基于PCA-DEA模型的中国省际生态效率研究

doi:10.7523/j.issn.2095-6134.2015.04.014

中国科学院大学学报 ›› 2015, Vol. 32 ›› Issue (4): 520-527.DOI: 10.7523/j.issn.2095-6134.2015.04.014

基于PCA-DEA模型的中国省际生态效率研究

王敏, 张晓平

中国科学院大学资源与环境学院, 北京 100049

收稿日期:2014-08-03 修回日期:2015-03-05 发布日期:2015-07-15
通讯作者: 张晓平
基金资助:
中国科学院STS计划项目(KFJ-EW-STS-003,KFJ-EW-STS-089)资助

Regional eco-efficiency evaluation of China based on PCA-DEA model

WANG Min, ZHANG Xiaoping

College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

Received:2014-08-03 Revised:2015-03-05 Published:2015-07-15

摘要/Abstract

摘要： 利用PCA-DEA模型对中国2004—2012年30个省市区的生态效率进行综合测评.结果表明:1)2种模型得出中国总体生态效率综合平均值分别为0.760和0.581,相对效率较低;自2011年以来有显著提升,且规模效率逐渐向技术效率转变;2)省际生态效率差异明显,但有缩小的趋势;3)东部地区的生态效率最高,但内部差异也最大,整体上东中西部地区内部差异有扩大趋势;4)省区"投入-产出"模式的划分,有助于因地制宜采取不同的政策导向,逐步提高区域社会经济发展的生态效率.

关键词: 生态效率, PCA-DEA模型, 区域差异

Abstract: In order to evaluate eco-efficiency of every province in China from 2004 to 2012, PCA-DEA model was applied. We found that the average of Chinese relative eco-efficiency was low and had no significant change mainly due to technical inefficiency, but the scale efficiency had shifted to technical efficiency since 2011. Although the eco-efficiency disparities between different provinces were obvious, the disparities had decreasing tendency. In contrast, regional disparity of eco-efficiency in the east region tends to expand. Accordingly, policy incentives are suggested to improve the regional eco-efficiency.

Key words: eco-efficiency, PCA-DEA model, regional variation

中图分类号:

F124
F205

王敏, 张晓平. 基于PCA-DEA模型的中国省际生态效率研究[J]. 中国科学院大学学报, 2015, 32(4): 520-527.

WANG Min, ZHANG Xiaoping. Regional eco-efficiency evaluation of China based on PCA-DEA model[J]. , 2015, 32(4): 520-527.

参考文献

[1] 吕彬,杨建新. 生态效率方法研究进展与应用[J]. 生态学,2006,26(11):3 890-3 906.
[2] Schaltegger S, Sturm A. Kologische rationalitat [R]//Die Unternehmung. 1990: 273-290.
[3] Schmidheiny S. Changing course: a global business perspective on development and the environment[M]. MA: MIT Press, 1992:108-110.
[4] Greening L A, Davis W B, Schipper L. Decomposition of aggregate carbon intensity for the manufacturing sector: comparison of declining trends from 10 OECD countries for the period 1971-1991[J]. Energy Economics, 1998,20(1):5-12.
[5] Huang J H, Yang X G, Cheng G, et al. A comprehensive eco-efficiency model and dynamics of regional eco-efficiency in China[J]. Journal of Cleaner Production, 2014,67(3):228-238.
[6] Huppes G, Ishikawa M. Eco-efficiency and its terminology[J]. Journal of Industrial Ecology, 2005, 9(4): 43-46.
[7] World Business Council for Sustainable Development. Measuring eco-efficiency: a guide to reporting company performance [R]. WBCSD, 2000:2-30.
[8] Kuosmanen T. Measurement and analysis of eco-efficiency: an economist's perspective[J]. Journal of Industrial Ecology, 2005, 9(4):15-18.
[9] Mickwitz P, Melanen M, Rosenström U, et al. Regional eco-efficiency indicators: a participatory approach[J]. Journal of Cleaner Production, 2006, 14(18): 1 603-1 611.
[10] 杨斌. 2000—2006年中国区域生态效率研究:基于DEA方法的实证分析[J].经济地理,2009,29(7):1 197-1 202.
[11] 张炳,黄和平,毕军.基于物质流分析和数据包络分析的区域生态效率评价: 以江苏省为例[J]. 生态学报,2009,29(5):2 473－2 480.
[12] 周景博,陈妍.中国区域环境效率分析 [J]. 统计与决策,2008,14:44-46.
[13] 程晓娟,韩庆兰,全春光. 基于PCA-DEA组合模型的中国煤炭产业生态效率研究[J].资源科学,2013,35(6):1 292-1 299.
[14] Põldaru R, Roots J. A PCA-DEA approach to measure the quality of life in Estonian counties[J]. Socio-Economic Planning Science, 2014, 48(1): 65-73.
[15] 林海明.对主成分分析法运用中十个问题的解析[J].统计与决策,2007, 16:16-18.
[16] Azadeh A, Amalnick M S. An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors[J].Energy Policy, 2007, 35(7):3 792-3 806.
[17] Adler N, Yazhemsky E. Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction[J]. European Journal of Operational Research, 2010, 202(1):273-284.
[18] Pearson K, Mag P. On lines and planes of closest fit to systems of points in space[J]. Philosophical Magazine,1901 (2):559-572.
[19] Charnes A, Cooper W W, Rhodes E L. Measuring the efficiency of decision making units[J]. European Journal of Operational Research, 1978, 2(6): 429-444.
[20] Kleine A. A general model framework for DEA[J]. Omega, 2004, 32(1):17-23.
[21] Cook W D, Seiford L M. Data envelopment analysis (DEA): thirty years on[J]. European Journal of Operational Research, 2009,192(1):1-17.
[22] 诸大建,邱寿丰.作为我国循环经济测度的生态效率指标及其实证研究[J].长江流域资源与环境,2008,17(1):1-5.
[23] 石敏俊,王妍,张卓颖,等.中国各省区碳足迹与碳排放空间转移[J].地理学报,2012, 67(10):1 327-1 338.
[24] 刘春腊,刘卫东.中国生态补偿的省域差异及影响因素分析[J].自然资源学报,2014,29(7):1 091-1 104.

基于PCA-DEA模型的中国省际生态效率研究

Regional eco-efficiency evaluation of China based on PCA-DEA model

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 5

编辑推荐

Metrics

本文评价

访问统计

联系我们

[1]	闫涛, 张晓平, 赵艳艳. 基于超效率SBM模型的中国城市生态效率时空演变及影响因素[J]. 中国科学院大学学报, 2021, 38(4): 486-493.
[2]	周彦楠, 杨宇, 程博, 黄季夏. 基于脱钩指数和LMDI的中国经济增长与碳排放耦合关系的区域差异[J]. 中国科学院大学学报, 2020, 37(3): 295-307.
[3]	赵曌, 石敏俊, 袁永娜. 市场潜力与中国制造业区域差异[J]. 中国科学院大学学报, 2010, 27(3): 338-349.
[4]	邓丽君, 张平宇, 李平. 中国十大城市群人口与经济发展平衡性分析[J]. 中国科学院大学学报, 2010, 27(2): 154-162.
[5]	马国霞田玉军王志强. 京津冀都市圈经济增长区域差异及其动力机制量化分析[J]. 中国科学院大学学报, 2007, 24(4): 446-452.