Bayesian Economics Through Numerical Methods
DOWNLOAD
FREE 30 Days
Download Bayesian Economics Through Numerical Methods PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Bayesian Economics Through Numerical Methods book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Bayesian Economics Through Numerical Methods
DOWNLOAD
FREE 30 Days
Author : Jeffrey H. Dorfman
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-03-31
Bayesian Economics Through Numerical Methods written by Jeffrey H. Dorfman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-03-31 with Business & Economics categories.
Providing researchers in economics, finance, and statistics with an up-to-date introduction to applying Bayesian techniques to empirical studies, this book covers the full range of the new numerical techniques which have been developed over the last thirty years. Notably, these are: Monte Carlo sampling, antithetic replication, importance sampling, and Gibbs sampling. The author covers both advances in theory and modern approaches to numerical and applied problems, and includes applications drawn from a variety of different fields within economics, while also providing a quick overview of the underlying statistical ideas of Bayesian thought. The result is a book which presents a roadmap of applied economic questions that can now be addressed empirically with Bayesian methods. Consequently, many researchers will find this a readily readable survey of this growing topic.
The Oxford Handbook Of Bayesian Econometrics
DOWNLOAD
FREE 30 Days
Author : Herman van Dijk
language : en
Publisher: Oxford University Press
Release Date : 2011-09-29
The Oxford Handbook Of Bayesian Econometrics written by Herman van Dijk and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-29 with Business & Economics categories.
A broad coverage of the application of Bayesian econometrics in the major fields of economics and related disciplines, including macroeconomics, microeconomics, finance, and marketing.
Introduction To Modern Bayesian Econometrics
DOWNLOAD
FREE 30 Days
Author : Tony Lancaster
language : en
Publisher: Wiley-Blackwell
Release Date : 2004-06-18
Introduction To Modern Bayesian Econometrics written by Tony Lancaster and has been published by Wiley-Blackwell this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-06-18 with Business & Economics categories.
In this new and expanding area, Tony Lancaster’s text is the first comprehensive introduction to the Bayesian way of doing applied economics. Uses clear explanations and practical illustrations and problems to present innovative, computer-intensive ways for applied economists to use the Bayesian method; Emphasizes computation and the study of probability distributions by computer sampling; Covers all the standard econometric models, including linear and non-linear regression using cross-sectional, time series, and panel data; Details causal inference and inference about structural econometric models; Includes numerical and graphical examples in each chapter, demonstrating their solutions using the S programming language and Bugs software Supported by online supplements, including Data Sets and Solutions to Problems, at www.blackwellpublishing.com/lancaster
Bayesian Inference In The Social Sciences
DOWNLOAD
FREE 30 Days
Author : Ivan Jeliazkov
language : en
Publisher: John Wiley & Sons
Release Date : 2014-11-04
Bayesian Inference In The Social Sciences written by Ivan Jeliazkov and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-04 with Mathematics categories.
Presents new models, methods, and techniques and considers important real-world applications in political science, sociology, economics, marketing, and finance Emphasizing interdisciplinary coverage, Bayesian Inference in the Social Sciences builds upon the recent growth in Bayesian methodology and examines an array of topics in model formulation, estimation, and applications. The book presents recent and trending developments in a diverse, yet closely integrated, set of research topics within the social sciences and facilitates the transmission of new ideas and methodology across disciplines while maintaining manageability, coherence, and a clear focus. Bayesian Inference in the Social Sciences features innovative methodology and novel applications in addition to new theoretical developments and modeling approaches, including the formulation and analysis of models with partial observability, sample selection, and incomplete data. Additional areas of inquiry include a Bayesian derivation of empirical likelihood and method of moment estimators, and the analysis of treatment effect models with endogeneity. The book emphasizes practical implementation, reviews and extends estimation algorithms, and examines innovative applications in a multitude of fields. Time series techniques and algorithms are discussed for stochastic volatility, dynamic factor, and time-varying parameter models. Additional features include: Real-world applications and case studies that highlight asset pricing under fat-tailed distributions, price indifference modeling and market segmentation, analysis of dynamic networks, ethnic minorities and civil war, school choice effects, and business cycles and macroeconomic performance State-of-the-art computational tools and Markov chain Monte Carlo algorithms with related materials available via the book’s supplemental website Interdisciplinary coverage from well-known international scholars and practitioners Bayesian Inference in the Social Sciences is an ideal reference for researchers in economics, political science, sociology, and business as well as an excellent resource for academic, government, and regulation agencies. The book is also useful for graduate-level courses in applied econometrics, statistics, mathematical modeling and simulation, numerical methods, computational analysis, and the social sciences.
Bayesian Econometric Methods
DOWNLOAD
FREE 30 Days
Author : Joshua Chan
language : en
Publisher: Cambridge University Press
Release Date : 2019-08-15
Bayesian Econometric Methods written by Joshua Chan and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-15 with Business & Economics categories.
Illustrates Bayesian theory and application through a series of exercises in question and answer format.
Bayesian Inference In Dynamic Econometric Models
DOWNLOAD
FREE 30 Days
Author : Luc Bauwens
language : en
Publisher: OUP Oxford
Release Date : 2000-01-06
Bayesian Inference In Dynamic Econometric Models written by Luc Bauwens and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-01-06 with Business & Economics categories.
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.
Contemporary Bayesian Econometrics And Statistics
DOWNLOAD
FREE 30 Days
Author : John Geweke
language : en
Publisher: John Wiley & Sons
Release Date : 2005-10-03
Contemporary Bayesian Econometrics And Statistics written by John Geweke and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-10-03 with Mathematics categories.
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 Econometrics
DOWNLOAD
FREE 30 Days
Author : Gary Koop
language : en
Publisher: Wiley-Interscience
Release Date : 2003
Bayesian Econometrics written by Gary Koop and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Business & Economics categories.
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.
Bayesian Econometrics
DOWNLOAD
FREE 30 Days
Author : Mauro Bernardi
language : en
Publisher: MDPI
Release Date : 2020-12-28
Bayesian Econometrics written by Mauro Bernardi and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-28 with Business & Economics categories.
Since the advent of Markov chain Monte Carlo (MCMC) methods in the early 1990s, Bayesian methods have been proposed for a large and growing number of applications. One of the main advantages of Bayesian inference is the ability to deal with many different sources of uncertainty, including data, models, parameters and parameter restriction uncertainties, in a unified and coherent framework. This book contributes to this literature by collecting a set of carefully evaluated contributions that are grouped amongst two topics in financial economics. The first three papers refer to macro-finance issues for real economy, including the elasticity of factor substitution (ES) in the Cobb–Douglas production function, the effects of government public spending components, and quantitative easing, monetary policy and economics. The last three contributions focus on cryptocurrency and stock market predictability. All arguments are central ingredients in the current economic discussion and their importance has only been further emphasized by the COVID-19 crisis.
Bayesian Analysis And Uncertainty In Economic Theory
DOWNLOAD
FREE 30 Days
Author : Richard Michael Cyert
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Bayesian Analysis And Uncertainty In Economic Theory written by Richard Michael Cyert and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.
We began this research with the objective of applying Bayesian methods of analysis to various aspects of economic theory. We were attracted to the Bayesian approach because it seemed the best analytic framework available for dealing with decision making under uncertainty, and the research presented in this book has only served to strengthen our belief in the appropriateness and usefulness of this methodology. More specif ically, we believe that the concept of organizational learning is funda mental to decision making under uncertainty in economics and that the Bayesian framework is the most appropriate for developing that concept. The central and unifying theme of this book is decision making under uncertainty in microeconomic theory. Our fundamental aim is to explore the ways in which firms and households make decisions and to develop models that have a strong empirical connection. Thus, we have attempted to contribute to economic theory by formalizing models of the actual pro cess of decision making under uncertainty. Bayesian methodology pro vides the appropriate vehicle for this formalization.