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Books > Business & Economics > Economics > Econometrics
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Bayesian Inference in Dynamic Econometric Models (Hardcover, New)
Loot Price: R6,653
Discovery Miles 66 530
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Bayesian Inference in Dynamic Econometric Models (Hardcover, New)
Series: Advanced Texts in Econometrics
Expected to ship within 10 - 15 working days
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Total price: R6,673
Discovery Miles: 66 730
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This work contains an up-to-date coverage of the last 20 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. This
book is intended for econometrics and statistics postgraduates,
professors and researchers in economics departments, business
schools, statistics departments, or any research centre in the same
fields, especially econometricians.
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