Bayesian Econometric Methods

Joshua Chan

ISBN 10: 1108423388 / ISBN 13: 9781108423380

Published by Cambridge University Press, 2019

About this Item

Druck auf Anfrage Neuware - Printed after ordering - The second edition of Bayesian Econometric Methods illustrates Bayesian theory and application through a series of exercises, complete with solutions to those exercises and computer code. The book is suitable for graduate students in statistics, economics, finance and other disciplines.

Seller Inventory # 9781108423380

Bibliographic Details

• Title: Bayesian Econometric Methods
• Publisher: Cambridge University Press
• Publication Date: 2019
• Language: English
• ISBN 10: 1108423388
• ISBN 13: 9781108423380
• Binding: Buch
• Edition: 2nd Edition
• Condition: Neu
• Dimensions: 250W x 175H x 31D millimeters 250 millimeters width by 175 millimeters height by 31 millimeters depth
• Weight: 1020 grams

About this title

Synopsis

Illustrates Bayesian theory and application through a series of exercises in question and answer format.

About the Authors

Joshua Chan is Professor of Economics at Purdue University, Indiana. He is interested in building flexible models for large datasets and developing efficient estimation methods. His favorite applications include trend inflation estimation and macroeconomic forecasting. He has co-authored the textbook Statistical Modeling and Computation (2013).

Gary Koop is a professor in the Department of Economics at the University of Strathclyde. He received his Ph.D. at the University of Toronto in 1989. His research work in Bayesian econometrics has resulted in numerous publications in top econometrics journals such as the Journal of Econometrics. He has also published several textbooks, including Bayesian Econometrics, and Bayesian Econometric Methods, and is co-editor of The Oxford Handbook of Bayesian Econometrics (2011). He is on the editorial board of several journals, including the Journal of Business and Economic Statistics and the Journal of Applied Econometrics.

Dale J. Poirier is Emeritus Professor of Economics and Statistics at the University of California, Irvine. He is a fellow of the Econometric Society, the American Statistical Association, the International Society for Bayesian Analysis, and the Journal of Econometrics. He has been on the Editorial Boards of the Journal of Econometrics and Econometric Theory, and was the founding editor of Econometric Reviews. His previous books include Intermediate Statistics and Econometrics: A Comparative Approach (1995), and The Econometrics of Structural Change (1976).

Justin L. Tobias is Professor and Head of the Economics Department at Purdue University, Indiana. He received his Ph.D. from the University of Chicago in 1999 and has contributed to and served as an Associate Editor for several leading econometrics journals, including the Journal of Applied Econometrics and the Journal of Business and Economic Statistics. His work focuses primarily on the development and application of Bayesian microeconometric methods.