摘要
本文利用高维机制转换因子模型(LD-RS-FM)研究大规模经济数据的机制转换特征和经济的周期性特征。借助主成分分析(PCA)和共同因子自回归的二步分析方法,LD-RS-FM从大规模变量中提炼出维数较小并可以概括经济周期运动的共同因子,在此基础上进行机制转换分析。这些共同因子代表了大部分宏观经济运动的趋势和特征,并具有明显的结构化含义。实证结果表明,LD-RS-FM在中国宏观经济周期性特征研究方面具有一定的理论和应用价值。
This paper focused on high dimensional economic variables that were subject to regime switching and put forward a new model： large-dimensional regime-switching factor model （LD-RS-FM）. Based on a two-step analysis, principal component analysis and autoregressive analysis, the model pro- posed here was capable of capturing important macroeconomic features, such as co-movements and struc- tural changes, with a very small number of representative common factors. Therefore, these factors could be used for purpose of regime switching analysis. Additionally, there were also some structural meanings underlying these factors. Conclusions suggested that LD-RS-FM was a powerful tool for the study the bus-iness cycle features of Chinese macro-economy.
出处
《经济理论与经济管理》
CSSCI
北大核心
2012年第10期12-24,共13页
Economic Theory and Business Management
基金
教育部人文社会科学重点研究基地重大项目(2009JJD790050)
