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Creator: Geweke, John. Series: Working paper (Federal Reserve Bank of Minneapolis. Research Dept.) Number: 532 Abstract:
This paper integrates and extends some recent computational advances in Bayesian inference with the objective of more fully realizing the Bayesian promise of coherent inference and model comparison in economics. It combines Markov chain Monte Carlo and independence Monte Carlo with importance sampling to provide an efficient and generic method for updating posterior distributions. It exploits the multiplicative decomposition of marginalized likelihood into predictive factors, to compute posterior odds ratios efficiently and with minimal further investment in software. It argues for the use of predictive odds ratios in model comparison in economics. Finally, it suggests procedures for public reporting that will enable remote clients to conveniently modify priors, form posterior expectations of their own functions of interest, and update the posterior distribution with new observations. A series of examples explores the practicality and efficiency of these methods.
This paper was prepared for the inaugural Colin Clark Lecture, Australasian Meetings of the Econometric Society, July 1994.
Mot-clé: Model comparison, Econometric modeling, Bayesian inference, and Computation Assujettir: C11 - Econometric and statistical methods : General - Bayesian analysis and C53 - Econometric modeling - Forecasting and other model applications
Creator: Richard, Jean François. and Zhang, Wei. Series: Simulation-based inference in econometrics La description:
Original document was hand-written so not in OCR searchable format.
Mot-clé: Simulation, Econometric modeling, and Latent variables Assujettir: C15 - Econometric and statistical methods : General - Simulation methods and C32 - Multiple or simultaneous equation models - Time-series models ; Dynamic quantile regressions