Introduction to Bayesian Econometrics
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Book Overview
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.
Format:Paperback
Language:English
ISBN:110743677X
ISBN13:9781107436770
Release Date:August 2014
Publisher:Cambridge University Press
Length:270 Pages
Weight:1.05 lbs.
Dimensions:0.7" x 6.9" x 9.8"
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