吉林省县域经济效率时空格局演化研究

doi:10.13249/j.cnki.sgs.2019.08.011

摘要/Abstract

摘要：

基于吉林省39个县域11 a的面板数据,采用DEA-Malmquist指数法测度县域的全要素生产率,并运用探索性空间数据分析手段（ESDA）,对不同时间维度的县域经济发展效率进行空间关联性与空间差异度分析。研究发现:①在考察期内,吉林省县域全要素生产率总体呈现波动上升,县域间的差异性表现出先扩大、后缩小的趋势。全要素生产率与县域经济总量之间不存在显著的正相关关系;②在全要素生产率改善方面,技术进步发挥了主导性作用,但近年来其对全要素生产率的贡献度逐年下降。而技术效率和规模效率对吉林省县域全要素生产率的促进作用在逐年增强; ③就全省范围而言,县域全要素生产率总体上不存在显著的全局空间自相关性,基本呈现随机分布的空间格局。但在局部空间尺度上,具有一定程度的空间集聚性,并且以高-高和高-低分布形式为主;④县域间经济效率的时空分异主要受其资源禀赋,以及在此基础上形成的县域经济分工、产业结构和经济集聚水平等的影响。

关键词: 县域经济, 全要素生产率, 县域经济发展效率, DEA-Malmquist指数, 吉林省

Abstract:

County economy is the important support of China's economic growth, while the promotion of total factor productivity has become the only way to promote the economic growth of the county. Based on 11-year panel data of 39 counties in Jilin Province, the article estimated the total factor productivity of the counties, using the DEA-Malmquist index method. And then, by means of the exploratory spatial data analysis (ESDA), the article made a further study on the spatial correlation and spatial difference of the economic development efficiency of the counties from different time dimensions. Research findings: 1) During the inspection period, the total factor productivity of county area in Jilin Province was generally rising, and the differences among counties showed the trend of expanding first and then narrowing. And there is no positive correlation between total factor productivity and county economic aggregate; 2) In terms of total factor productivity improvement, technological progress has played a dominant role, but in recent years, the contribution to total factor productivity has decreased year by year. While the promoting effect of technical efficiency and scale efficiency on the total factor productivity of Jilin Province is increasing year by year; 3) As far as the whole province is concerned, there is no significant global spatial autocorrelation in the total factor productivity of the counties, and the spatial pattern of random distribution is basically presented. However, in the local spatial scale, there is a certain degree of spatial agglomeration, and the main distribution pattern is H-H and H-L; 4) The spatial and temporal differentiation of economic efficiency between counties is mainly affected by their resource endowment and county economic division, industrial structure and economic agglomeration level formed on this basis.

Key words: county economy, total factor productivity, economic efficiency of the counties, DEA-Malmquist index, Jilin Province

中图分类号:

F127

李宁,李铁滨,房艳刚,周丽君,王昱,赵伟. 吉林省县域经济效率时空格局演化研究[J]. 地理科学, 2019, 39(8): 1293-1301.

Li Ning,Li Tiebin,Fang Yangang,Zhou Lijun,Wang Yu,Zhao Wei. Spatiotemporal Pattern Evolution of Economic Efficiency in County Area of Jilin Province Based on Malmquist and ESDA[J]. SCIENTIA GEOGRAPHICA SINICA, 2019, 39(8): 1293-1301.

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指标类型	指标选取（单位）	评价目的
投入	固定资产投资额（万元）	资本存量
	从业人员数（单位、乡村）（人）	劳动力投入
	财政支出（科技、教育）（万元）	技术进步、人力资本
产出	地区生产总值（万元）	经济效益
	社会消费品零售总额（万元）	社会福利
	单位从业人员平均劳动报酬（元）	居民生活

年份	技术变化		纯效率变化		规模效率变化		全要素生产率(M_k)
年份	均值	变异系数	均值	变异系数	均值	变异系数	均值	变异系数
2006	1.032	0.064	0.989	0.114	1.003	0.079	1.021	0.128
2007	1.037	0.127	1.034	0.138	0.997	0.070	1.061	0.149
2008	3.588	0.205	0.984	0.096	1.055	0.091	3.767	0.284
2009	0.289	0.225	1.052	0.072	1.004	0.050	0.305	0.234
2010	1.084	0.109	0.992	0.070	1.000	0.047	1.070	0.102
2011	1.169	0.065	0.994	0.101	0.992	0.061	1.150	0.119
2012	1.076	0.066	1.009	0.059	0.990	0.031	1.074	0.082
2013	1.042	0.070	1.028	0.075	1.001	0.029	1.071	0.092
2014	1.036	0.043	1.013	0.056	1.010	0.043	1.059	0.073
2015	1.023	0.060	1.026	0.059	1.027	0.063	1.076	0.088
均值	1.238	0.103	1.012	0.084	1.008	0.056	1.265	0.135

	2006年	2007年	2008年	2009年	2010年
Moran's I	0.250740	-0.123414	0.351845	0.580101	0.064258
Z	1.951771	-0.668290	2.580378	4.215935	0.642646
P	0.050965	0.503949	0.009869	0.000025	0.520454
	2011年	2012年	2013年	2014年	2015年
Moran's I	-0.024617	-0.004675	-0.180969	0.104833	-0.003056
Z	0.012159	0.149172	-1.094051	0.911476	0.160802
P	0.990299	0.881418	0.273933	0.362045	0.872250