Predicting Chinese consumption series with Baidu

IF 2.4 Q2 ECONOMICS
Zhongchen Song, T. Coupé
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引用次数: 0

Abstract

ABSTRACT There is a substantial literature that suggests that search behavior data from Google Trends can be used for both private and public sector decision-making. In this paper, we use search behavior data from Baidu, the internet search engine most popular in China, to analyze whether these can improve nowcasts and forecasts of the Chinese economy. Using a wide variety of estimation and variable selection procedures, we find that Baidu’s search data can improve nowcast and forecast performance of the sales of automobiles and mobile phones reducing forecast errors by more than 10%, as well as reducing forecast errors of total retail sales of consumptions goods in China by more than 40%. Google Trends data, in contrast, do not improve performance.
用b百度预测中国消费系列
摘要有大量文献表明,谷歌趋势的搜索行为数据可以用于私营部门和公共部门的决策。在本文中,我们使用了中国最受欢迎的互联网搜索引擎百度的搜索行为数据,来分析这些数据是否可以改善中国经济的现状和预测。通过多种估计和变量选择程序,我们发现百度的搜索数据可以提高汽车和手机销售的实时预测性能,将预测误差降低10%以上,并将中国消费品零售总额的预测误差降低40%以上。相比之下,谷歌趋势数据并没有改善性能。
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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来源期刊
CiteScore
4.50
自引率
5.00%
发文量
22
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