G2TT
来源类型Discussion paper
规范类型论文
来源IDDP8867
DP8867 Finite sample performance of small versus large scale dynamic factor models
Gabriel Pérez-Quirós; Máximo Camacho
发表日期2012-03-01
出版年2012
语种英语
摘要We examine the finite-sample performance of small versus large scale dynamic factor models. Our Monte Carlo analysis reveals that small scale factor models out-perform large scale models in factor estimation and forecasting for high levels of cross-correlation across the idiosyncratic errors of series belonging to the same category, for oversampled categories and, especially, for high persistence in either the common factor series or the idiosyncratic errors. Using a panel of 147 US economic indicators, which are classified into 13 economic categories, we show that a small scale dynamic factor model that uses one representative indicator of each category yields satisfactory or even better forecasting results than a large scale dynamic factor model that uses all the economic indicator
主题International Macroeconomics
关键词Business cycles Output growth Time series
URLhttps://cepr.org/publications/dp8867
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/537705
推荐引用方式
GB/T 7714
Gabriel Pérez-Quirós,Máximo Camacho. DP8867 Finite sample performance of small versus large scale dynamic factor models. 2012.
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