全球智库信息集成服务系统(G2TT): DP9130 Estimating Dynamic Equilibrium Models with Stochastic Volatility

G2TT

来源类型	Discussion paper
规范类型	论文
来源ID	DP9130
	DP9130 Estimating Dynamic Equilibrium Models with Stochastic Volatility
	Juan Francisco Rubio-Ramírez; Jesus Fernandez-Villaverde; Pablo A. Guerron-Quintana
发表日期	2012-09-16
出版年	2012
语种	英语
摘要	We propose a novel method to estimate dynamic equilibrium models with stochastic volatility. First, we characterize the properties of the solution to this class of models. Second, we take advantage of the results about the structure of the solution to build a sequential Monte Carlo algorithm to evaluate the likelihood function of the model. The approach, which exploits the profusion of shocks in stochastic volatility models, is versatile and computationally tractable even in large-scale models, such as those often employed by policy-making institutions. As an application, we use our algorithm and Bayesian methods to estimate a business cycle model of the U.S. economy with both stochastic volatility and parameter drifting in monetary policy. Our application shows the importance of stochastic volatility in accounting for the dynamics of the data.
主题	International Macroeconomics
关键词	Bayesian methods Dynamic equilibrium models Parameter drifting stochastic volatility
URL	https://cepr.org/publications/dp9130
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/537964
推荐引用方式 GB/T 7714	Juan Francisco Rubio-Ramírez,Jesus Fernandez-Villaverde,Pablo A. Guerron-Quintana. DP9130 Estimating Dynamic Equilibrium Models with Stochastic Volatility. 2012.