首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Using simulation methods for bayesian econometric models: inference, development,and communication
Authors:John Geweke
Institution:  a Department of Economics, University of Minnesota, Minneapolis, Minnesota, U.S.A b Research Department, Federal Reserve Bank of Minneapolis, Minneapolis, Minnesota, U.S.A
Abstract:This paper surveys the fundamental principles of subjective Bayesian inference in econometrics and the implementation of those principles using posterior simulation methods. The emphasis is on the combination of models and the development of predictive distributions. Moving beyond conditioning on a fixed number of completely specified models, the paper introduces subjective Bayesian tools for formal comparison of these models with as yet incompletely specified models. The paper then shows how posterior simulators can facilitate communication between investigators (for example, econometricians) on the one hand and remote clients (for example, decision makers) on the other, enabling clients to vary the prior distributions and functions of interest employed by investigators. A theme of the paper is the practicality of subjective Bayesian methods. To this end, the paper describes publicly available software for Bayesian inference, model development, and communication and provides illustrations using two simple econometric models.
Keywords:
本文献已被 InformaWorld 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号