G2TT
来源类型Discussion paper
规范类型论文
来源IDDP15964
DP15964 Addressing COVID-19 Outliers in BVARs with Stochastic Volatility
Massimiliano Marcellino; Todd Clark; Andrea Carriero; Elmar Mertens
发表日期2021-03-25
出版年2021
语种英语
摘要Incoming data in 2020 posed sizable challenges for the use of VARs in economic analysis: Enormous movements in a number of series have had strong effects on parameters and forecasts constructed with standard VAR methods. We propose the use of VAR models with time-varying volatility that include a treatment of the COVID extremes as outlier observations. Typical VARs with time-varying volatility assume changes in uncertainty to be highly persistent. Instead, we adopt an outlier-adjusted stochastic volatility (SV) model for VAR residuals that combines transitory and persistent changes in volatility. In addition, we consider the treatment of outliers as missing data. Evaluating forecast performance over the last few decades in quasi-real time, we find that the outlier-augmented SV scheme does at least as well as a conventional SV model, while both out-perform standard homoskedastic VARs. Point forecasts made in 2020 from heteroskedastic VARs are much less sensitive to outliers in the data, and the outlier-adjusted SV model generates more reasonable gauges of forecast uncertainty than a standard SV model. At least pre-COVID, a close alternative to the outlier-adjusted model is an SV model with t-distributed shocks. Treating outliers as missing data also generates better-behaved forecasts than the conventional SV model. However, since uncertainty about the incidence of outliers is ignored in that approach, it leads to strikingly tight predictive densities.
主题Monetary Economics and Fluctuations
关键词Bayesian vars stochastic volatility Outliers Pandemics forecasts
URLhttps://cepr.org/publications/dp15964
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/544954
推荐引用方式
GB/T 7714
Massimiliano Marcellino,Todd Clark,Andrea Carriero,et al. DP15964 Addressing COVID-19 Outliers in BVARs with Stochastic Volatility. 2021.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Massimiliano Marcellino]的文章
[Todd Clark]的文章
[Andrea Carriero]的文章
百度学术
百度学术中相似的文章
[Massimiliano Marcellino]的文章
[Todd Clark]的文章
[Andrea Carriero]的文章
必应学术
必应学术中相似的文章
[Massimiliano Marcellino]的文章
[Todd Clark]的文章
[Andrea Carriero]的文章
相关权益政策
暂无数据
收藏/分享

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。