广东省区域经济差异的多尺度与多机制研究

doi:10.13249/j.cnki.sgs.2014.010.1184

摘要/Abstract

摘要：

以广东省88个县域为基本单元,基于“多尺度和多机制”框架,综合运用了总体差异指数、空间自相关、空间多水平回归等方法,分析了广东省1990~2010年区域经济差异的时空动态演变。① 总体差异指数测度表明,20世纪90年代初期以来,广东省区域经济差异在地区尺度、地级尺度、县级尺度和城乡尺度均表现出不断增大的趋势,地理尺度和空间组织对区域经济差异有很大影响。② 基于GIS应用,空间自相关检测发现广东省在经济发展过程中存在空间集聚“俱乐部趋同”现象,潜在地加深了区域经济差异。③ 空间多水平回归分析表明,全球化、简政放权、固定资产投资是促使区域经济差异加剧的主要原因,而市场化在一定程度上缓和了区域经济差异,城乡分异和地形因素也是区域经济差异的影响因素,但显著性较低。

关键词: 区域经济差异, 多尺度与多机制, 空间自相关, 空间多水平回归, 广东省

Abstract:

Regional inequality is an important issue in geographical research and regional development studies. China is the largest developing country in the world and its economy has undergone rapid and continuous expansion since the Chinese economic reform in 1978. China has achieved great success in economic development with an annual growth rate at 9.9%. However, behind the economic success in China, the country also faces serious challenges arising from imbalanced growth and intensifying social injustice. Since regional inequality may threaten national unity and social stability, it is a hot issue in research internationally and domestically. Almost all previous studies of the regional inequality have transformed static, qualitative measurement into a dynamic and quantitative evaluation. Most of the research in China has focused on lateral comparisons at a national level, only a few have addressed the provincial level. Added this above, this article analyses the regional inequality in Guangdong Province from 1990 to 2010 and follows a GIS-based multi-scale and multi-mechanism framework. Conventional global inequality indexes, spatial autocorrelation and spatial multi-level regression are utilized in the article to examine the regional inequality in Guangdong Province. Conventional global inequality indexes (including Coefficient variance, Gini coefficient, Theil index) analysis reveal that since the early 1990s, the regional inequalities at county level, municipality level, regional level and urban-rural level are experiencing increasing tends and fluctuated change. Geographical scale and spatial organization play an important effect on regional inequality. Based on GIS, spatial autocorrelation finds that spatial agglomeration-"convergence club" exists in the process of economic growth of Guangdong, which is attributing to intensity the regional inequality. The spatial multi-level regression analysis reveals that globalization, decentralization and investment are the three important mechanisms for understanding the regional inequality in Guangdong Province, and marketization has remitted the regional inequality effectively. What′s more, urban-rural and geomorphology are also the elements of the regional inequality, but the impact is not significant.

Key words: regional inequality, multi-scale and multi-mechanism, spatial autocorrelation, spatial multi-level regression analysis, Guangdong Province

中图分类号:

F127

王少剑, 赵亚博, 王洋. 广东省区域经济差异的多尺度与多机制研究[J]. 地理科学, 2014, 34(10): 1184-1192.

Shao-jian WANG, Yang WANG, Ya-bo ZHAO. GIS-based Multi-scale and Multi-mechanism Research on Regional Inequality in Guangdong Province[J]. SCIENTIA GEOGRAPHICA SINICA, 2014, 34(10): 1184-1192.

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参考文献 53

[1]	中华人民共和国国家统计局. 中国统计年鉴(2011)[M]. 北京: 中国统计出版社, 2011.
[2]	李广东,方创琳. 中国区域经济增长差异研究进展与展望[J]. 地理科学进展, 2013, 32(7): 1102~1112.
[3]	Krugman P.Increasing returns and economic geography[J]. Journal of Political Economy, 1991, 99(3): 483-499.
[4]	Krugman P.The role of geography in development[J]. International Regional Science Review, 1999, 22(2): 483-499.
[5]	Krugman P.The new economic geography, now middle-aged[J]. Regional Studies, 2011, 45(1):1-7.
[6]	Fingleton B.Specification and testing of Markov chain models: an application to convergence in the European Union[J]. Oxford Bulletin of Economics and Statistics, 1997, 59(3):385-403.
[7]	Moore A.Rethinking scale as a geographical category: From analysis to practice[J]. Progress in Human Geography, 2008, 32(2): 203-225.
[8]	Brenner N.The limits to scale? Methodological reflections on scalar structuration[J]. Progress in Human Geography, 2001, 25(4): 591-614.
[9]	Rodríguez-Pose A, Ezcurra R.Does decentralization matter for regional disparities? A cross-country analysis[J]. Journal of Economic Geography, 2010, 10(5): 619-644.
[10]	刘慧. 区域差异测度方法与评价[J]. 地理研究, 2006, 25(4):710~718.
[11]	Wei Y H D, Yu D L, Chen X J. Scale, Agglomeration, and Regional Inequality in Provincial China[J]. Tijdschrift voor Economische en Sociale Geografie, 2011, 102(4): 406-425.
[12]	欧向军,沈正平,王荣成. 中国区域经济增长与差异格局演变探析[J]. 地理科学,2006,26(6):641~648.
[13]	Wang Y, Fang C L, Xiu C L, et al.A new approach to measurement of regional inequality in particular directions[J]. Chinese Geographical Science, 2012, 22(6): 705-717.
[14]	洪国志, 胡华颖, 李郇. 中国区域经济发展收敛的空间计量分析[J]. 地理学报, 2010,65(12): 1548~1558.
[15]	李小建, 乔家君. 20 世纪90 年代中国县际经济差异的空间分析[J]. 地理学报, 2001, 56(2): 136~145.
[16]	蒲英霞, 葛莹, 马荣华, 等. 基于ESDA的区域经济空间差异分析:以江苏省为例[J]. 地理研究, 2005, 24(6): 965~974.
[17]	孟斌, 王劲峰, 张文忠, 等. 基于空间分析方法的中国区域经济差异研究[J]. 地理科学,2005, 25(4):393~400.
[18]	李国平, 陈晓玲. 中国省区经济增长空间分布动态[J]. 地理学报, 2007, 62(10): 1051~1062.
[19]	林光平, 龙志和, 吴梅. 中国地区经济σ-收敛的空间计量实证分析[J]. 数量经济技术经济研究, 2006, 23(4): 14~21.
[20]	刘强. 中国经济增长的收敛性分析[J]. 经济研究, 2001, 36(6): 70~77.
[21]	关兴良,方创琳,罗奎. 基于空间场能的中国区域经济发展差异评价[J]. 地理科学,2012,32(9):1055~1065.
[22]	潘文卿. 中国区域经济差异与收敛[J]. 中国社会科学, 2010, (1): 72~84, 222~223.
[23]	沈坤荣, 马俊杰.中国经济增长的俱乐部收敛特征及其成因研究[J]. 经济研究, 2002, 37(1): 33~39.
[24]	张伟丽, 覃成林, 李小建. 中国地市经济增长空间俱乐部趋同研究: 兼与省份数据的比较[J]. 地理研究, 2011, 30(8): 1457~1470.
[25]	徐建华, 鲁凤, 苏方林, 等. 中国区域经济差异的时空尺度分析[J]. 地理研究, 2005, 24(1): 57~68.
[26]	管卫华, 林振山, 顾朝林. 中国区域经济发展差异及其原因的多尺度分析[J]. 经济研究, 2006, (7):117~125.
[27]	王洋, 修春亮. 1990~2008 年中国区域经济格局时空演变[J]. 地理科学进展, 2011, 30(8): 1037~1046.
[28]	仇方道,朱传耿, 佟连军,等. 淮海经济区县域经济差异变动的空间分析[J]. 地理科学, 2012, 32(9):56~63.
[29]	陈培阳, 朱喜钢. 基于不同尺度的中国区域经济差异[J].地理学报, 2012, 61(8): 1085~1079.
[30]	张锦宗,梁进社,朱瑜馨. 新疆县域经济分异特征、原因及对策探讨[J]. 地理科学, 2010, 30(4): 536~543.
[31]	Liao F L H F, Wei Y H D. Dynamics, space, and regional inequality in provincial China: A case study of Guangdong province[J]. Applied Geography, 2012, 35(1):71-83.
[32]	甄峰, 顾朝林, 沈建法,等.改革开放以来广东省空间极化研究[J]. 地理科学, 2000, 20(05): 403~410.
[33]	王铮, 葛昭攀. 中国区域经济发展的多重均衡态与转变前兆[J]. 中国社会科学, 2002, (4): 31~39, 204.
[34]	伍世代, 王强. 中国东南沿海区域经济差异及经济增长因素分析[J]. 地理学报, 2008, 63(2): 123~134.
[35]	刘清春, 王铮. 中国区域经济差异形成的三次地理要素[J]. 地理研究, 2009, 28(2): 430~440.
[36]	柯文前, 陆玉麒, 俞肇元, 等. 多变量驱动的江苏县域经济空间格局演化[J]. 地理学报, 2013,68(6): 802~812.
[37]	周春山, 王晓珊, 盛修深, 等. 1990s以来广东省县域经济差异研究[J]. 地域研究与开发,2011, 30(2): 27~32.
[38]	广东省统计局. 广东统计年鉴(1991~2011) [M]. 北京: 中国统计出版社, 1991~2011.
[39]	国家统计局国民经济综合统计司. 中国区域经济统计年鉴(2000~2011)[M]. 北京: 中国统计出版社, 2000~2011.
[40]	国家统计局城市社会经济调查司. 中国城市统计年鉴(1991~2011) [M]. 北京: 中国统计出版社, 1991~2011.
[41]	Williamson J G.Regional inequality and the process of national development: A description of the patterns[J]. Economic Development and Cultural Change, 1965, 13(4): 3-45.
[42]	Cowell, Frank A.Measuring Inequality(Second Edition)[M]. London: Prentice Hall/Harvester Wheatsheaf,1995.
[43]	Theil H.Economics and Theory [M]. Amsterdam: North Holland Publishing Company,1967.
[44]	Bo Y C, Li X F, Xue Z.Spatial data analysis and spatial models[J]. Geographical Research, 1999, 18(2):49-55.
[45]	Anselin L.The Moran scatterplot as an ESDA tool to assess local instability in spatial association[M]. London: Taylor & Francis, 1996.
[46]	Rasbash J, Steele F, Browne W J, et al.A user’s guide to MLwiN, v2.10[M].Bristol, U.K: Centre for Multilevel Modelling University of Bristol, 2009.
[47]	Ren Z P, Wang J F, Liao Y L, et al.Using spatial multilevel regression analysis to assess soil type contextual effects on neural tube defects[J]. Stochastic Environmental Research and Risk Assessment, 2013, 27: 1695~1708.
[48]	王少剑, 方创琳, 王洋,等. 广东省区域经济差异的方向及影响机制[J]. 地理研究, 2013, 32(12): 2244~2256.
[49]	陈修颖. 1990年以来浙江沿海区域差异及其成因分析. 地理科学, 2009, 29(1): 22~29.
[50]	宋丽智. 我国固定资产投资于经济增长关系再检验:1980~2010[J]. 宏观经济研究,2011, 11: 17~22.
[51]	萧琛. 论中国经济升级的理论内涵与政策取向—“简政放权”“民营新政”“城镇化”“美丽中国”[J].北京大学学报(哲学社会科学版), 2013, 50(5): 5~13.
[52]	樊纲, 王小鲁, 马光荣. 中国市场化进程对经济增长的贡献[J]. 经济研究, 2011, 9: 4~16.
[53]	张向妮. 我国固定资产投资对GDP影响的实证分析,[J].东方企业文化2011(4):36.

	One-level（县级）		Two-level（县级和核心-边缘）		Three-level（县级、核心-边缘和时间）
	回归系数	p值	回归系数	p值	回归系数	p值
全球化	0.490	0.035	0.450	0.005	0.414	0.013
简政放权	0.319	0.464	0.376	0.001	0.393	0.001
市场化	0.246	0.001	0.155	0.128	0.164	0.078
投资水平	0.168	0.001	0.393	0.000	0.361	0.001
城乡划分	0.056	0.103	0.079	0.005	0.097	0.007
地形因素	-0.438	0.166	-0.414	0.265	-0.328	0.376
-2loglikehood	121.627		105.913		94.533
Adjust-r²	0.902		似然比检测	<0.001	似然比检测	<0.001