%0 Journal Article
%T 中国绿色全要素生产率时空分异及因素分解研究——基于超效率SBM和Malmquist指数<br>A Study on the Spatio-Temporal Differentiation and Factor Decomposition of China’s Green Total Factor Productivity—Based on the Super-Efficiency SBM and Malmquist Index
%A 宋祎楠
%A 杨洲木
%J Operations Research and Fuzziology
%P 367-379
%@ 2163-1530
%D 2024
%I Hans Publishing
%R 10.12677/ORF.2024.141035
%X 本文使用超效率SBM和Malmquist指数方法对中国30个省(区、市)2003~2019年的绿色全要素生产率(GTFP)进行测算，并采用RD分解法将Malmquist指数分解为效率变动、技术变动和规模变动，通过对比全国及东中西地区GTFP变动及其分解值，本文的主要结论有：1) 我国整体的GTFP呈现出上升态势，区域间的GTFP表现为东部 &gt; 西部 &gt; 中部，东部和西部地区GTFP增速快得益于区域内个别增长极拉动地区GTFP的增长，而中部地区GTFP的增速慢受限于区域内个别省份增长势能不足；2) 全国层面存在技术进步、规模扩大和效率下降情况，并且在东、中、西部地区之间存在区域异质性。为进一步提高中国GTFP，提出如下建议：全国层面要加强要素的跨区域流动，促进区域协调发展。东部地区更应促进优势产业集聚、扩大规模，而中西部地区更应加大研发投入、促进技术进步。<br />
In this paper, we use the super-efficiency SBM and Malmquist index methods to measure green total factor productivity (GTFP) for 30 provinces (autonomous regions and municipalities) in China from 2003 to 2019, and used the RD decomposition to decompose Malmquist index into efficiency change, technology change and scale change, by comparing national and sub-regional GTFP’s change and the decomposition values, the main conclusions of this paper are: 1) China’s GTFP shows an upward trend, GTFP between regions shows East &gt; West &gt; Central. The faster growth of GTFP in eastern and western regions is due to some growth poles within the region driving regional GTFP growth, and the slow growth of GTFP in the central region was limited by insufficient growth potential in some provinces. 2) Technical progress, scaling up and efficiency degradation exist at national level, and there is regional heterogeneity between eastern, central and western regions. To improve China’s GTFP, the suggestions are as follow: At the national level, it is important to enhance factors’ cross-regional flow and promote coordinated regional development. The eastern region should promote the clustering expansion of advantaged industries, and the central and western regions need to increase investment in R&amp;D and promote technological progress.
%K 绿色全要素生产率，数据包络分析，RD分解法，区域异质性<br>Green Total Factor Productivity
%K Data Envelopment Analysis
%K RD Decomposition Method
%K Regional Heterogeneity
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=81404