Estimating a Dynamic Factor Model in EViews Using the Kalman Filter and Smoother

被引:0
|
作者
Martin Solberger
Erik Spånberg
机构
[1] Uppsala University,Department of Statistics
[2] Ministry of Finance,Department of Statistics
[3] Stockholm University,undefined
来源
Computational Economics | 2020年 / 55卷
关键词
Dynamic factor model; State space; Kalman filter; EViews;
D O I
暂无
中图分类号
学科分类号
摘要
Dynamic factor models have become very popular for analyzing high-dimensional time series, and are now standard tools in, for instance, business cycle analysis and forecasting. Despite their popularity, most statistical software do not provide these models within standard packages. We briefly review the literature and show how to estimate a dynamic factor model in EViews. A subroutine that estimates the model is provided. In a simulation study, the precision of the estimated factors are evaluated, and in an empirical example, the usefulness of the model is illustrated.
引用
收藏
页码:875 / 900
页数:25
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