Identification and Inference for Econometric Models

Identification and Inference for Econometric Models PDF Author: Donald W. K. Andrews
Publisher: Cambridge University Press
ISBN: 1139444603
Category : Business & Economics
Languages : en
Pages : 589

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Book Description
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.

Identification and Inference for Econometric Models

Identification and Inference for Econometric Models PDF Author: Donald W. K. Andrews
Publisher: Cambridge University Press
ISBN: 1139444603
Category : Business & Economics
Languages : en
Pages : 589

Get Book

Book Description
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.

Identification and Inference for Econometric Models

Identification and Inference for Econometric Models PDF Author: Donald W. K. Andrews
Publisher:
ISBN: 9780511122125
Category : Econometric models
Languages : en
Pages : 573

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Book Description


Economic Modeling and Inference

Economic Modeling and Inference PDF Author: Bent Jesper Christensen
Publisher: Princeton University Press
ISBN: 1400833108
Category : Business & Economics
Languages : en
Pages : 488

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Book Description
Economic Modeling and Inference takes econometrics to a new level by demonstrating how to combine modern economic theory with the latest statistical inference methods to get the most out of economic data. This graduate-level textbook draws applications from both microeconomics and macroeconomics, paying special attention to financial and labor economics, with an emphasis throughout on what observations can tell us about stochastic dynamic models of rational optimizing behavior and equilibrium. Bent Jesper Christensen and Nicholas Kiefer show how parameters often thought estimable in applications are not identified even in simple dynamic programming models, and they investigate the roles of extensions, including measurement error, imperfect control, and random utility shocks for inference. When all implications of optimization and equilibrium are imposed in the empirical procedures, the resulting estimation problems are often nonstandard, with the estimators exhibiting nonregular asymptotic behavior such as short-ranked covariance, superconsistency, and non-Gaussianity. Christensen and Kiefer explore these properties in detail, covering areas including job search models of the labor market, asset pricing, option pricing, marketing, and retirement planning. Ideal for researchers and practitioners as well as students, Economic Modeling and Inference uses real-world data to illustrate how to derive the best results using a combination of theory and cutting-edge econometric techniques. Covers identification and estimation of dynamic programming models Treats sources of error--measurement error, random utility, and imperfect control Features financial applications including asset pricing, option pricing, and optimal hedging Describes labor applications including job search, equilibrium search, and retirement Illustrates the wide applicability of the approach using micro, macro, and marketing examples

Econometric Modeling and Inference

Econometric Modeling and Inference PDF Author: Jean-Pierre Florens
Publisher: Cambridge University Press
ISBN: 1139466771
Category : Business & Economics
Languages : en
Pages : 17

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Book Description
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

Identification and Inference for Econometric Models PDF Author: Donald W. K. Andrews
Publisher: Cambridge University Press
ISBN: 9780521844413
Category : Business & Economics
Languages : en
Pages : 606

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

Methods for Estimation and Inference in Modern Econometrics

Methods for Estimation and Inference in Modern Econometrics PDF Author: Stanislav Anatolyev
Publisher: CRC Press
ISBN: 1439838267
Category : Business & Economics
Languages : en
Pages : 230

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Book Description
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.

Simultaneous Inference in Econometric Models

Simultaneous Inference in Econometric Models PDF Author: Walter Katzenbeisser
Publisher:
ISBN: 9783445021885
Category : Econometric models
Languages : en
Pages : 127

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Book Description


Mostly Harmless Econometrics

Mostly Harmless Econometrics PDF Author: Joshua D. Angrist
Publisher: Princeton University Press
ISBN: 0691120358
Category : Business & Economics
Languages : en
Pages : 392

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Book Description
In addition to econometric essentials, this book covers important new extensions as well as how to get standard errors right. The authors explain why fancier econometric techniques are typically unnecessary and even dangerous.

Microeconometrics

Microeconometrics PDF Author: A. Colin Cameron
Publisher: Cambridge University Press
ISBN: 1139444867
Category : Business & Economics
Languages : en
Pages : 1058

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Book Description
This book provides the most comprehensive treatment to date of microeconometrics, the analysis of individual-level data on the economic behavior of individuals or firms using regression methods for cross section and panel data. The book is oriented to the practitioner. A basic understanding of the linear regression model with matrix algebra is assumed. The text can be used for a microeconometrics course, typically a second-year economics PhD course; for data-oriented applied microeconometrics field courses; and as a reference work for graduate students and applied researchers who wish to fill in gaps in their toolkit. Distinguishing features of the book include emphasis on nonlinear models and robust inference, simulation-based estimation, and problems of complex survey data. The book makes frequent use of numerical examples based on generated data to illustrate the key models and methods. More substantially, it systematically integrates into the text empirical illustrations based on seven large and exceptionally rich data sets.

Econometric Analysis of Cross Section and Panel Data, second edition

Econometric Analysis of Cross Section and Panel Data, second edition PDF Author: Jeffrey M. Wooldridge
Publisher: MIT Press
ISBN: 0262232588
Category : Business & Economics
Languages : en
Pages : 1095

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Book Description
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.