六盘山集中连片特困地区县域经济发展驱动因素的时空分异研究*——基于ESDA与GWR模型的探索

RESEARCH ON SPATIAL-TEMPORAL DIFFERENTIATION OF DRIVING FACTORS OF COUNTY ECONOMIC DEVELOPMENT IN LIUPANSHAN POVERTY CONCENTRATED AND CONTIGUOUS AREA*——BASED ON ESDA AND GWR MODELS

关键词:  六盘山集中连片特困地区县域经济驱动力时空分异GWR模型

Key words:  Liupanshan poverty concentrated and contiguous area  county economy  driving factors  temporal and spatial differentiation  GWR model.

摘要:

［目的］为了更好地促进六盘山集中连片特困地区县域经济发展，提高居民生活水平；县域经济发展需要更加深入细致研究，其驱动因素分异研究具有重要意义。［方法］结合县域经济驱动研究现状及六盘山片区区情，确定了自然、产业、投入等8个方面的驱动因素，基于ESDA与GWR模型的原理及实践经验，进行定量化研究。［结果］（1）产业因素、投入因素及自然因素存在时空分异，各年的空间分异特点不同； 其他因素存在空间分异。（2）产业结构调整的效应将快速反应在县域经济总量上； 集中连片特困地区经济发展落后，对于二产的依赖性强于其他发达区域； （3）投入要素对于县域经济发展具有较强时效性； （4）县域经济驱动因素的多样化、动态性决定了自然要素只是县域经济发展的限制因素或贡献因素而非决定性因素； （5）交通区位条件亦是限制因素或贡献因素，随着县域经济发展进阶，将拓宽到综合交通地理区位条件； 人口因素对于县域经济发展具有一定的门槛效应或阈值要求，对处于不同发展阶段的不同县域影响存在差异。各县域发展政策、发展历史及基础、技术、外资及社会资本、全球化与市场化水平等方面亦存在空间差异，一定程度上影响着县域经济空间分异程度。［结论］GWR模型的演进可拓宽部分驱动因素的量化研究； 其他因素如人力资本、技术等是今后研究需突破的重点，同时需深入分析或模拟各驱动因素的驱动机制及作用过程，突出动态化、系统性研究的深度及广度。总体上，县域经济是复杂系统，研究难度大，但该研究为县域经济研究提供了一些视角，为其他学者的未来研究提供了借鉴与参考。

Abstract:

Studies on driving factors′ spatial differentiation of county economic development are of great significance because they can to some extent boost county economic development and can increase residents′ individual income to promote their living standards. What′s more, they can satisfy the interior requirements of in depth and scrutinized studies of county economic development. Based on status quo of county economy studies and main features of Liupanshan poverty concentrated and contiguous area, this study adopted theories and practical models of ESDA (Explorative Spatial Data Analysis) and GWR (Geographically Weighted Regression) to intensify quantification studies, and eight driving factors were chosen including natural, industrial, input factors, transportation and some others. Research findings were as follows. (1) Industrial, input and natural factors presented temporal and spatial differentiation; other factors had shown spatial differentiation. Characteristics of annual spatial differentiation were not the same. (2) Effects would be remarkable in county economic aggregate once industrial structure was adjusted. For undeveloped county scale economies in poverty concentrated and contiguous area, their economic growth was more depending on the second industry than counties from developed area. (3)Input factors were directly time sensitive for county economies. That meant input factors could make county economies change quickly once input factors were increased or shorten.(4)The driving factors were diversified and dynamical, which determined natural factors were just as the limiting or contributing factors, not the decisive. (5)Traffic and location was also as a limiting or contributing factor, and it would expand to other fields as county economies evolved. Population reflected a threshold requirement. Different counties perhaps had different thresholds at different development phases. Policy, development history, technology improvement, marketization and globalization level, foreign investment and social capital, etc. was also spatially different and this maybe affect spatial differentiation of counties economic development to a certain extent. Besides, advancement of GWR model will expand quantitative research for other factors. Human capital, technology, and other factors are the foci of further studies. And dynamics and mechanism will be deeply studied and simulated in future to contribute to the depth and breadth of county economic development studies. As a whole, county economies are complex systems, and it′s difficult to do research for them. The diversified and changeable driving factors (which are the main factors, how the driving factors affect) make county economic development not an easy research project. But this study is an attempt and can propose some perspectives or inspire other scholars to further and deeper thoughts.