G2TT
来源类型Discussion paper
规范类型论文
来源IDDP5513
DP5513 Estimating Macroeconomic Models: A Likelihood Approach
Juan Francisco Rubio-Ramírez; Jesus Fernandez-Villaverde
发表日期2006-03-22
出版年2006
语种英语
摘要This paper shows how particle filtering allows us to undertake likelihood-based inference in dynamic macroeconomic models. The models can be nonlinear and/or non-normal. We describe how to use the output from the particle filter to estimate the structural parameters of the model, those characterizing preferences and technology, and to compare different economies. Both tasks can be implemented from either a classical or a Bayesian perspective. We illustrate the technique by estimating a business cycle model with investment-specific technological change, preference shocks, and stochastic volatility.
主题International Macroeconomics
关键词Dynamic macroeconomic models Particle filtering Nonlinear and/or non-normal models Business cycle stochastic volatility
URLhttps://cepr.org/publications/dp5513
来源智库Centre for Economic Policy Research (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/534410
推荐引用方式
GB/T 7714
Juan Francisco Rubio-Ramírez,Jesus Fernandez-Villaverde. DP5513 Estimating Macroeconomic Models: A Likelihood Approach. 2006.
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