地理学报 ›› 2015, Vol. 70 ›› Issue (6): 965-979.doi: 10.11821/dlxb201506010

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1990年来广东区域发展的空间溢出效应及驱动因素

王少剑1,2,3(), 王洋4(), 赵亚博5   

  1. 1. 中山大学地理科学与规划学院,广州 510275
    2. 中国科学院地理科学与资源研究所,北京 100101
    3. 中国科学院大学,北京 100049
    4. 广州地理研究所,广州 510070
    5. 北京师范大学地理学与遥感科学学院,北京 100875
  • 收稿日期:2014-09-18 修回日期:2015-02-13 出版日期:2015-06-20 发布日期:2015-07-16
  • 作者简介:

    作者简介:王少剑(1986-), 男, 河南驻马店人, 博士, 主要研究方向为为经济地理、城市与区域规划。E-mail:1987wangshaojian@163.com

  • 基金资助:
    国家自然科学基金项目(41401164)

Spatial spillover effects and multi-mechanism for regional development in Guangdong province since 1990s

Shaojian WANG1,2,3(), Yang WANG4(), Yabo ZHAO5   

  1. 1. School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
    2 Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    3. University of Chinese Academy of Sciences, Beijing 100049, China
    4. Guangzhou Institute of Geography, Guangzhou 510070, China
    5. School of Geography, Beijing Normal University, Beijing 100875, China
  • Received:2014-09-18 Revised:2015-02-13 Online:2015-06-20 Published:2015-07-16
  • Supported by:
    National Natural Science Foundation of China, No.41401164

摘要:

采用尺度方差、核密度估计、空间马尔科夫链和地理加权回归对1990-2010年广东省区域经济发展的溢出效应及其驱动因素进行了时空动态分析。① 尺度方差研究表明,在3个尺度分析的基础上发现县级尺度对整个区域经济差异的贡献份额最大,因此是空间溢出效应研究的核心尺度;② 核密度估计研究表明,1990-2010年间县域人均GDP差距呈不断扩大趋势,2000-2010年相比于1990-2000年人均GDP差距幅度更大,使得空间溢出更为明显;③ 空间马尔科夫链研究表明,在县域经济发展过程中存在空间溢出效应,若以较富裕地区为邻,受到的溢出效应是正向的,县域经济向上转移的概率增加,向下转移的概率减小,反之亦然。④ 空间滞后回归和地理加权回归研究表明,全球化、简政放权和固定资产投资是广东省空间溢出效应的三个核心驱动因素;市场化、城镇化水平和储蓄水平是辅助理解其空间溢出效应的驱动因素。

关键词: 尺度方差, 核密度估计, 空间溢出效应, 空间马尔科夫链, 地理加权回归, 广东省

Abstract:

Under the background of global economic integration, regional economic growth is not isolated in geographical space. Economic growth relies on both internal and external factors. At the regional level, global economic integration shows the form of regional and local economic cooperation and integration. In the open economic system, regions struggle for more benefits through adjusting local development policies. Propelled by the new round of economic growth and urbanization, China's regional economic development presents a trend of much more profound regional cooperation. Therefore, this paper intends to explore the spatial spillover effects of regional economic growth by analyzing the case of Guangdong province from 1990 to 2010. Located in South China, Guangdong has witnessed dramatic development since the reform and opening-up started, and has become the largest economic region in China. However, behind its economic success, it is facing great challenges arising from unbalanced growth and intensified social injustice. Generally, Guangdong can be divided into four parts, namely, the Pearl River Delta, eastern Guangdong, western Guangdong and northern Guangdong, among them, the Pearl River Delta developed much better and faster. This is because the Pearl River Delta region attracted more capital investments and human resources with better natural resources, location conditions and supporting policies. As a result, increasing regional inequality and differences threatens national unity and social stability to some extent. Hence, regional disparity becomes an important issue in Guangdong's geographical research, as well as in regional development studies. In this paper, the scale variance analysis and statistics showed that the regional development at the county level made the greatest contribution among the three scales of county, municipality and region. The Kernel density estimation indicated that there was an increasing inequality in GDP per capita at county level from 1990 to 2010. Moreover, the inequality in 2000-2010 was larger than that in 1990-2000. The spatial Markov chain analysis revealed that the spatial spillover effects did exist in economic development at county-level, which means, if a county is adjacent to a richer county, its economy has a relatively high possibility to increase, and vice versa. The spatial lag regression model and the geographically weighted regression analyses indicated that globalization, decentralization and investments were the core driving forces of Guangdong's spatial spillover effects, and marketization, urbanization and savings were the secondary driving forces for increasing the regional inequality.

Key words: scale variance, Kernel density estimation, spatial spillover effect, spatial Markov chain, geographically weighted regression, Guangdong province