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The Oxford Handbook of Bayesian Econometrics
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Bayesian econometric methods have enjoyed an increase in popularity in recent years. Econometricians, empirical economists, and policymakers are increasingly making use of Bayesian methods. The Oxford Handbook of Bayesian Econometrics is a single source about Bayesian methods in specialized fields. It contains articles 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 articles 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 articles on Bayesian principles and methodology.
Oxford University Press
Title: The Oxford Handbook of Bayesian Econometrics
Description:
Bayesian econometric methods have enjoyed an increase in popularity in recent years.
Econometricians, empirical economists, and policymakers are increasingly making use of Bayesian methods.
The Oxford Handbook of Bayesian Econometrics is a single source about Bayesian methods in specialized fields.
It contains articles 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 articles 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 articles on Bayesian principles and methodology.
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