基于互联网大数据的CPI舆情指数构建与应用——以百度指数为例

发布时间：2018-08-28 15:46

【摘要】：研究目标:基于互联网大数据构建CPI舆情指数辅助预测CPI。研究方法:提出了一种构建CPI低频与高频舆情指数的统计方法,并通过选用2006年6月至2015年12月的数据验证了该方法的有效性。研究发现:相关关键词的搜索热度指标具有领先CPI的预测作用,依此建立的CPI舆情指数有助于改进CPI预测精度。研究创新:揭示了基于相关关键词的搜索热度指标与CPI的非线性关系,提出了一种基于门限回归的CPI低频舆情指数构建方法;使用动态因子模型估计出了CPI高频舆情指数。研究价值:预测CPI时可辅助利用基于大数据构建的CPI低频与高频舆情指数信息。
[Abstract]:Objective: to construct CPI Public opinion Index aided Prediction CPI. based on Internet big data Research methods: a statistical method of constructing CPI low frequency and high frequency public opinion index is proposed. The validity of this method is verified by selecting the data from June 2006 to December 2015. It is found that the search heat index of relevant keywords can predict the leading CPI, and the CPI public opinion index is helpful to improve the accuracy of CPI prediction. Research innovation: the nonlinear relationship between search heat index based on relevant keywords and CPI is revealed, a method of constructing CPI low frequency public opinion index based on threshold regression is proposed, and the CPI high frequency public opinion index is estimated by using dynamic factor model. Research value: the low frequency and high frequency public opinion index information of CPI based on big data can be used to predict CPI.
【作者单位】：中南财经政法大学统计与数学学院;中国人民银行长沙中心支行调查统计处;
【基金】：中南财经政法大学一流学科建设项目“大数据统计预测与决策方法研究”的资助
【分类号】：F49;F726

【相似文献】