Bayesian and Likelihood Methods in Statistics and Econometrics
Author: Seymour Geisser
Publisher: North Holland
Published: 1990
Total Pages: 520
ISBN-13:
DOWNLOAD EBOOK →On Bayesian econometrics
Lanterna Rally
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Contemporary Bayesian Econometrics and Statistics
Author: John Geweke
Publisher: John Wiley & Sons
Published: 2005-10-03
Total Pages: 322
ISBN-13: 0471744727
DOWNLOAD EBOOK →Tools to improve decision making in an imperfect world This publication provides readers with a thorough understanding of Bayesian analysis that is grounded in the theory of inference and optimal decision making. Contemporary Bayesian Econometrics and Statistics provides readers with state-of-the-art simulation methods and models that are used to solve complex real-world problems. Armed with a strong foundation in both theory and practical problem-solving tools, readers discover how to optimize decision making when faced with problems that involve limited or imperfect data. The book begins by examining the theoretical and mathematical foundations of Bayesian statistics to help readers understand how and why it is used in problem solving. The author then describes how modern simulation methods make Bayesian approaches practical using widely available mathematical applications software. In addition, the author details how models can be applied to specific problems, including: * Linear models and policy choices * Modeling with latent variables and missing data * Time series models and prediction * Comparison and evaluation of models The publication has been developed and fine- tuned through a decade of classroom experience, and readers will find the author's approach very engaging and accessible. There are nearly 200 examples and exercises to help readers see how effective use of Bayesian statistics enables them to make optimal decisions. MATLAB? and R computer programs are integrated throughout the book. An accompanying Web site provides readers with computer code for many examples and datasets. This publication is tailored for research professionals who use econometrics and similar statistical methods in their work. With its emphasis on practical problem solving and extensive use of examples and exercises, this is also an excellent textbook for graduate-level students in a broad range of fields, including economics, statistics, the social sciences, business, and public policy.
Bayesian Analysis in Statistics and Econometrics
Author: Donald A. Berry
Publisher: John Wiley & Sons
Published: 1996
Total Pages: 610
ISBN-13: 9780471118565
DOWNLOAD EBOOK →This book is a definitive work that captures the current state of knowledge of Bayesian Analysis in Statistics and Econometrics and attempts to move it forward. It covers such topics as foundations, forecasting inferential matters, regression, computation and applications.
Computational Methods in Statistics and Econometrics
Author: Hisashi Tanizaki
Publisher: CRC Press
Published: 2004-01-21
Total Pages: 538
ISBN-13: 9780203022023
DOWNLOAD EBOOK →Reflecting current technological capacities and analytical trends, Computational Methods in Statistics and Econometrics showcases Monte Carlo and nonparametric statistical methods for models, simulations, analyses, and interpretations of statistical and econometric data. The author explores applications of Monte Carlo methods in Bayesian estimation, state space modeling, and bias correction of ordinary least squares in autoregressive models. The book offers straightforward explanations of mathematical concepts, hundreds of figures and tables, and a range of empirical examples. A CD-ROM packaged with the book contains all of the source codes used in the text.
Bayesian Econometric Methods
Author: Joshua Chan
Publisher: Cambridge University Press
Published: 2019-08-15
Total Pages: 491
ISBN-13: 1108423388
DOWNLOAD EBOOK →Illustrates Bayesian theory and application through a series of exercises in question and answer format.
The Oxford Handbook of Bayesian Econometrics
Author: John Geweke
Publisher: Oxford University Press, USA
Published: 2011-09-29
Total Pages: 571
ISBN-13: 0199559082
DOWNLOAD EBOOK →A broad coverage of the application of Bayesian econometrics in the major fields of economics and related disciplines, including macroeconomics, microeconomics, finance, and marketing.
Bayesian Econometrics
Author: Gary Koop
Publisher: Wiley-Interscience
Published: 2003
Total Pages: 382
ISBN-13:
DOWNLOAD EBOOK →Researchers in many fields are increasingly finding the Bayesian approach to statistics to be an attractive one. This book introduces the reader to the use of Bayesian methods in the field of econometrics at the advanced undergraduate or graduate level. The book is self-contained and does not require that readers have previous training in econometrics. The focus is on models used by applied economists and the computational techniques necessary to implement Bayesian methods when doing empirical work. Topics covered in the book include the regression model (and variants applicable for use with panel data), time series models, models for qualitative or censored data, nonparametric methods and Bayesian model averaging. The book includes numerous empirical examples and the website associated with it contains data sets and computer programs to help the student develop the computational skills of modern Bayesian econometrics.
Statistics and Econometric Models
Author: Christian Gourieroux
Publisher: Cambridge University Press
Published: 1995-10-26
Total Pages: 528
ISBN-13: 9780521477444
DOWNLOAD EBOOK →This is the first volume in a major two-volume set of advanced texts in econometrics.
Intermediate Statistics and Econometrics
Author: Dale J. Poirier
Publisher: MIT Press
Published: 1995
Total Pages: 744
ISBN-13: 9780262161497
DOWNLOAD EBOOK →The standard introductory texts to mathematical statistics leave the Bayesian approach to be taught later in advanced topics courses-giving students the impression that Bayesian statistics provide but a few techniques appropriate in only special circumstances. Nothing could be further from the truth, argues Dale Poirier, who has developed a course for teaching comparatively both the classical and the Bayesian approaches to econometrics. Poirier's text provides a thoroughly modern, self-contained, comprehensive, and accessible treatment of the probability and statistical foundations of econometrics with special emphasis on the linear regression model. Written primarily for advanced undergraduate and graduate students who are pursuing research careers in economics, Intermediate Statistics and Econometrics offers a broad perspective, bringing together a great deal of diverse material. Its comparative approach, emphasis on regression and prediction, and numerous exercises and references provide a solid foundation for subsequent courses in econometrics and will prove a valuable resource to many nonspecialists who want to update their quantitative skills. The introduction closes with an example of a real-world data set-the Challengerspace shuttle disaster-that motivates much of the text's theoretical discussion. The ten chapters that follow cover basic concepts, special distributions, distributions of functions of random variables, sampling theory, estimation, hypothesis testing, prediction, and the linear regression model. Appendixes contain a review of matrix algebra, computation, and statistical tables.
Introduction to Bayesian Econometrics
Author: Edward Greenberg
Publisher: Cambridge University Press
Published: 2013
Total Pages: 271
ISBN-13: 1107015316
DOWNLOAD EBOOK →This textbook explains the basic ideas of subjective probability and shows how subjective probabilities must obey the usual rules of probability to ensure coherency. It defines the likelihood function, prior distributions and posterior distributions. It explains how posterior distributions are the basis for inference and explores their basic properties. Various methods of specifying prior distributions are considered, with special emphasis on subject-matter considerations and exchange ability. The regression model is examined to show how analytical methods may fail in the derivation of marginal posterior distributions. The remainder of the book is concerned with applications of the theory to important models that are used in economics, political science, biostatistics and other applied fields. New to the second edition is a chapter on semiparametric regression and new sections on the ordinal probit, item response, factor analysis, ARCH-GARCH and stochastic volatility models. The new edition also emphasizes the R programming language.
