Measurement of Regional Industrial Ecological Efficiency in China and an Analysis of Its Influencing Factors
Journal of World Economic Research
Volume 9, Issue 1, June 2020, Pages: 43-50
Received: Dec. 7, 2019;
Accepted: Dec. 16, 2019;
Published: Jan. 17, 2020
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Wu Mingran, School of Management, Nanjing University of Posts and Telecommunications, Nanjing, China
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In recent years, with the rapid advancement of industrialization and urbanization, China's economy has experienced a period of rapid development. However, while China has become the world's second largest economy, it has also become a veritable resource consumer and environmental polluter. So China must need to transform its economic development model and vigorously promote ecological progress. We use interprovincial panel data from 2012 to 2016 to calculate and analyze the industrial ecological efficiency of 31 provinces in China, and then discuss the factors that influence efficiency. The results show that, during the research year, the industrial eco-efficiency of 31 provinces and municipalities in China has been rising steadily in time series but differs significantly in regional cross-sections. Moreover, the eco-efficiency of the eastern region was higher than the central and western regions. Among the influencing factors, the per capita GDP, the proportion of the secondary industry's output value to the regional GDP, and the population density all had a positive impact on industrial eco-efficiency, and the overall industrial eco-efficiency level of the eastern region is higher than the central and western regions. Therefore, the keys to improving regional industrial eco-efficiency are as follows: increasing the income of residents, accelerating the ecological transformation of traditional industries, optimizing the population lay out to alleviate the conflict between people and land, and narrowing the regional development gap.
Industrial Eco-efficiency, Economic Development, Industrial Structure, Population Density, Regional Dummy Variable
To cite this article
Measurement of Regional Industrial Ecological Efficiency in China and an Analysis of Its Influencing Factors, Journal of World Economic Research.
Vol. 9, No. 1,
2020, pp. 43-50.
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
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Stefan Schaltegger, Andreas Sturm. Ökologische Ratio-naliät//Die Unternehmung Nr4/90, 1990: 273-290.
Liu X M, Meng X R, Wang K L. Measurement and Evaluation of Urban Industrial Ecological Efficiency: Empirical Evidence from Anhui Province [J]. East China Economic Management, 2016, (8): 29-34.
Zhang W M, Fang Q M, Liu T. Eco-efficiency evaluation of urban industries: taking Hunan Province for example [J]. Urban Problems, 2015, (3): 62-66+104.
Wu M R, Ma J. Measurement on Regional Ecological Efficiency in China and Analysis on Its Influencing Factors: Based on DEA-Tobit Two-stage Method [J]. Technology Economics, 2016, (3): 75-80+122.
Dai Z M, Zeng Y H, Guo L. Study of the Industrial Eco-efficiency with the Panel Data in East China——Based on the Super Efficiency DEA Model [J]. Soft Science, 2016, (7): 35-39.
Han J P, Wen A L, Yan J. A Research of China’s Industrial Eco-innovation Efficiency Based on DEA Model [J]. Ecological Economy, 2016, (5): 102-105.
You D M, Huang X Z. Evaluation on Provincial Industrial Eco-Technology Innovation Efficiencyin Yangtze River Economic Zone [J]. Economic Geography, 2016, (9): 128-134.
Gao W. Research on Industrial Enterprises’ Co-Efﬁ ciency and Pollution Control in China [J]. Ecological Economy, 2017, (1): 21-27.
Zhao S, Liu H. Evaluation of Industrial Enterprise’s Co-Efficiency Based on Three-Stage DEA Model in China [J]. Ecological Economy, 2016, (11): 88-91+102.
Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision making units [J]. European Journal of Operation Research, 1978 (2): 429-444.
Copper, W. W., Li, S., Seiford, L. M., et al. Sensitivity and stability analysis in DEA: Some recent development [J]. Journal of Productivity Analysis, 2001, 15 (3): 217-246.
Fu S X. Study on the Industrial Regional Distribution of Ecological Civilization [M]. Beijing: Encyclopedia of China Publishing House, 2016.
Pan X X, He Y Q. A Study on Evaluation of Industrial Eco-efficiency and Its Influencing Factors—Based on Provincial Panel Data in Central and East China [J]. East China Economic Management, 2014, 28 (3): 33-38.