用b百度预测中国消费系列

IF 2.4 Q2 ECONOMICS
Zhongchen Song, T. Coupé
{"title":"用b百度预测中国消费系列","authors":"Zhongchen Song, T. Coupé","doi":"10.1080/14765284.2022.2161175","DOIUrl":null,"url":null,"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.","PeriodicalId":45444,"journal":{"name":"Journal of Chinese Economic and Business Studies","volume":"21 1","pages":"429 - 463"},"PeriodicalIF":2.4000,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predicting Chinese consumption series with Baidu\",\"authors\":\"Zhongchen Song, T. Coupé\",\"doi\":\"10.1080/14765284.2022.2161175\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":45444,\"journal\":{\"name\":\"Journal of Chinese Economic and Business Studies\",\"volume\":\"21 1\",\"pages\":\"429 - 463\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2022-12-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Chinese Economic and Business Studies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/14765284.2022.2161175\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chinese Economic and Business Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/14765284.2022.2161175","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0

摘要

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。
Predicting Chinese consumption series with Baidu
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
4.50
自引率
5.00%
发文量
22
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信