基于互联网在线数据的居民消费价格指数
Internet-based Consumer Price Index
基于互联网在线数据的居民消费价格指数
Internet-based Consumer Price Index
The team is directed by Professor Liu Taoxiong, Professor Tang Ke from the Economics Institute of the school of Social Sciences, Tsinghua University, and Professor Xu Bin of the Department of computer science of Tsinghua University. The members have economic background and computer background, including two engineers, three postdoctoral students, four doctoral students and seven master students. The team members are rich in innovation and exploration, and are determined to combine big data technology with economic analysis to provide a new perspective for China's economy under the new normal.
This project, iCPI, is aiming at constructing an online CPI through real-time data, which could establish a description and prediction system with stronger timeliness and higher reliability, providing faster and more accurate reference for macroeconomic decisions.
(a).According to the statistical basket of National Bureau of Statistic of China (NBS): 8 sets, 262 subcategories.
(b).The principle of sample picking: target the goods which have large market share, normal price fluctuation and sold at multiple e-commerce platforms.
(a).Web crawler
(b).Data cleaning
iCPI, Sets, Categories, Subcategories
(a).Daily index
(b).Weekly index
(c).Monthly index