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Predicting Chinese consumption series with Baidu

Zhongchen Song and Tom Coupé

Working Papers in Economics from University of Canterbury, Department of Economics and Finance

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.

Keywords: China; Baidu Index; Google Trends; forecasting; consumption. (search for similar items in EconPapers)
JEL-codes: C53 E21 E27 (search for similar items in EconPapers)
Pages: 63 pages
Date: 2022-12-01
New Economics Papers: this item is included in nep-big, nep-cna, nep-for and nep-pay
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Persistent link: https://EconPapers.repec.org/RePEc:cbt:econwp:22/19

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