区域经济增长的同群效应——来自中国城市数据的经验证据

doi:10.11821/dlyj020190300

摘要/Abstract

摘要：

厘清中国区域经济发展中多样化的空间相互作用,对于探索新时期区域协调发展的新理念具有重要意义。根据增长极理论和中心地理论构建空间计量模型,以中国260个地级及以上城市为研究对象,研究不同收入水平城市间的同群效应,从新的视角解释区域协调发展的内在动力。研究发现：高收入城市通过正向同群效应对邻近中等收入城市的经济增长产生了带动作用,通过负向同群效应对邻近陷阱城市的经济增长产生了抑制作用,中国城市之间未完全发挥自上而下的辐射带动作用;中等收入城市对高收入城市的经济增长、陷阱城市对中等收入城市的经济增长均具有正向同群效应,中国城市之间存在着自下而上的经济增长促进作用;同等收入水平城市间的经济增长通过正向同群效应相互促进。进一步的作用机制检验表明：同群效应的产生更多是源于分权体制下的“标尺竞争”,其中学习和竞争机制在不同收入水平城市内部的作用效果存在明显异质性。最后,从实施多中心空间战略、构建新型城市合作模式、加强基础设施建设、完善政绩考核体系等方面提出了实现区域协调发展的政策启示。

关键词: 区域经济增长, 同群效应, 不同收入水平, 标尺竞争, 区域协调发展

Abstract:

Clarifying the diversified spatial interaction in China's regional economic development is of great significance to explore the new concept of regional coordinated development in the new era. This paper constructs the spatial econometric model based on growth pole and central place theories, and studies the peer effects of urban areas in different income levels taking 260 prefecture-level cities in China as the research object, and explains the internal motive force of regional coordinated development from a new perspective. The results show that: (1) High-income cities have a driving effect on the economic growth of neighboring middle-income cities through positive peer effects, and have a dampening effect on the economic growth of neighboring trap cities through negative peer effects. The top-down radiation action between Chinese cities is not fully utilized. (2) Middle-income cities have positive peer effects on the economic growth of high-income cities, and trap cities have positive peer effects on the economic growth of middle-income cities, and there is a bottom-up economic growth promotion between our cities. (3) Economic growth between cities at equal income levels is mutually reinforced by positive peer effects. Further study finds that peer effects are largely due to the yardstick competition under decentralized fiscal system, and there is a significant heterogeneity in the effects of learning and competition mechanisms within cities with different income levels. Finally, the policy enlightenment of realizing regional coordinated development is put forward from the aspects of implementing a multi-central space strategy, building a new type of urban cooperation model, strengthening the infrastructure construction, and improving the performance evaluation system.

Key words: regional economic growth, peer effects, different income levels, yardstick competition, regional coordinated development

石磊, 陈乐一, 李玉双. 区域经济增长的同群效应——来自中国城市数据的经验证据[J]. 地理研究, 2020, 39(4): 853-864.

SHI Lei, CHEN Leyi, LI Yushuang. Peer effects of regional economic growth: Empirical evidence from data of Chinese cities[J]. GEOGRAPHICAL RESEARCH, 2020, 39(4): 853-864.

图/表 6

表1

增长收敛模型回归估计结果"

变量	模型1		模型2		模型3
变量	参数估计	t值	参数估计	t值	参数估计	t值
$ln y i t 0$	-0.095^***	-23.36	-0.146^***	-18.26	-0.272^***	-12.27
Hr			0.040^***	5.01	0.016^**	2.43
K			0.088^***	5.08	0.092^***	4.49
-cons	1.036^***	25.83	1.305^***	21.32	2.527^***	12.52
地区固定	是		是		是
时间固定	否		否		是
R²	0.169		0.199		0.294
F值	545.802		204.900		67.010

表1

图1

表2

不同收入水平城市的估计结果"

变量	模型1：W_d（R）		模型2：W_d（E）		模型3：We
变量	参数估计	t值	参数估计	t值	参数估计	t值
$ln y i t 0$	-0.055^***	-6.37	-0.127^***	-17.06	-0.072^***	-7.77
Hr	0.025^***	3.87	0.047^***	7.29	0.031^***	4.38
K	0.052^***	4.55	0.067^***	4.93	0.082^***	6.02
Tech	0.015^***	3.08	0.005	0.93	0.016^**	2.43
Open	-0.091	-0.76	-0.027	-0.19	0.060	0.47
高→低
g^HM	0.733^**	2.12	17.039^***	3.49	1.493^**	2.23
g^HL	-1.915^*	-1.73	-60.907^***	-4.13	-27.677^**	-2.41
g^ML	0.530	1.63	-1.385^***	-6.50	0.474^***	2.74
低→高
g^MH	0.692^***	3.96	9.295^**	2.50	0.726^***	3.05
g^LH	2.026^*	1.75	-29.639	-1.36	-3.024^**	-2.04
g^LM	1.744^***	3.41	0.993^***	12.69	2.109^***	4.92
同等收入
g^HH	1.304^***	4.62	1.544	0.82	1.156^***	6.58
g^MM	0.847^***	6.67	3.534^***	2.67	0.840^***	7.15
g^LL	2.524^***	5.03	29.388^***	3.48	1.757^***	9.07
R²	0.382		0.267		0.305
F值	83.798		99.057		67.252

表2

表3

表4

表5

参考文献 29

[1]	Manski C F . Economic analysis of social interactions. Journal of Economic Perspectives, 2000,14(3):115-136.
[2]	Marotta L . Peer effects in early schooling: Evidence from Brazilian primary schools. International Journal of Educational Research, 2017, ( 82):110-123.
[3]	陆铭, 蒋仕卿, 陈钊 , 等. 摆脱城市化的低水平均衡:制度推动、社会互动与劳动力流动. 复旦学报: 社会科学版, 2013,55(3):48-64.
	[ Lu Ming, Jiang Shiqing, Chen Zhao , et al. Escaping the low-equilibrium of urbanization: Institutional push, social interaction and labor migration. Fudan Journal: Social Sciences Edition, 2013,55(3):48-64.]
[4]	McIntosh C, Alegria T, Ordóñez G , et al. The neighborhood impacts of local infrastructure investment: Evidence from urban Mexico. American Economic Journal: Applied Economics, 2018,10(3):263-86.
[5]	Dimmock S G, Gerken W C, Graham N P . Is fraud contagious? Coworker influence on misconduct by financial advisors. Journal of Finance, 2018,73(3):1417-1450.
[6]	邓慧慧, 赵家羚 . 地方政府经济决策中的同群效应. 中国工业经济, 2018, ( 4):59-78.
	[ Deng Huihui, Zhao Jialing . Peer effects in economic decision-making of China's local governments. China Industrial Economics, 2018, ( 4):59-78.]
[7]	Sacerdote B . Peer effects with random assignment: Results for Dartmouth roommates. Quarterly Journal of Economics, 2001,116(2):681-704. doi: 10.1162/00335530151144131
[8]	Groenewold N, Lee G, Chen A . Inter-regional spillovers in China: The importance of common shocks and the definition of the regions. China Economic Review, 2008,19(1):32-52. doi: 10.1016/j.chieco.2007.10.002
[9]	Ojede A, Atems B, Yamarik S . The direct and indirect (spillover) effects of productive government spending on state economic growth. Growth and Change, 2018,49(1):122-141. doi: 10.1111/grow.2018.49.issue-1
[10]	Ke S, Feser E . Count on the growth pole strategy for regional economic growth? Spread-backwash effects in Greater Central China. Regional Studies, 2010,44(9):1131-1147. doi: 10.1080/00343400903373601
[11]	Chen A, Partridge M D . When are cities engines of growth in China? Spread and backwash effects across the urban hierarchy. Regional Studies, 2013,47(8):1313-1331. doi: 10.1080/00343404.2011.589831
[12]	孙斌栋, 丁嵩 . 大城市有利于小城市的经济增长吗? 来自长三角城市群的证据. 地理研究, 2016,35(9):1615-1625. doi: 10.11821/dlyj201609002
	[ Sun Bindong, Ding Song . Do large cities contribute to economic growth of small cities? Evidence from Yangtze River Delta in China. Geographical Research, 2016,35(9):1615-1625.] doi: 10.11821/dlyj201609002
[13]	陈玉, 孙斌栋 . 京津冀存在“集聚阴影”吗? 大城市的区域经济影响. 地理研究, 2017,36(10):1936-1946. doi: 10.11821/dlyj201710010
	[ Chen Yu, Sun Bindong . Does “agglomeration shadow” exist in Beijing-Tianjin-Hebei region? Large cities' impact on regional economic growth. Geographical Research, 2017,36(10):1936-1946.] doi: 10.11821/dlyj201710010
[14]	覃成林, 杨霞 . 先富地区带动了其他地区共同富裕吗? 基于空间外溢效应的分析. 中国工业经济, 2017, ( 10):44-61.
	[ Qin Chenglin, Yang Xia . Have the earlier prosperous regions driven the other regions to be rich?A perspective of spatial spillover effects. China Industrial Economics, 2017, ( 10):44-61.]
[15]	Perroux F . Economic space: Theory and applications. The Quarterly Journal of Economics, 1950,64(1):89-104. doi: 10.2307/1881960
[16]	Myrdal G . Economic Theory and Underdeveloped Regions. London: Gerald Duckworth and Co, 1957.
[17]	Hirschman A. The Strategy of Economic Development. New Haven: Yale University Press, 1958.
[18]	Christaller W. Central Places in Southern Germany. Translated by Chang Zhengwen, Huang Xingzhong. Beijing: The Commercial Press, 1998: 19-32.
[19]	Losch A . The Economics of Location. New Haven: Yale University Press, 1954: 1-15.
[20]	Berry B J L, Garrison W L . The functional bases of the central place hierarchy. Economic Geography, 1958,34(2):145-154. doi: 10.2307/142299
[21]	柯善咨 . 扩散与回流: 城市在中部崛起中的主导作用. 管理世界, 2009, ( 1):61-71.
	[ Ke Shanzi . Spread and backwash: The leading role of cities in the rise of central China. Management World, 2009, ( 1):61-71.]
[22]	柯善咨 . 中国城市与区域经济增长的扩散回流与市场区效应. 经济研究, 2009, ( 8):85-98.
	[ Ke Shanzi . Spread-backwash and market area effects of urban and regional growth in Chin. Economic Research Journal, 2009, ( 8):85-98.]
[23]	万良勇, 梁婵娟, 饶静 . 上市公司并购决策的行业同群效应研究. 南开管理评论, 2016,19(3):40-50.
	[ Wan Liangyong, Liang Chanjuan, Rao Jing . Industry peer effect in M&A decisions of China's listed companies. Nankai Business Review, 2016,19(3):40-50.]
[24]	周黎安 . 中国地方官员的晋升锦标赛模式研究. 经济研究, 2007, ( 7):36-50.
	[ Zhou Lian . Governing China's local officials: An analysis of promotion tournament model. Economic Research Journal, 2007, ( 7):36-50.]
[25]	林光平, 龙志和 . 空间经济计量: 理论与实证. 北京: 科学出版社, 2014: 74-77.
	[ Lin Guangping, Long Zhihe . Spatial Econometrics: Theory and Demonstration Beijing: Science Press, 2014: 74-77.]
[26]	Aiyar S, Duval R, Puy D , et al. Growth slowdowns and the Middle-Income Trap. Japan and the World Economy, 2018,48:22-37. doi: 10.1016/j.japwor.2018.07.001
[27]	林志帆 . “中等收入陷阱”存在吗? 基于增长收敛模型的识别方法. 世界经济研究, 2014, ( 11):10-15.
	[ Lin Zhifan . On the existence of the "Middle-Income Trap": An identification method based on growth convergence model. World Economy Studies, 2014, ( 11):10-15.]
[28]	王守坤, 任保平 . 中国省级政府间财政竞争效应的识别与解析: 1978—2006年. 管理世界, 2008, ( 11):32-43.
	[ Wang Shoukun, Ren Baoping . The identification and analysis of the effect of the financial competition between China's provincial governments between 1978 and 2006. Management World, 2008, ( 11):32-43.]
[29]	张学良 . 在区域协调发展中持续释放经济发展新动能. 光明日报, 2019-05-24(11).
	[ Zhang Xueliang . Continue to release new kinetic energy development in regional coordinated development. Guangming Daily, 2019-05-24(11).]

变量	（1）内部学习		（2）外部示范		（3）招商引资竞争		（4）财税竞争
变量	参数估计	t值	参数估计	t值	参数估计	t值	参数估计	t值
Internal	4.4223^***	3.8847
External			-0.1307	-0.2708
Invest					4.2296	0.3045
Fiscal							0.0329	0.0901
控制变量	Y		Y		Y		Y
R²	0.1509		0.1134		0.1134		0.1134
F值	24.8391		25.5492		25.9141		32.1059

变量	（1）内部学习		（2）外部示范		（3）招商引资竞争		（4）财税竞争
变量	参数估计	t值	参数估计	t值	参数估计	t值	参数估计	t值
Internal	2.1766^***	8.0193
External			0.4913	1.1273
Invest					30.3433^***	2.6796
Fiscal							-2.8807^**	-4.9761
控制变量	Y		Y		Y		Y
R²	0.2670		0.2403		0.2459		0.2683
F值	113.9499		107.2311		100.9682		104.1406

变量	（1）内部学习		（2）外部示范		（3）招商引资竞争		（4）财税竞争
变量	参数估计	t值	参数估计	t值	参数估计	t值	参数估计	t值
Internal	5.1008^***	13.8299
External			0.3354^*	1.8907
Invest					-0.7718	-0.0678
Fiscal							-0.0220	-0.2419
控制变量	Y		Y		Y		Y
R²	0.2294		0.1082		0.1074		0.1074
F值	103.6193		82.8320		92.3094		84.6474