How can open public data promote efficient and equitable green production? Evidence from eco-efficiency in China

被引：0
作者：
Wu T. [1 ]
机构：
[1] School of Applied Economics, Renmin University of China, No.59 Zhongguancun Street, Haidian District, Beijing
来源：
Environmental Science and Pollution Research | 2024年 / 31卷 / 24期
关键词：
China; Club convergence; Difference in difference model; Eco-efficiency; Ordered logit model; Public data;
D O I：
10.1007/s11356-024-33464-x
中图分类号：
学科分类号：
摘要：
Nowadays, concurrent attention to economic development and ecological issues is becoming an important trend. In this paper, we measure the eco-efficiency of 285 Chinese cities from 2003 to 2019 using a non-radial directional distance function and the data envelopment analysis method, based on which we analyze the club convergence of cities’ eco-efficiency using the logt test; we estimate the impact of open public data platforms on eco-efficiency and its convergence using a multi-period difference in difference model and panel-ordered logit model, respectively. We find that, first, open public data platforms improve cities’ eco-efficiency by about 6.5%, and the impact mechanisms include scale efficiency, technical efficiency, and total factor productivity, or, at the micro level, increasing the economic agglomeration degree, boosting the amount of foreign investment used, and increasing green innovation level. Second, there are three convergence clubs of eco-efficiency in China’s cities, whose average eco-efficiency trends are above, close to, and below average, respectively. Third, public data platforms significantly increase the probability of cities belonging to the convergence clubs of high and medium eco-efficiency (Clubs 1 and 2) and decrease the probability of belonging to the low one (Club 3). However, the mechanisms only include technical efficiency and total factor productivity, or the amount of foreign investment used and the green innovation level at the micro level. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
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页码：35173 / 35193
页数：20
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