Sequential Monte Carlo Sampling for DSGE Models
收藏NBER2013-06-01 更新2025-01-04 收录
下载链接：
https://www.nber.org/papers/w19152
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资源简介：
We develop a sequential Monte Carlo (SMC) algorithm for estimating Bayesian dynamic stochastic general equilibrium (DSGE) models, wherein a particle approximation to the posterior is built iteratively through tempering the likelihood. Using three examples consisting of an artificial state-space
提供机构：
美国国家经济研究局
创建时间：
2013-06-01
