Contemporary Bayesian Econometrics And Statistics
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Contemporary Bayesian Econometrics and Statistics
Author | : John Geweke |
Publsiher | : John Wiley & Sons |
Total Pages | : 322 |
Release | : 2005-10-03 |
Genre | : Mathematics |
ISBN | : 9780471744726 |
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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 Econometric Methods
Author | : Joshua Chan,Gary Koop,Dale J. Poirier,Justin L. Tobias |
Publsiher | : Cambridge University Press |
Total Pages | : 491 |
Release | : 2019-08-15 |
Genre | : Business & Economics |
ISBN | : 9781108423380 |
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Illustrates Bayesian theory and application through a series of exercises in question and answer format.
The Oxford Handbook of Bayesian Econometrics
Author | : Herman van Dijk |
Publsiher | : Oxford University Press |
Total Pages | : 571 |
Release | : 2011-09-29 |
Genre | : Business & Economics |
ISBN | : 9780199559084 |
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A broad coverage of the application of Bayesian econometrics in the major fields of economics and related disciplines, including macroeconomics, microeconomics, finance, and marketing.
Complete and Incomplete Econometric Models
Author | : John Geweke |
Publsiher | : Princeton University Press |
Total Pages | : 176 |
Release | : 2010-02-08 |
Genre | : Business & Economics |
ISBN | : 9781400835249 |
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Econometric models are widely used in the creation and evaluation of economic policy in the public and private sectors. But these models are useful only if they adequately account for the phenomena in question, and they can be quite misleading if they do not. In response, econometricians have developed tests and other checks for model adequacy. All of these methods, however, take as given the specification of the model to be tested. In this book, John Geweke addresses the critical earlier stage of model development, the point at which potential models are inherently incomplete. Summarizing and extending recent advances in Bayesian econometrics, Geweke shows how simple modern simulation methods can complement the creative process of model formulation. These methods, which are accessible to economics PhD students as well as to practicing applied econometricians, streamline the processes of model development and specification checking. Complete with illustrations from a wide variety of applications, this is an important contribution to econometrics that will interest economists and PhD students alike.
Bayesian and Likelihood Methods in Statistics and Econometrics
Author | : Seymour Geisser |
Publsiher | : North Holland |
Total Pages | : 520 |
Release | : 1990 |
Genre | : Business & Economics |
ISBN | : MINN:31951D00518128K |
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On Bayesian econometrics
Studies in Bayesian Econometrics and Statistics
Author | : Anonim |
Publsiher | : Unknown |
Total Pages | : 0 |
Release | : 1975 |
Genre | : Bayesian statistical decision theory |
ISBN | : 072043100X |
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Bayesian Analysis in Econometrics and Statistics
Author | : Harold Jeffreys,Arnold Zellner |
Publsiher | : North-Holland |
Total Pages | : 496 |
Release | : 1980 |
Genre | : Business & Economics |
ISBN | : STANFORD:36105038901406 |
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Introduction to Bayesian Econometrics
Author | : Edward Greenberg |
Publsiher | : Cambridge University Press |
Total Pages | : 271 |
Release | : 2013 |
Genre | : Business & Economics |
ISBN | : 9781107015319 |
Download Introduction to Bayesian Econometrics Book in PDF, Epub and Kindle
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.