基于网络搜索数据的湖北省社会消费品零售总额的预测研究

The Research about Forecast of Total Retail Sales of Consumer Goods of HuBei Based on Web Search Data

本文基于湖北省的数据,研究网络搜索数据能否优化以往仅使用政府统计指标对社会消费品零售总额的预测。为此,建立6种模型,分别以政府统计数据、网络搜索数据或它们的不同组合做解释变量。实证结果显示,网络搜索数据的加入显著地改进了仅用政府统计指标做解释变量模型的预测效果,网络搜索数据是政府统计数据的良好补充,需要注意的是,须将其和政府统计数据加以区分使用。本文的研究结果可助力湖北省社会消费品零售总额的统计工作,也能为政府部门制定拉动内需政策提供一定参考。

In the era of big data,web search data is generated at an alarming rate every day,which enriches the type and source of data.There is still little literature involved about whether and how to use web search data to predict the total retail sales of social consumer goods.Based on the data of Hubei Province,this paper researches whether the web search data can optimize the prediction model which used only the government statistical indicators as explanatory variables in the past.To achieve this goal,this study established six types of models,including government statistical data,web search data or different combinations of them as explanatory variables.The empirical results show that the addition of web search data plays a significant role in promoting the model only use the government statistical indicators as explanatory variables.The web search data is a good complement to the government statistical data.To be noted that it should be distinguished from the government statistical data.The results of this paper can be used to help statistical work of the total retail sales of consumer goods,and also provide a reference for government departments to formulate policies to stimulate domestic demand.