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Economic Modeling and Inference

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Release : 2009
Genre : Business & Economics
Kind : eBook
Book Rating : 591/5 ( reviews)

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Book Synopsis Economic Modeling and Inference by : Bent Jesper Christensen

Download or read book Economic Modeling and Inference written by Bent Jesper Christensen. This book was released on 2009. Available in PDF, EPUB and Kindle. Book excerpt: 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

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Release : 2007-07-02
Genre : Business & Economics
Kind : eBook
Book Rating : 771/5 ( reviews)

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Book Synopsis Econometric Modeling and Inference by : Jean-Pierre Florens

Download or read book Econometric Modeling and Inference written by Jean-Pierre Florens. This book was released on 2007-07-02. Available in PDF, EPUB and Kindle. Book excerpt: 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

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Release : 2005-06-17
Genre : Business & Economics
Kind : eBook
Book Rating : 413/5 ( reviews)

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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. This book was released on 2005-06-17. Available in PDF, EPUB and Kindle. Book excerpt: This 2005 collection pushed forward the research frontier in four areas of theoretical econometrics.

Methods for Estimation and Inference in Modern Econometrics

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Release : 2011-06-07
Genre : Business & Economics
Kind : eBook
Book Rating : 267/5 ( reviews)

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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. This book was released on 2011-06-07. 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.

Bayesian Inference in Dynamic Econometric Models

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Release : 2000-01-06
Genre : Business & Economics
Kind : eBook
Book Rating : 466/5 ( reviews)

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Book Synopsis Bayesian Inference in Dynamic Econometric Models by : Luc Bauwens

Download or read book Bayesian Inference in Dynamic Econometric Models written by Luc Bauwens. This book was released on 2000-01-06. Available in PDF, EPUB and Kindle. Book excerpt: This book contains an up-to-date coverage of the last twenty years advances in Bayesian inference in econometrics, with an emphasis on dynamic models. It shows how to treat Bayesian inference in non linear models, by integrating the useful developments of numerical integration techniques based on simulations (such as Markov Chain Monte Carlo methods), and the long available analytical results of Bayesian inference for linear regression models. It thus covers a broad range of rather recent models for economic time series, such as non linear models, autoregressive conditional heteroskedastic regressions, and cointegrated vector autoregressive models. It contains also an extensive chapter on unit root inference from the Bayesian viewpoint. Several examples illustrate the methods.

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