Estimation, Inference and Specification Analysis

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Publisher : Cambridge University Press
ISBN 13 : 9780521574464
Total Pages : 396 pages
Book Rating : 4.5/5 (744 download)

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Book Synopsis Estimation, Inference and Specification Analysis by : Halbert White

Download or read book Estimation, Inference and Specification Analysis written by Halbert White and published by Cambridge University Press. This book was released on 1996-06-28 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the consequences of misspecifications for the interpretation of likelihood-based methods of statistical estimation and interference. The analysis concludes with an examination of methods by which the possibility of misspecification can be empirically investigated.

Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis

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Publisher : Springer Science & Business Media
ISBN 13 : 1461416531
Total Pages : 582 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis by : Xiaohong Chen

Download or read book Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis written by Xiaohong Chen and published by Springer Science & Business Media. This book was released on 2012-08-01 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of articles that present the most recent cutting edge results on specification and estimation of economic models written by a number of the world’s foremost leaders in the fields of theoretical and methodological econometrics. Recent advances in asymptotic approximation theory, including the use of higher order asymptotics for things like estimator bias correction, and the use of various expansion and other theoretical tools for the development of bootstrap techniques designed for implementation when carrying out inference are at the forefront of theoretical development in the field of econometrics. One important feature of these advances in the theory of econometrics is that they are being seamlessly and almost immediately incorporated into the “empirical toolbox” that applied practitioners use when actually constructing models using data, for the purposes of both prediction and policy analysis and the more theoretically targeted chapters in the book will discuss these developments. Turning now to empirical methodology, chapters on prediction methodology will focus on macroeconomic and financial applications, such as the construction of diffusion index models for forecasting with very large numbers of variables, and the construction of data samples that result in optimal predictive accuracy tests when comparing alternative prediction models. Chapters carefully outline how applied practitioners can correctly implement the latest theoretical refinements in model specification in order to “build” the best models using large-scale and traditional datasets, making the book of interest to a broad readership of economists from theoretical econometricians to applied economic practitioners.

Estimation, Interference and Specification Analysis

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Publisher :
ISBN 13 :
Total Pages : 380 pages
Book Rating : 4.:/5 (118 download)

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Book Synopsis Estimation, Interference and Specification Analysis by : Halbert White

Download or read book Estimation, Interference and Specification Analysis written by Halbert White and published by . This book was released on 1994 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Maximum Likelihood Estimation of Misspecified Models

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Publisher : Elsevier
ISBN 13 : 9780762310753
Total Pages : 280 pages
Book Rating : 4.3/5 (17 download)

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Book Synopsis Maximum Likelihood Estimation of Misspecified Models by : T. Fomby

Download or read book Maximum Likelihood Estimation of Misspecified Models written by T. Fomby and published by Elsevier. This book was released on 2003-12-12 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comparative study of pure and pretest estimators for a possibly misspecified two-way error component model / Badi H. Baltagi, Georges Bresson, Alain Pirotte -- Estimation, inference, and specification testing for possibly misspecified quantile regression / Tae-Hwan Kim, Halbert White -- Quasimaximum likelihood estimation with bounded symmetric errors / Douglas Miller, James Eales, Paul Preckel -- Consistent quasi-maximum likelihood estimation with limited information / Douglas Miller, Sang-Hak Lee -- An examination of the sign and volatility switching arch models under alternative distributional assumptions / Mohamed F. Omran, Florin Avram -- estimating a linear exponential density when the weighting matrix and mean parameter vector are functionally related / Chor-yiu Sin -- Testing in GMM models without truncation / Timothy J. Vogelsang -- Bayesian analysis of misspecified models with fixed effects / Tiemen Woutersen -- Tests of common deterministic trend slopes applied to quarterly global temperature data / Thomas B. Fomby, Timothy J. Vogelsang -- The sandwich estimate of variance / James W. Hardin -- Test statistics and critical values in selectivity models / R. Carter Hill, Lee C. Adkins, Keith A. Bender -- Introduction / Thomas B Fomby, R. Carter Hill.

Econometric Analysis

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Publisher : Simon & Schuster Books For Young Readers
ISBN 13 :
Total Pages : 832 pages
Book Rating : 4.:/5 (321 download)

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Book Synopsis Econometric Analysis by : William H. Greene

Download or read book Econometric Analysis written by William H. Greene and published by Simon & Schuster Books For Young Readers. This book was released on 1993 with total page 832 pages. Available in PDF, EPUB and Kindle. Book excerpt: Matrix algebra; Probability abd distribution theory; Statistical inference; Computation and optimization; The classical multiple linear regression model - specification and estimation; Inference and prediction; Functional form, nonlinearity, and specification; Data problems; Nonlinear regression models; Nonspherical disturbances; generalized regression, and GMM estimation; Autocorrelated disturbances; Models for panel data; Systems of regression equations; Regressions with lagged variables; Time-series models; Models with discrete dependent variables; Limited dependent variable and duration models.

Topics in Advanced Econometrics

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Publisher : Cambridge University Press
ISBN 13 : 9780521565110
Total Pages : 274 pages
Book Rating : 4.5/5 (651 download)

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Book Synopsis Topics in Advanced Econometrics by : Herman J. Bierens

Download or read book Topics in Advanced Econometrics written by Herman J. Bierens and published by Cambridge University Press. This book was released on 1996-02-23 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: A rigorous treatment of a number of timely topics in advanced econometrics.

Estimation, Inference, and Specification Testing for Possibly Misspecified Quantile Regression

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Publisher :
ISBN 13 :
Total Pages : 33 pages
Book Rating : 4.:/5 (248 download)

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Book Synopsis Estimation, Inference, and Specification Testing for Possibly Misspecified Quantile Regression by : Tae-Hwan Kim

Download or read book Estimation, Inference, and Specification Testing for Possibly Misspecified Quantile Regression written by Tae-Hwan Kim and published by . This book was released on 2002 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Econometric Modeling and Inference

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Publisher : Cambridge University Press
ISBN 13 : 1139466771
Total Pages : 17 pages
Book Rating : 4.1/5 (394 download)

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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 and published by Cambridge University Press. This book was released on 2007-07-02 with total page 17 pages. 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.

Handbook Of Applied Econometrics And Statistical Inference

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Publisher : CRC Press
ISBN 13 : 0203911075
Total Pages : 744 pages
Book Rating : 4.2/5 (39 download)

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Book Synopsis Handbook Of Applied Econometrics And Statistical Inference by : Aman Ullah

Download or read book Handbook Of Applied Econometrics And Statistical Inference written by Aman Ullah and published by CRC Press. This book was released on 2002-01-29 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summarizing developments and techniques in the field, this reference covers sample surveys, nonparametric analysis, hypothesis testing, time series analysis, Bayesian inference, and distribution theory for applications in statistics, economics, medicine, biology, engineering, sociology, psychology, and information technology. It supplies a geometric proof of an extended Gauss-Markov theorem, approaches for the design and implementation of sample surveys, advances in the theory of Neyman's smooth test, and methods for pre-test and biased estimation. It includes discussions ofsample size requirements for estimation in SUR models, innovative developments in nonparametric models, and more.

Generalized Method of Moments

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Publisher : OUP Oxford
ISBN 13 : 0191513938
Total Pages : 412 pages
Book Rating : 4.1/5 (915 download)

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Book Synopsis Generalized Method of Moments by : Alastair R. Hall

Download or read book Generalized Method of Moments written by Alastair R. Hall and published by OUP Oxford. This book was released on 2004-12-23 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generalized Method of Moments (GMM) has become one of the main statistical tools for the analysis of economic and financial data. This book is the first to provide an intuitive introduction to the method combined with a unified treatment of GMM statistical theory and a survey of recent important developments in the field. Providing a comprehensive treatment of GMM estimation and inference, it is designed as a resource for both the theory and practice of GMM: it discusses and proves formally all the main statistical results, and illustrates all inference techniques using empirical examples in macroeconomics and finance. Building from the instrumental variables estimator in static linear models, it presents the asymptotic statistical theory of GMM in nonlinear dynamic models. Within this framework it covers classical results on estimation and inference techniques, such as the overidentifying restrictions test and tests of structural stability, and reviews the finite sample performance of these inference methods. And it discusses in detail recent developments on covariance matrix estimation, the impact of model misspecification, moment selection, the use of the bootstrap, and weak instrument asymptotics.

Seemingly Unrelated Regression Equations Models

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Publisher : CRC Press
ISBN 13 : 1000148939
Total Pages : 398 pages
Book Rating : 4.0/5 (1 download)

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Book Synopsis Seemingly Unrelated Regression Equations Models by : Virendera K. Srivastava

Download or read book Seemingly Unrelated Regression Equations Models written by Virendera K. Srivastava and published by CRC Press. This book was released on 2020-08-14 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together the scattered literature associated with the seemingly unrelated regression equations (SURE) model used by econometricians and others. It focuses on the theoretical statistical results associated with the SURE model.

Casual Analysis Using Two-part Models

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Publisher :
ISBN 13 :
Total Pages : 160 pages
Book Rating : 4.:/5 (15 download)

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Book Synopsis Casual Analysis Using Two-part Models by : Zhuang Hao

Download or read book Casual Analysis Using Two-part Models written by Zhuang Hao and published by . This book was released on 2018 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-part model (2PM) is the most widely applied modeling and estimation framework in empirical health economics. By design, the two-part model allows the process governing observation at zero to systematically differ from that which determines non-zero observations. The former is commonly referred to as the extensive margin (EM) and the latter is called the intensive margin (IM). The analytic focus of my dissertation is on the development of a general framework for specifying, estimating and drawing inference regarding causally interpretable (CI) effect parameters in the 2PM context. Our proposed fully parametric 2PM (FP2PM) framework comprises very flexible versions of the EM and IM for both continuous and count-valued outcome models and encompasses all implementations of the 2PM found in the literature. Because our modeling approach is potential outcomes (PO) based, it provides a context for clear definition of targeted counterfactual CI parameters of interest. This PO basis also provides a context for identifying the conditions under which such parameters can be consistently estimated using the observable data (via the appropriately specified data generating process). These conditions also ensure that the estimation results are CI. There is substantial literature on statistical testing for model selection in the 2PM context, yet there has been virtually no attention paid to testing the "one-part" null hypothesis. Within our general modeling and estimation framework, we devise a relatively simple test of that null for both continuous and count-valued outcomes. We illustrate our proposed model, method and testing protocol in the context of estimating price effects on the demand for alcohol.

Specification Searches

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Publisher :
ISBN 13 :
Total Pages : 392 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Specification Searches by : E. E. Leamer

Download or read book Specification Searches written by E. E. Leamer and published by . This book was released on 1978-04-24 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offers a radically new approach to inference with nonexperimental data when the statistical model is ambiguously defined. Examines the process of model searching and its implications for inference. Identifies six different varieties of specification searches, discussing the inferential consequences of each in detail.

Specification Analysis and Instrumental Variables Estimation

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Publisher :
ISBN 13 : 9780867465136
Total Pages : 17 pages
Book Rating : 4.4/5 (651 download)

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Book Synopsis Specification Analysis and Instrumental Variables Estimation by : David E. A. Giles

Download or read book Specification Analysis and Instrumental Variables Estimation written by David E. A. Giles and published by . This book was released on 1983 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Applied Time Series Analysis for the Social Sciences

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Publisher : Wiley
ISBN 13 : 9780470749937
Total Pages : 0 pages
Book Rating : 4.7/5 (499 download)

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Book Synopsis Applied Time Series Analysis for the Social Sciences by : Regina Baker

Download or read book Applied Time Series Analysis for the Social Sciences written by Regina Baker and published by Wiley. This book was released on 2024-06-04 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore this indispensable and comprehensive guide to time series analysis for students and practitioners in a wide variety of disciplines Applied Time Series Analysis for the Social Sciences: Specification, Estimation, and Inference delivers an accessible guide to time series analysis that includes both theory and practice. The coverage spans developments from ARIMA intervention models and generalized least squares to the London School of Economics (LSE) approach and vector autoregression. Designed to break difficult concepts into manageable pieces while offering plenty of examples and exercises, the author demonstrates the use of lag operator algebra throughout to provide a better understanding of dynamic specification and the connections between model specifications that appear to be more different than they are. The book is ideal for those with minimal mathematical experience, intended to follow a course in multiple regression, and includes exercises designed to build general skills such as mathematical expectation calculations to derive means and variances. Readers will also benefit from the inclusion of: A focus on social science applications and a mix of theory and detailed examples provided throughout An accompanying website with data sets and examples in Stata, SAS and R A simplified unit root testing strategy based on recent developments An examination of various uses and interpretations of lagged dependent variables and the common pitfalls students and researchers face in this area An introduction to LSE methodology such as the COMFAC critique, general-to-specific modeling, and the use of forecasting to evaluate and test models Perfect for students and professional researchers in the political sciences, public policy, sociology, and economics, Applied Time Series Analysis for the Social Sciences: Specification, Estimation, and Inference will also earn a place in the libraries of post graduate students and researchers in public health, public administration and policy, and education.

Handbook of Econometrics

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Publisher : Elsevier
ISBN 13 : 0080556558
Total Pages : 1057 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Handbook of Econometrics by : James J. Heckman

Download or read book Handbook of Econometrics written by James J. Heckman and published by Elsevier. This book was released on 2007-12-14 with total page 1057 pages. Available in PDF, EPUB and Kindle. Book excerpt: As conceived by the founders of the Econometric Society, econometrics is a field that uses economic theory and statistical methods to address empirical problems in economics. It is a tool for empirical discovery and policy analysis. The chapters in this volume embody this vision and either implement it directly or provide the tools for doing so. This vision is not shared by those who view econometrics as a branch of statistics rather than as a distinct field of knowledge that designs methods of inference from data based on models of human choice behavior and social interactions. All of the essays in this volume and its companion volume 6A offer guidance to the practitioner on how to apply the methods they discuss to interpret economic data. The authors of the chapters are all leading scholars in the fields they survey and extend.Handbook of Econometrics is now available online at ScienceDirect — full-text online from volume 1 onwards. *Part of the renowned Handbooks in Economics Series *Updates and expands the exisiting Handbook of Econometrics volumes *An invaluable reference written by some of the world's leading econometricians.

Statistical Machine Learning

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Publisher : CRC Press
ISBN 13 : 1351051490
Total Pages : 525 pages
Book Rating : 4.3/5 (51 download)

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Book Synopsis Statistical Machine Learning by : Richard Golden

Download or read book Statistical Machine Learning written by Richard Golden and published by CRC Press. This book was released on 2020-06-24 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent rapid growth in the variety and complexity of new machine learning architectures requires the development of improved methods for designing, analyzing, evaluating, and communicating machine learning technologies. Statistical Machine Learning: A Unified Framework provides students, engineers, and scientists with tools from mathematical statistics and nonlinear optimization theory to become experts in the field of machine learning. In particular, the material in this text directly supports the mathematical analysis and design of old, new, and not-yet-invented nonlinear high-dimensional machine learning algorithms. Features: Unified empirical risk minimization framework supports rigorous mathematical analyses of widely used supervised, unsupervised, and reinforcement machine learning algorithms Matrix calculus methods for supporting machine learning analysis and design applications Explicit conditions for ensuring convergence of adaptive, batch, minibatch, MCEM, and MCMC learning algorithms that minimize both unimodal and multimodal objective functions Explicit conditions for characterizing asymptotic properties of M-estimators and model selection criteria such as AIC and BIC in the presence of possible model misspecification This advanced text is suitable for graduate students or highly motivated undergraduate students in statistics, computer science, electrical engineering, and applied mathematics. The text is self-contained and only assumes knowledge of lower-division linear algebra and upper-division probability theory. Students, professional engineers, and multidisciplinary scientists possessing these minimal prerequisites will find this text challenging yet accessible. About the Author: Richard M. Golden (Ph.D., M.S.E.E., B.S.E.E.) is Professor of Cognitive Science and Participating Faculty Member in Electrical Engineering at the University of Texas at Dallas. Dr. Golden has published articles and given talks at scientific conferences on a wide range of topics in the fields of both statistics and machine learning over the past three decades. His long-term research interests include identifying conditions for the convergence of deterministic and stochastic machine learning algorithms and investigating estimation and inference in the presence of possibly misspecified probability models.