1990年来广东区域发展的空间溢出效应及驱动因素

doi:10.11821/dlxb201506010

Abstract

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

Shaojian WANG, Yang WANG, Yabo ZHAO. Spatial spillover effects and multi-mechanism for regional development in Guangdong province since 1990s[J].Acta Geographica Sinica, 2015, 70(6): 965-979.

Figures/Tables 10

Fig. 1

Fig. 2

Fig. 3

Tab. 1

Fig. 4

Fig. 5

Tab. 2

Tab. 3

Results of overall regression analyses in 1996 and 2010

OLS 模型
1996						2010
		系数	标准差	t/z值	P值 (>\|t\|)	系数	标准差	t/z值	P值(>\|t\|)
(截距)		3.453e-02	2.324e-02	1.235	5.914e-03	4.466e-02	1.609e-02	2.774	6.779e-03
全球化		6.654e-01	1.647e-01	1.546	4.016e-01	8.769e-01	1.243e-01	0.464	6.437e-01
市场化		4.145e-01	3.368e-01	2.683	1.402e-03	5.078e-01	2.494e-01	3.238	1.707e-03
简政放权		7.567e-01	1.643e-01	0.321	3.467e-01	4.080e-01	1.181e-01	0.679	4.987e-01
投资水平		4.473e-01	2.874e-01	4.124	1.576e-03	6.621e-01	2.167e-01	3.054	2.999e-03
城镇化		1.214e-01	3.871e-02	3.543	3.265e-04	1.508e-01	4.078e-02	3.697	3.829e-04
储蓄水平		2.231e-01	2.648e-01	3.678	1.863e-03	2.975e-01	2.083e-01	3.348	1.206e-03
1996——Adjusted R²：0.7416,F统计：41.5576,p值：2.53632e-11 2010——Adjusted R²：0.8216,F统计：53.4372,p值：3.76843e-12
空间残差模型
(截距)	4.241e-02		1.647e-02	2.618	3.104e-03	4.387e-02	1.503e-02	2.917	3.525e-03
全球化	5.876e-02		1.206e-01	0.7065	6.471e-01	6.09e-02	1.192e-01	0.5038	0.6143794
市场化	7.286e-01		2.813e-01	3.904	5.023e-04	8.287e-01	2.377e-01	3.4856	0.0004911
简政放权	7.743e-01		2.173e-01	3.84213	5.275e-04	7.147e-01	2.076e-01	3.44286	0.0005757
投资水平	1.659e-01		1.123e-01	0.7963	4.874e-01	8.590e-02	1.108e-01	0.77512	0.4382686
城镇化	2.468e-01		4.002e-02	3.5742	1.926e-04	1.468e-01	3.908e-02	3.756601	0.0001723
储蓄水平	-6.309e-01		1.694e-01	-3.2618	2.214e-04	-7.39e-01	1.969e-01	-3.712067	0.0002056
1996——Lambda：0.7424532,拉格朗日乘数检验：18.372,p值：0.000763,似然估计：66.893746(残差模型),AIC：77.678 (OLS:89.781),拉格朗日乘数检验：5.5314,p值:0.0967 2010——Lambda：0.7722286,拉格朗日乘数检验：24.864,p值：0.0000456,似然估计：98.551733(残差模型),AIC：61.657 (OLS:86.564),拉格朗日乘数检验：7.1662,p值：0.1058
空间滞后模型
(截距)	2.865e-02		2.513e-02	1.765	4.254e-02	3.269e-02	1.639e-02	1.994	4.614e-02
全球化	6.234e-02		1.781e-01	1.013	6.001e-01	7.582e-01	1.160e-01	0.648	5.160e-01
市场化	4.176e-01		2.456e-01	2.842	3.354e-02	5.640e-01	2.620e-01	2.154	3.100e-02
简政放权	4.982e-01		3.243e-01	2.687	2.902e-02	4.886e-01	2.120e-01	2.298	2.100e-02
投资水平	3.962e-01		1.675e-01	1.021	3.321e-01	4.903e-01	1.110e-01	0.803	4.210e-01
城镇化	1.302e-01		3.167e-02	2.242	1.345e-04	1.470e-01	3.800e-02	3.812	1.377e-04
储蓄水平	3.331e-01		1.536e-01	3.146	2.123e-04	3.230e-01	1.970e-01	3.659	2.542e-04
1996——Rho：0.6248,拉格朗日乘数检验：33.679,p值：0.000831,似然估计：89.2768(空间滞后模型),AICs：62.431(OLS:89.781),拉格朗日乘数检验：28.799,p值：0.000001564 2010——Rho：0.5436, 拉格朗日乘数检验：35.672,p值：0.0001450,似然估计：100.534(空间滞后模型),AICs：56.468(OLS:86.564),拉格朗日乘数检验：31.644,p值：0.0003241

Tab. 3

Tab. 4

Tab. 5

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	n	P(≤57.4%)	L(57.5%~79.6%)	D(79.7%~103.7%)	R(≥103.8%)
1990-2010
P	428	0.943	0.057	0.000	0.000
L	441	0.106	0.841	0.053	0.000
D	433	0.000	0.082	0.881	0.037
R	431	0.000	0.000	0.034	0.966
1990-2000
P	200	0.870	0.130	0.000	0.000
L	281	0.084	0.855	0.061	0.000
D	257	0.000	0.078	0.875	0.047
R	251	0.000	0.000	0.032	0. 968
2001-2010
P	228	0.957	0.043	0.000	0.000
L	160	0.124	0.826	0.050	0.000
D	176	0.000	0.080	0.903	0.017
R	180	0.000	0.000	0.017	0.983

1990-2000							2001-2010
		n	P	L	D	R	n	P	L	D	R
P	P	58	0.928	0.072	0.000	0.000	176	0.976	0.024	0.000	0.000
	L	20	0.180	0.785	0.035	0.000	27	0.176	0.769	0.055	0.000
	D	12	0.000	0.083	0.917	0.000	34	0.000	0.056	0.871	0.073
	R	5	0.000	0.000	0.000	1.000	6	0.000	0.000	0.000	1.000
L	P	82	0.842	0.158	0.000	0.000	33	0.944	0.056	0.000	0.000
	L	109	0.112	0.854	0.034	0.000	97	0.093	0.876	0.031	0.000
	D	87	0.000	0.044	0.893	0.063	24	0.000	0.042	0.917	0.041
	R	41	0.000	0.000	0.036	0.964	16	0.000	0.000	0.063	0.937
D	P	54	0.827	0.173	0.000	0.000	15	0.867	0.133	0.000	0.000
	L	137	0.053	0.891	0.056	0.000	30	0.099	0.866	0.005	0.000
	D	90	0.000	0.100	0.867	0.033	107	0.000	0.103	0.889	0.018
	R	52	0.000	0.000	0.044	0.956	37	0.000	0.000	0.027	0.973
R	P	6	1.000	0.000	0.000	0.000	4	0.750	0.250	0.000	0.000
	L	15	0.067	0.863	0.067	0.000	6	0.167	0.833	0.000	0.000
	D	68	0.000	0.051	0.915	0.034	11	0.000	0.000	0.909	0.091
	R	153	0.000	0.000	0.007	0.993	121	0.000	0.000	0.008	0.992

GWR模型的非平稳性检测, 1996
	截距	全球化	市场化	简政放权	投资水平	城镇化	储蓄水平
F统计	12.647	1.534	3.453	1.504	0.789	0.942	1.897
分子自由度	16.532	12.785	15.864	20.547	11.632	16.275	24.675
分母自由度	66.091	66.091	66.091	66.091	66.091	66.091	66.091
p值	0.000	0.000	0.005	0.001	0.153	0.435	0.546
GWR模型的非平稳性检测, 2010
F统计	25.324	2.628	1.986	2.593	3.024	4.165	0.541
分子自由度	22.578	9.583	5.585	9.041	7.645	5.465	18.927
分母自由度	58.234	58.234	58.234	58.234	58.234	58.234	58.234
p值	0.000	0.005	0.100	0.261	0.104	0.542	0.741

非平稳性模型
1996					2010
	系数	标准差	t/z值	P值 (>\|t\|)	系数	标准差	t/z值	P值(>\|t\|)
全球化	0.0053217	0.0107864	0.886	0.0345	0.007435	0.2068423	0.569	0.741
市场化	0.0013004	0.0005876	2.378	0.0146	0.003142	0.0009826	1.133	0.258
简政放权	0.0051657	0.0041095	4.322	0.0237	0.005634	0.0167452	1.254	0.692
投资水平	0.0039412	0.0008543	3.578	0.0201	0.004297	0.0006754	0.679	0.347
城镇化	0.0014864	0.0002876	5.629	0.5346	0.002657	0.0002384	0.924	0.189
储蓄水平	0.0027542	0.0005233	4.714	0.8265	0.002988	0.0001678	0.832	0.326
1996—GWR 模型AICs：54.253 (空间滞后模型：62.431,OLS模型：89.781)
2010—GWR 模型AICs：24.472 (空间滞后模型：56.468,OLS模型：86.564)

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

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