 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

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: 13421 р.
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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.

Автор: Mariano, Roberto S.
Название: Simulation-based Inference in Econometrics
ISBN: 052108802X ISBN-13(EAN): 9780521088022
Издательство: Cambridge Academ
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Цена: 4792 р.
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Описание: An overview of the techniques and practices involved in simulation-based inference.

Автор: Baum
Название: An Introduction to Modern Econometrics Using Stata
ISBN: 1597180130 ISBN-13(EAN): 9781597180139
Издательство: Taylor&Francis
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Цена: 11961 р.
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Описание: Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, this introduction illustrates how to apply econometric theories used in modern empirical research using Stata. The author emphasizes the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how to apply the theories to real data sets. The book first builds familiarity with the basic skills needed to work with econometric data in Stata before delving into the core topics, which range from the multiple linear regression model to instrumental-variables estimation.

Автор: Martin
Название: Econometric Modelling with Time Series
ISBN: 0521139813 ISBN-13(EAN): 9780521139816
Издательство: Cambridge Academ
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Цена: 8900 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, 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.

Автор: Jean-Pierre Florens
Название: Econometric Modeling and Inference
ISBN: 0521876400 ISBN-13(EAN): 9780521876407
Издательство: Cambridge Academ
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Цена: 9722 р.
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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.

Автор: Martin
Название: Econometric Modelling with Time Series
ISBN: 0521196604 ISBN-13(EAN): 9780521196604
Издательство: Cambridge Academ
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Цена: 13420 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, 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.