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Author : John Geweke
Publisher : Unknown
Page : 62 pages
File Size : 46,6 Mb
Release : 1998
Category : Bayesian statistical decision theory
ISBN : OCLC:245920281
Author : Herman K. van Dijk,Alain Monfort,Bryan W. Brown
Publisher : Unknown
Page : 288 pages
File Size : 40,8 Mb
Release : 1995-07-11
Category : Business & Economics
ISBN : STANFORD:36105009818449
This book provides a comprehensive assessment of the latest simulation techniques, and examines the three main areas of econometric inference where the use of simulation methods has been successful; Bayesian inference, classical inference, and the solution and stochastic simulation of dynamic econometric models, in particular general equilibrium models.
Author : Luc Bauwens,Michel Lubrano,Jean-François Richard
Publisher : OUP Oxford
Page : 370 pages
File Size : 54,7 Mb
Release : 2000-01-06
Category : Business & Economics
ISBN : 9780191588464
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.
Author : Roberto Mariano,Til Schuermann,Melvyn J. Weeks
Publisher : Cambridge University Press
Page : 488 pages
File Size : 52,5 Mb
Release : 2000-07-20
Category : Business & Economics
ISBN : 0521591120
This substantial volume has two principal objectives. First it provides an overview of the statistical foundations of Simulation-based inference. This includes the summary and synthesis of the many concepts and results extant in the theoretical literature, the different classes of problems and estimators, the asymptotic properties of these estimators, as well as descriptions of the different simulators in use. Second, the volume provides empirical and operational examples of SBI methods. Often what is missing, even in existing applied papers, are operational issues. Which simulator works best for which problem and why? This volume will explicitly address the important numerical and computational issues in SBI which are not covered comprehensively in the existing literature. Examples of such issues are: comparisons with existing tractable methods, number of replications needed for robust results, choice of instruments, simulation noise and bias as well as efficiency loss in practice.
Author : John Geweke,Gary Koop,Herman van Dijk
Publisher : Oxford University Press
Page : 576 pages
File Size : 55,9 Mb
Release : 2011-09-29
Category : Business & Economics
ISBN : 9780191618260
Bayesian econometric methods have enjoyed an increase in popularity in recent years. Econometricians, empirical economists, and policymakers are increasingly making use of Bayesian methods. This handbook is a single source for researchers and policymakers wanting to learn about Bayesian methods in specialized fields, and for graduate students seeking to make the final step from textbook learning to the research frontier. It contains contributions by leading Bayesians on the latest developments in their specific fields of expertise. The volume provides broad coverage of the application of Bayesian econometrics in the major fields of economics and related disciplines, including macroeconomics, microeconomics, finance, and marketing. It reviews the state of the art in Bayesian econometric methodology, with chapters on posterior simulation and Markov chain Monte Carlo methods, Bayesian nonparametric techniques, and the specialized tools used by Bayesian time series econometricians such as state space models and particle filtering. It also includes chapters on Bayesian principles and methodology.
Author : Joshua Chan,Gary Koop,Dale J. Poirier,Justin L. Tobias
Publisher : Cambridge University Press
Page : 491 pages
File Size : 45,5 Mb
Release : 2019-08-15
Category : Business & Economics
ISBN : 9781108423380
Illustrates Bayesian theory and application through a series of exercises in question and answer format.
Author : John Geweke
Publisher : Princeton University Press
Page : 176 pages
File Size : 51,9 Mb
Release : 2010-02-08
Category : Business & Economics
ISBN : 9781400835249
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.
Author : John Geweke
Publisher : John Wiley & Sons
Page : 322 pages
File Size : 48,8 Mb
Release : 2005-10-03
Category : Mathematics
ISBN : 9780471744726
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.
Author : Riccardo Scarpa,Anna Alberini
Publisher : Springer Science & Business Media
Page : 456 pages
File Size : 52,5 Mb
Release : 2005-08-12
Category : Business & Economics
ISBN : 1402036833
Simulation methods are revolutionizing the practice of applied economic analysis. In this book, leading researchers from around the world discuss interpretation issues, similarities and differences across alternative models, and propose practical solutions for the choice of the model and programming. Case studies show the practical use and the results brought forth by the different methods.
Author : Joshua Chan,Gary Koop,Dale J. Poirier,Justin L. Tobias
Publisher : Cambridge University Press
Page : 491 pages
File Size : 53,6 Mb
Release : 2019-08-15
Category : Business & Economics
ISBN : 9781108530255
Bayesian Econometric Methods examines principles of Bayesian inference by posing a series of theoretical and applied questions and providing detailed solutions to those questions. This second edition adds extensive coverage of models popular in finance and macroeconomics, including state space and unobserved components models, stochastic volatility models, ARCH, GARCH, and vector autoregressive models. The authors have also added many new exercises related to Gibbs sampling and Markov Chain Monte Carlo (MCMC) methods. The text includes regression-based and hierarchical specifications, models based upon latent variable representations, and mixture and time series specifications. MCMC methods are discussed and illustrated in detail - from introductory applications to those at the current research frontier - and MATLAB® computer programs are provided on the website accompanying the text. Suitable for graduate study in economics, the text should also be of interest to students studying statistics, finance, marketing, and agricultural economics.
Author : Kenneth E. Train
Publisher : Cambridge University Press
Page : 400 pages
File Size : 40,9 Mb
Release : 2009-06-30
Category : Business & Economics
ISBN : 9781139480376
This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. This second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
Author : Siddhartha Chib,William Griffiths
Publisher : Emerald Group Publishing
Page : 656 pages
File Size : 51,7 Mb
Release : 2008-12-18
Category : Business & Economics
ISBN : 9781848553088
Illustrates the scope and diversity of modern applications, reviews advances, and highlights many desirable aspects of inference and computations. This work presents an historical overview that describes key contributions to development and makes predictions for future directions.
Author : J.J. Heckman,Edward Leamer
Publisher : Elsevier
Page : 740 pages
File Size : 49,7 Mb
Release : 2001-11-22
Category : Business & Economics
ISBN : 0080524796
The Handbook is a definitive reference source and teaching aid for econometricians. It examines models, estimation theory, data analysis and field applications in econometrics. Comprehensive surveys, written by experts, discuss recent developments at a level suitable for professional use by economists, econometricians, statisticians, and in advanced graduate econometrics courses. For more information on the Handbooks in Economics series, please see our home page on http://www.elsevier.nl/locate/hes
Author : Jan Kmenta,James B. Ramsey
Publisher : Academic Press
Page : 424 pages
File Size : 47,9 Mb
Release : 2014-05-10
Category : Business & Economics
ISBN : 9781483267340
Evaluation of Econometric Models presents approaches to assessing and enhancing the progress of applied economic research. This book discusses the problems and issues in evaluating econometric models, use of exploratory methods in economic analysis, and model construction and evaluation when theoretical knowledge is scarce. The data analysis by partial least squares, prediction analysis of economic models, and aggregation and disaggregation of nonlinear equations are also elaborated. This text likewise covers the comparison of econometric models by optimal control techniques, role of time series analysis in econometric model evaluation, and hypothesis testing in spectral regression. Other topics include the relevance of laboratory experiments to testing resource allocation theory and token economy and animal models for the experimental analysis of economic behavior. This publication is intended for students and researchers interested in evaluating econometric models.
Author : David Ardia
Publisher : Springer Science & Business Media
Page : 206 pages
File Size : 45,7 Mb
Release : 2008-05-08
Category : Business & Economics
ISBN : 9783540786573
This book presents in detail methodologies for the Bayesian estimation of sing- regime and regime-switching GARCH models. These models are widespread and essential tools in n ancial econometrics and have, until recently, mainly been estimated using the classical Maximum Likelihood technique. As this study aims to demonstrate, the Bayesian approach o ers an attractive alternative which enables small sample results, robust estimation, model discrimination and probabilistic statements on nonlinear functions of the model parameters. The author is indebted to numerous individuals for help in the preparation of this study. Primarily, I owe a great debt to Prof. Dr. Philippe J. Deschamps who inspired me to study Bayesian econometrics, suggested the subject, guided me under his supervision and encouraged my research. I would also like to thank Prof. Dr. Martin Wallmeier and my colleagues of the Department of Quantitative Economics, in particular Michael Beer, Roberto Cerratti and Gilles Kaltenrieder, for their useful comments and discussions. I am very indebted to my friends Carlos Ord as Criado, Julien A. Straubhaar, J er ^ ome Ph. A. Taillard and Mathieu Vuilleumier, for their support in the elds of economics, mathematics and statistics. Thanks also to my friend Kevin Barnes who helped with my English in this work. Finally, I am greatly indebted to my parents and grandparents for their support and encouragement while I was struggling with the writing of this thesis.