The determinants of urban sustainability in Chinese resource-based cities: A panel quantile regression approach

Yan, D., Kong, Y., Ren, X., Shi, Y. and Chiang, S. (2019) The determinants of urban sustainability in Chinese resource-based cities: A panel quantile regression approach. Science of the Total Environment, 686, pp. 1210-1219. (doi: 10.1016/j.scitotenv.2019.05.386)

Abstract

Improving energy efficiency and reducing environmental pollution emissions are two important ways to alleviate energy problems. Despite the progress in energy efficiency, the growth in energy demand still exceeds the efficiency improvements. This study adopts nonparametric methods to estimate the total factor energy efficiency (TFEE) of 105 resource-based cities covering the period 2010-2016 in China and analyzes the spatiotemporal characteristics of changes in energy efficiency. Furthermore, panel quantile regression is applied to analyze the multiple impacts of economic level, industrial structure, resource endowment, energy price, government intervention and degree of openness on energy efficiency. The main findings are as follows. (1) Each determinant has a different influence on TFEE at different levels; among them, the influence of the fuel and energy price index show an inverted U-shaped distribution as the quantile increases, and that of the GDP per capita shows a stronger heterogeneity than those of other factors. (2) Resource-based cities with lower efficiency are more sensitive to government intervention than are cities with higher efficiency. (3) A city's openness has a negative effect on TFEE, which partly supports the pollution haven hypothesis: the more foreign investment a resource-based city receives, the lower its energy and technology efficiency. Finally, some practical suggestions for the sustainable development of resource-based cities are discussed.

• Item Type: Articles
• Additional Information: Theauthors are grateful forfinancialsupport byShenzhenMunicipalDevelopment and Reform Commission, Shenzhen Environmental Sci-ence and New Energy Technology Engineering Laboratory, Grant Num-ber: SDRC [2016]172; the National Natural Science Foundation of Chinaunder Grant No. 71803182; No. 21808119 and China Postdoctoral Sci-ence Foundation under Grant No. 2019M650733.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Shi, Dr Yukun
• Authors: Yan, D., Kong, Y., Ren, X., Shi, Y., and Chiang, S.
• College/School: College of Social Sciences > Adam Smith Business School > Accounting and Finance
• Journal Name: Science of the Total Environment
• Publisher: Elsevier
• ISSN: 0048-9697
• ISSN (Online): 1879-1026
• Published Online: 30 May 2019
• Copyright Holders: Copyright © 2019 Elsevier B.V.
• First Published: First published in Science of the Total Environment 686:1210-1219
• Publisher Policy: Reproduced in accordance with the publisher copyright policy