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Decarbonization by digits: How data factors drive nonlinear sustainable dynamics in manufacturing

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  • Wu, Qingyang
  • Li, Shanhong

Abstract

Digital technology presents critical opportunities for controlling global warming within the 1.5 °C threshold established by the Paris Agreement. However, the nonlinear effects of data factors on climate resilience remain poorly understood. This paper, employing a Green Solow model within the framework of a Constant Elasticity of Substitution production function, uncovers a nonlinear, inverted U-shaped response. Utilizing a high-dimensional fixed-effects model and panel data from 30 Chinese provinces between 2011 and 2020, we identify a U-shaped relationship between data factors and low-carbon development in the manufacturing sector, with more pronounced effects in regions with higher levels of marketization. This impact is primarily driven by pathways such as green technological innovation and enhanced resource allocation efficiency. To further validate the global applicability of our findings, we extended the analysis to 166 countries worldwide. The results remained robust, indicating that the positive effects of improved data production factors on low-carbon development in the manufacturing sector are more significant in high-income countries, OECD member states, and nations with advanced digital infrastructure. Our study suggests that supporting and incentivizing data openness, promoting interaction and sharing of manufacturing data, and enhancing data center and network infrastructure construction are essential.

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  • Wu, Qingyang & Li, Shanhong, 2024. "Decarbonization by digits: How data factors drive nonlinear sustainable dynamics in manufacturing," Applied Energy, Elsevier, vol. 374(C).
    • Handle: RePEc:eee:appene:v:374:y:2024:i:c:s0306261924013503
    DOI: 10.1016/j.apenergy.2024.123967
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