China’s Economic Growth: The “Two-Dimensional Driving Effect” of Data Factors

Yang Yan, Wang Li (), Li Yujia and Liao Zujun
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Yang Yan: School of Economics, Sichuan University, Sichuan, China
Wang Li: School of Economics, Sichuan University, Sichuan, China
Li Yujia: School of Economics, Sichuan University, Sichuan, China
Liao Zujun: Institute of Regional Economy of Sichuan Academy of Social Sciences, Sichuan, China

China Finance and Economic Review, 2023, vol. 12, issue 4, 86-107

Abstract: Data factors have become one of the five essential production factors, but their role in economic growth has always been ambiguous. Starting from AI technologies, this paper establishes an endogenous growth model of data factors affecting economic growth, constructs the generation path and value path of data factors, and estimates the value of new data factors at the provincial level in China from 1999 to 2018 accordingly. Based on theoretical analyses and empirical tests, it clarifies that data factors have a “two-dimensional driving effect” on China’s economic growth, that is, data factors can drive growth both directly through its own economic growth effect and indirectly by promoting technological progress. Furthermore, this paper makes three extended discussions, aiming to make a trial study on the impacts of local government big data transaction platforms on data factors and their growth effects, discuss whether it is possible to reduce the uncertainties of local economic policy based on the nature of data factors, and make a preliminary survey of the output elasticity of data factors between 1999 and 2018.

Keywords: data factors, economic growth, AI; economic, growth effect (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:cferev:v:12:y:2023:i:4:p:86-107:n:4

DOI: 10.1515/cfer-2023-0023

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