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Bayesian Inference in Dynamic Econometric Models$
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Luc Bauwens, Michel Lubrano, and Jean-François Richard

Print publication date: 2000

Print ISBN-13: 9780198773122

Published to Oxford Scholarship Online: September 2011

DOI: 10.1093/acprof:oso/9780198773122.001.0001

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Decision Theory and Bayesian Inference

Decision Theory and Bayesian Inference

Chapter:
(p.1) 1 Decision Theory and Bayesian Inference
Source:
Bayesian Inference in Dynamic Econometric Models
Author(s):

Luc Bauwens

Michel Lubrano

Jean-François Richard

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198773122.003.0001

This chapter discusses the relationship between mathematical statistics, decision theory, and the application of Bayesian inference to econometrics. It analyses the Bayesian approach to decision making under uncertainty and suggests that this method provides a strong rationale for the use of Bayesian techniques in econometrics. It introduces a set of simple axioms to formalize a concept of rational behaviour in the face of uncertainty and presents estimation and hypothesis testing, both from a classical and Bayesian perspective.

Keywords:   Bayesian inference, mathematical statistics, decision theory, econometrics, uncertainty, hypothesis testing

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