EconPapers    
Economics at your fingertips  
 

Predicting Chinese consumption series with Baidu

Zhongchen Song and Tom Coupé

Journal of Chinese Economic and Business Studies, 2023, vol. 21, issue 3, 429-463

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.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/14765284.2022.2161175 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Predicting Chinese consumption series with Baidu (2022) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:jocebs:v:21:y:2023:i:3:p:429-463

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RCEA20

DOI: 10.1080/14765284.2022.2161175

Access Statistics for this article

Journal of Chinese Economic and Business Studies is currently edited by Professor Xiaming Liu

More articles in Journal of Chinese Economic and Business Studies from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2024-09-06
Handle: RePEc:taf:jocebs:v:21:y:2023:i:3:p:429-463