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来源类型 | Discussion paper |
规范类型 | 论文 |
来源ID | DP16346 |
DP16346 Using Time-Varying Volatility for Identification in Vector Autoregressions: An Application to Endogenous Uncertainty | |
Massimiliano Marcellino; Andrea Carriero; Todd Clark | |
发表日期 | 2021-07-08 |
出版年 | 2021 |
语种 | 英语 |
摘要 | We develop a structural vector autoregression with stochastic volatility in which one of the variables can impact both the mean and the variance of the other variables. We provide conditional posterior distributions for this model, develop an MCMC algorithm for estimation, and show how stochastic volatility can be used to provide useful restrictions for the identification of structural shocks. We then use the model with US data to show that some variables have a significant contemporaneous feedback effect on macroeconomic uncertainty, and overlooking this channel can lead to distortions in the estimated effects of uncertainty on the economy. |
主题 | Monetary Economics and Fluctuations |
关键词 | Endogeneity Causality stochastic volatility Bayesian methods |
URL | https://cepr.org/publications/dp16346 |
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/545310 |
推荐引用方式 GB/T 7714 | Massimiliano Marcellino,Andrea Carriero,Todd Clark. DP16346 Using Time-Varying Volatility for Identification in Vector Autoregressions: An Application to Endogenous Uncertainty. 2021. |
条目包含的文件 | 条目无相关文件。 |
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