Revisiting and evaluation of the index of sustainable economic welfare based on artificial intelligence: data from 30 Chinese provinces from 2003 to 2019

Yulin Liu (), Xincheng Zhu () and Yuhao Wang ()
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Yulin Liu: Chongqing University
Xincheng Zhu: Chongqing University
Yuhao Wang: Chongqing University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2023, vol. 25, issue 4, No 8, 3123-3152

Abstract: Abstract As a useful complement to traditional economic indicators, the Index of Sustainable Economic Welfare (ISEW) is best known for its merits in assessing environmental and social costs. Artificial intelligence (AI) is applied in virtually every area of society, the economy, and the environment. Given the significant impact of inequality in the development of AI on economic growth and sustainable economic welfare, we propose an improved ISEW, namely, AI-ISEW. This paper explores the AI-ISEW gap in China and its influencing factors in the context of uneven AI development. We calculate the ISEW and AI-ISEW for 30 provinces in mainland China from 2003 to 2019 and discuss highly controversial methodological assumptions related to income inequality, long-term environmental damage, and nonrenewable energy consumption. The Dagum Gini coefficient is used to reveal regional differences in AI-ISEW, kernel density estimation is used to describe the dynamic evolutionary trend of AI-ISEW development, and quadratic assignment procedure regression is used to explore the factors influencing the AI-ISEW gap. The study found that the AI-ISEW is on the rise, but its growth rate is generally lower than that of GDP. Compared to the AI-ISEW, the ISEW generally overestimates economic welfare. There are regional differences in China’s AI-ISEW, and the main source of differences is interregional differences. Regarding internal differences in each region, the average Gini coefficient from large to small displays the following order: east > west > central > northeast. Adjusted personal consumption is the greatest factor contributing to the AI-ISEW gap. The most economically developed regions have the greatest disparities in welfare. The research reveals the evolutionary trend of China’s sustainable economic welfare from the perspective of AI development and provides evidence for improving the level of economic welfare and accelerating regional coordinated development.

Keywords: Index of sustainable economic welfare; AI index; Dagum Gini coefficient; Kernel density estimation; QAP (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10668-022-02180-2

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