A Study on Construction of Inflation Index based on Web Search Data

C. Hang, S. Yi, Y. Xin, Benfu Lv
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Abstract

In recent years, with the rapid development of network technology, network technology and social behaviour have crossed and integrated deeply. Web search data contains a huge search concerns and needs, which provides the necessary database for the study of social and economic behaviour. This paper applies web search data to the construction of inflation index. To begin with, the selection of key words; then, an empirical analysis based on the use of the Baidu index of access to the key words search data. Empirical analysis is divided into three parts:(1) key words classification;(2) construct the leading inflation index;(3) establish inflation forecasting model. The results show that the web search data exist co-integration with CPI; second, the leading inflation index constructed using principal component analysis with strong timeliness, about 4–8 months earlier than the data released by the National Bureau of Statistics; furthermore, the forecast model passes the equation of goodness-of-fit test, the test of significance and heteroscedasticity test, with a certain degree of scientific and effective.
基于网络搜索数据的通货膨胀指数构建研究
近年来,随着网络技术的飞速发展,网络技术与社会行为已经交叉并深度融合。网络搜索数据包含了巨大的搜索关注点和需求,为研究社会经济行为提供了必要的数据库。本文将网络搜索数据应用于通货膨胀指数的构建。首先,关键词的选择;然后,在实证分析的基础上利用百度索引获取关键词搜索数据。实证分析分为三个部分:(1)关键词分类;(2)构建先行通胀指数;(3)建立通胀预测模型。结果表明,网络搜索数据与CPI存在协整关系;二是采用主成分分析法构建的先行通胀指数,具有较强的时效性,比国家统计局公布的数据早4-8个月左右;并且,预测模型通过了方程拟合优度检验、显著性检验和异方差检验,具有一定的科学性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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