Dynamic Factor Forecasts for Chinese GDP

摘要：

In time series models, the number of parameters increases quickly with the number of variables, so that usually only small-scale multivariate models are considered. Factor models can cope with many variables without running into scarce degrees of freedom problems. Hence, in this paper we construct a large macroeconomic data-set for China, with about 41 variables, model it using a dynamic factor model, and compare the resulting forecasts with ARMA models. Finally, the factor-based forecasts are shown to improve upon standard benchmarks for GDP at virtually no additional modelling or computational costs.

关键词： dynamic factors time series models forecasting

作者: DU Yonghong WANG Jian WANG Rufang

作者单位: School of Economics, Nankai University, P.R.China, 300071 School of Economics, Beijing Wuzi University, P.R.China, 101149

会议类型: 国际会议

会议名称: The 3rd International Institute of Statistics & Management Engineering Symposium(2010 国际统计与管理工程研讨会 IISMES)

会议地点: 威海

会议语种:英文

页码: 303-307

在线出版日期: 2010-07-24（万方平台首次上网日期，不代表论文的发表时间）