厦门大学学报：哲学社会科学版
廈門大學學報：哲學社會科學版
하문대학학보：철학사회과학판
Journal of Xiamen University(A Quarterly for Studies in Arts & Social Sciences)
2014年
1期
110~118
,共null页
绿色经济效率 绿色Malmquist指数 SBM 超效率SBM 收敛性
綠色經濟效率 綠色Malmquist指數 SBM 超效率SBM 收斂性
록색경제효솔 록색Malmquist지수 SBM 초효솔SBM 수렴성
green economic efficiency, green Malmquist index, SBM/Super SBM, convergence
正确认识我国绿色经济效率区域的差异，是合理平衡资源与环境发展关系，实现节能减排的重要前提条件。运用SBM／超效率SBM模型，通过对我国各省区绿色经济效率静态水平和动态变动进行测度，可以深入分析省区差异、收敛性以及影响因素。研究发现：全国绿色经济效率年均值为0．706，从整体上呈现先降后升的倒u型演化过程。虽然三大区域绿色经济效率水平东部最高，西部次之，中部最低，但省区间的差异性有所下降，绿色经济效率具有条件卢收敛性。研究期内效率水平改善的主要动力是技术进步，经济增长对绿色经济效率的影响逐渐减弱，1996—2010年全国范围内绿色经济效率和经济增长之间存在显著的倒u型关系。经济发展水平、FDI、结构因素、能源强度、城市化水平对绿色经济效率的影响，在不同时期具有不同程度的时空差异。
正確認識我國綠色經濟效率區域的差異，是閤理平衡資源與環境髮展關繫，實現節能減排的重要前提條件。運用SBM／超效率SBM模型，通過對我國各省區綠色經濟效率靜態水平和動態變動進行測度，可以深入分析省區差異、收斂性以及影響因素。研究髮現：全國綠色經濟效率年均值為0．706，從整體上呈現先降後升的倒u型縯化過程。雖然三大區域綠色經濟效率水平東部最高，西部次之，中部最低，但省區間的差異性有所下降，綠色經濟效率具有條件盧收斂性。研究期內效率水平改善的主要動力是技術進步，經濟增長對綠色經濟效率的影響逐漸減弱，1996—2010年全國範圍內綠色經濟效率和經濟增長之間存在顯著的倒u型關繫。經濟髮展水平、FDI、結構因素、能源彊度、城市化水平對綠色經濟效率的影響，在不同時期具有不同程度的時空差異。
정학인식아국록색경제효솔구역적차이，시합리평형자원여배경발전관계，실현절능감배적중요전제조건。운용SBM／초효솔SBM모형，통과대아국각성구록색경제효솔정태수평화동태변동진행측도，가이심입분석성구차이、수렴성이급영향인소。연구발현：전국록색경제효솔년균치위0．706，종정체상정현선강후승적도u형연화과정。수연삼대구역록색경제효솔수평동부최고，서부차지，중부최저，단성구간적차이성유소하강，록색경제효솔구유조건로수렴성。연구기내효솔수평개선적주요동력시기술진보，경제증장대록색경제효솔적영향축점감약，1996—2010년전국범위내록색경제효솔화경제증장지간존재현저적도u형관계。경제발전수평、FDI、결구인소、능원강도、성시화수평대록색경제효솔적영향，재불동시기구유불동정도적시공차이。
To obtain a correct understanding of differences in green economic efficiency （GEE） in different regions of China is an important prerequisite for our capacity to strike a good balance between resources and environmental develop- ment and to materialize energy conservation and emission reduction. This study measures the stationary and dynamic levels of GEE in China＇s various provinces by SBM and super SBM and carries out an in-depth analysis of regional differences, convergence and influencing factors. The results show that the annual average of China＇s GEE is 0.706 and that its develop- ment follows an inverted U-shape on the whole. Although among the three traditional regions there is a progressive decrease in GEE, with the east being the highest, the west second highest and the middle the lowest, the GEE gaps between differ- ent provinces have been narrowed owing to its character of conditional 13 convergence. It is found that between 1996 and 2010 technological progress was the main driving force behind the improvement of GEE; that the effeet of economic growth on GEE gradually decreased; that across the country there existed a significant inverted U-shape relationship between GEE and economic growth; and that the influence of economic development, FDI, structural factor, energy intensity and level of urbanization on GEE varied according to different periods of time and regions.
