区域低碳发展及空间依赖&mdash;&mdash;基于2005&mdash;2015年中国省级数据的分析

雷明; 马海超; 李浩民; 孙淑晓

doi:10.3981/j.issn.1000-7857.2018.02.003

科技导报 >

2018 , Vol. 36 >Issue 2: 20 - 37

DOI: https://doi.org/10.3981/j.issn.1000-7857.2018.02.003

专题论文

区域低碳发展及空间依赖——基于2005—2015年中国省级数据的分析

雷明 ,
马海超 ,
李浩民 ,
孙淑晓

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北京大学光华管理学院, 北京 100871

雷明,教授,研究方向为决策分析、绿色管理及可持续发展,电子信箱:leiming@gsm.pku.edu.cn

收稿日期: 2017-11-08

修回日期: 2017-12-17

网络出版日期: 2018-02-05

基金资助

国家发改委基金项目子项目（417-106-002）

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Regional low carbon development and spatial interdependence: Analysis based on China's provincial data based analysis (2005-2015)

LEI Ming ,
MA Haichao ,
LI Haomin ,
SUN Shuxiao

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Guanghua School of Management, Peking University, Beijing 100871, China

Received date: 2017-11-08

Revised date: 2017-12-17

Online published: 2018-02-05

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摘要

低碳发展是可持续发展的重要方式，发展低碳经济是中国既定战略目标。结合2005—2015年中国省级层面的实证数据，运用TOPSIS模型对中国部分省份低碳发展进行评估、排序和分析。TOPSIS计算结果表明，本次统计的中国30个省份的低碳发展指数总体上较为稳定，一些省份的低碳指数表现出下降趋势。通过聚类分析可以将30个省份分为表现最好、中上游、中下游、表现最差4个梯队，单因素方差分析结果表明，不同梯队的低碳发展指数具有一定差异，表现差的省份与表现好的省份之间差距显著。为了检验省级低碳发展指数是否存在空间依赖性，计算了“莫兰指数I”进行空间自相关检验，检验结果表明省级低碳经济发展的空间依赖性并不显著。

关键词： 低碳发展; TOPSIS; 聚类分析; 单因素方差分析; 空间依赖性检验

本文引用格式

雷明 , 马海超 , 李浩民 , 孙淑晓 . 区域低碳发展及空间依赖——基于2005—2015年中国省级数据的分析[J]. 科技导报, 2018 , 36(2) : 20 -37 . DOI: 10.3981/j.issn.1000-7857.2018.02.003

Abstract

The low carbon development is an important way of sustainable development. It is China's established strategic goal to develop a low-carbon economy. In this background, based on the empirical data on China's provincial level from 2005 to 2015, this paper evaluates, ranks and analyzes the low carbon development performance for China's 30 provincial regions using the TOPSIS (technique for order preference similarity to ideal solution) model. It is indicated that low carbon development indicators of China's provincial regions are stable in general while some provinces show a downward trend. By clustering analysis, the 30 provincial regions can be divided into 4 groups, which are the best performed group, the upper-middle performed group, the middle-lower performed group and the worst performed group. The Analysis of Variance shows that there exist significant differences between the better performed groups and the worse performed groups. In order to examine whether there exists a spatial interdependence in terms of the provincial low carbon development, the statistical variable Moran's I is calculated to test the spatial reliance and it is found that the spatial interdependence is not significant among the provincial low carbon development indicators.

Key words： low carbon development; TOPSIS; clustering analysis; analysis of variance; spatial interdependence test

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