文章摘要
Zhou Decai,Tong Feijie,Hu Chenyu.Another Construction of Chinese Real-time Financial Conditions Index Based on Mixed Frequency Loss Function[J].The Journal of quantitative and technical economics,2018,(12):134-154
基于混频损失函数的中国实时金融状况指数另种构建
Another Construction of Chinese Real-time Financial Conditions Index Based on Mixed Frequency Loss Function
  
DOI：
中文关键词: 金融状况指数  货币政策  损失函数  实时  MF-VAR模型
英文关键词: Financial Conditions Index  Monetary Policy  Loss Function  Real-time  MF-VAR Model
基金项目:本文获得国家社会科学基金年度项目（17BTJ011）的资助。
Author NameAffiliation
Zhou Decai Research Center for Scientific & Technological Innovation and Economic Development 
Tong Feijie Center of Mathematical Economics, Shanghai Academy of Social Sciences 
Hu Chenyu School of Information Management & Engineering, Shanghai University of Finance and Economics 
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中文摘要:
      研究目标：基于货币政策双目标混频损失函数(MLF)，构建及检验中国实时金融状况指数(RTFCI)。研究方法：使用MF-DFM模型，构建了由通胀和GDP构成的中国MLF，同时从30个混频金融数据中分别抽取6个结构公因子(SFs)；在栾惠德和侯晓霞(2015)的基础上，克服了金融经济无关联和信息量少等问题，选择由MLF和SFs组成的日月混频数据，使用新构建的MF-SFAVAR模型，以另种方法构建中国RTFCI，并与延时FCI(DTFCI)比较。研究发现：中国MLF很好地刻画了货币政策双目标的共同成分；与DTFCI相比，中国RTFCI是通胀和GDP更优的先行性、相关性、因果性和预测指标；中国货币政策是价格和数量结合型的。研究创新：新构建了MF-SFAVAR模型和中国首个MLF；以另种方法构建了中国RTFCI。研究价值：为中国政府部门实施货币政策和对实体经济进行投融资决策提供了科学依据。
英文摘要:
      Research Objectives: In this paper we investigate how software and information technology service (SITS) industry development affects China‘s economic growth. Research Methods:We conduct empirical analysis with dynamic economic growth model, using provincial panel data from 2002 to 2016.Research Findings: We find that the SITS industry development has a significant role in promoting China‘s economic growth，and the correlation between SITS and economic growth has range effects. The SITS industry in the China‘s east coast area is much more developed than the mideast area, while some units in the west area are catching up quickly. Research Innovations: Based on the first hand of industry data, our analysis has provided further evidence that the application of information technology significantly contributed to China‘s economic growth from 2002 to 2016. Research Value: Our results suggest continue the software industry stimulating policy for sustainable period which is often under arguments, also shine some lights on the further revision of the policy.
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