This paper empirically studies the effect of central city economic growth on the peripheral city economic growth in urban agglomeration. Using the panel data of 120 Chinese cities from 2000 to 2012, we find that the central city economic growth significantly and substantially increases the peripheral city economic growth. These findings not only enrich the relative researches on Chinese urban agglomeration, but also strengthen the understanding of the key role of the central city under the background of promoting urbanization in China.
In recent years, with the acceleration of China’s urbanization process, the topic of promoting the development of urban agglomerations has received increasing attention. In the Eleventh Five-Year Plan and the Twelfth Five-Year Plan, the central government has successively proposed that “the urban agglomerations should be one of the main forms of urbanization” and “rely on big cities and focus on small and medium sized cities, gradually forming the urban agglomerations which have strong economic radiation effect. In the National New Urbanization Plan (2014-2020), it also emphasized the development of urban agglomerations with high agglomeration efficiency and strong functional complementarity.
Urban agglomeration is a highly developed spatial form of integrated cities. It occurs when the relationships among cities shift from mainly competition to both competition and cooperation (Fang and Yu, 2017 [
This paper exploits the panel data of prefecture-level cities in China from 2000 to 2012, using two-way fixed effects regression model to empirically examine how the economic growth of the central city within the urban agglomeration affects the economic growth of the peripheral cities. We find that the economic growth of the central city has a significant positive radiation effect on the economic growth of peripheral cities and this effect has weakened with the extension of geographical radius. The basic conclusion is still valid after a series of robustness tests. The marginal contribution of this paper lies in: it enriches the research on urban agglomerations in the field of economics and gives empirical evidence for the radiation effects of the central city within urban agglomerations on peripheral cities. The empirical results of this paper also provide a possible answer for the question about whether giving priority to the development of large cities or small and medium-sized cities. The development of small and medium-sized cities must actually rely on the development of large cities and take advantage of the external radiation function of large cities to promote the economic growth and upgrade the industrial structure.
The remaining parts of this paper are organized as follows: the second part reviews the relevant literature; the third part proposes the theoretical hypothesis; the fourth part is the empirical strategy and data sources; the fifth part gives the basic empirical results; finally, it is the conclusion and policy implications.
The source of urban economic growth has always been one of the most concerned topics in the field of economics. A number of studies have already explained the driving forces behind urban economic growth from the perspective of traditional factors of economic growth. These factors include physical capital (Xu and Shu, 2004 [
To understand the impact of space on urban economic growth, the first question to answer is: Why are economic activities concentrated within cities? For this issue, some scholars try to give answers based on the geographical determinism perspective. They believe that location conditions, climate and other geographical factors have important influence on regional economic and industrial development (Goldstein and Moses 1975 [
Cities do not isolate from the others. The development of agglomeration economy has enabled cities with similar geographical locations to gradually form urban agglomerations around some certain core cities. The formation and development of urban agglomerations is driven by the economic forces and this economic power is essentially consistent with the local market effect and the congestion effect mentioned in the core―periphery theory of New Economic Geography. According to the core―periphery theory, under the interaction between the two effects, the market potential of a city will show a cubic curve pattern as the distance of this city to the central city of the region increases in a single central urban system. In other words, as the distance of the peripheral city to the central city increases, the market potential of the peripheral city will drop first. When both cities reach at a certain distance, the market potential will gradually increase. However, as the distance continues to increase, the regional market potential will decline in the end (Fujita and Krugman, 1995 [
Recently, some scholars have begun to discuss the impact of urban agglomeration on regional economic growth and industrial structure. Wu and Liu (2008) [
A few scholars also discussed the issue of the division of labor within the urban agglomeration. Wei (2007) [
The literature has consistently verified that the development of urban agglomerations will have an impact on urban economic growth. Optimizing the industrial structure of cities within urban agglomerations and accelerating the process of regional integration are essential for exerting the advantages of urban agglomerations. However, respect to the empirical literature on Chinese urban agglomeration at present, only a few researches are based on the core―periphery theory of New Economic Geography to study the radiation range of urban agglomerations. The literature only takes the port cities into consideration and did not consider other non-portal core cities.
A number of literatures have examined the impact of the development of urban agglomeration on urban economic performance by measuring the degree of urban agglomerations and analyzed the internal mechanisms from the perspective of transport infrastructure, industrial structure and regional integration (Portnov, 2006 [
Due to lack comprehensive empirical studies on urban agglomerations, this paper tries to examine the impact of the economic growth of the central cities on the economic growth of peripheral cities within the top ten urban agglomerations in China. The reason why we take the central and peripheral cities within the urban agglomeration as the research unit is that respect to the current spatial distribution of economic agglomeration in China, economic activities are mainly concentrated in the central cities and other urban areas surrounding the central cities and the provincial economy divided by administrative boundaries has gradually transformed into urban agglomeration economy.
We believe that the economic growth of central cities will promote the economic growth of peripheral cities within urban agglomerations. The main reason stems from the following logic. From the perspective of the development of urban agglomerations, the relationship between central cities and peripheral cities is essentially faced with two kinds of forces, namely agglomeration effect and radiation effect. On one hand, due to the huge market size of the central city, the scale effect will enable producers to acquire inputs from a wider range of sources and reduce the production costs. At the same time, enterprises and labor will be able to get a more appropriate matching and the speed of knowledge diffusion will also become more rapid, so various factors of production will tend to shift to the central city, the economic growth of the central city will be faster than the peripheral cities. Driven by the economies of scale and agglomeration effects, the central city has become the center of factor allocation, industrial transformation and technological innovation in the region. What’s more, it is important that the external radiation effect of central cities has begun to exert. The reason is that the central city has certain advantages in terms of labor productivity, technology and information compared with the peripheral cities. The central city makes use of different channels, such as the labor shifting, the division in the industry and the spread of knowledge and technology. In particular, from the perspective of the industrial structure, the radiation effect may be exerted through the development of the secondary industry in the central city. The reason is that China is currently in the stage of economic agglomeration and industrial structure transformation. Although the tertiary industry is showing a trend of rapid development, the secondary industry still occupies a large proportion in the national economy. The contribution of secondary industry to economic growth is still very obvious. Therefore, under the background of industrial structure transformation, the optimization and development of the secondary industry by the central city will not only contribute to further enhance the level of its own economic development but also enable the peripheral cities to develop their associated industries based on the comparative advantages. As a result, it promotes the economic growth of the peripheral cities. In summary, we propose the following theoretical hypothesis.
Hypothesis: Ceteris paribus, the economic growth of the central city will promote the economic growth of the peripheral cities.
The data of 120 cities in top ten urban agglomerations of China from 2000-2012 is collected from different statistical yearbooks. We only use the data for the years 2000-2012 mainly because the data of the statistical yearbook was only updated to 2015 and the data of 2013 has some obvious mistakes. The data of city level variables including nominal GDP per capita, nominal GDP, total population, the rate of investment, the rate of population growth come from China City Statistical Yearbook. The GDP deflator is calculated by China Statistical Yearbook. The geographic distance of cities is calculated by ArcGIS 10.2 based on map data provided by the National Basic Geographic Information System.
Urban economic growth will be affected by a number of economic and social factors. In this paper, we concerned about the relationship between economic growth of peripheral cities and the economic spillover effect of central cities. In order to examine this relationship, we first construct a variable that measures the degree of the radiation effect of the central city.
d i s t a n c e i t = ln r p g d p _ c j t ln d i s i j (1)
In Equation (1), the subscript i, j and t denotes the peripheral city, the central city and the year respectively. The variable lnrpgdp_c represents the logarithm of the real GDP per capita of the central city j in year t. The variable lndis represents the geographical distance between the central city j and the peripheral city i.
In order to test whether the economic growth of the central city will affect the economic growth of the peripheral city, this paper construct the following regression model based on the standard economic growth model:
ln r p g d p i t = β 0 + β 1 d i s t a n c e i t + β 2 ln r g d p i t − 1 + β 3 ln p o p i t − 1 + β 4 ln i n v i t − 1 + β 5 ln ( n i t − 1 + γ i t − 1 + δ i t − 1 ) + η i + λ t + ε i t (2)
In Equation (2), the subscript i and t represent city and year respectively. The explained variable lnrpgdp is the real GDP per capita of the peripheral city which is calculated by the nominal GDP per capita and the GDP deflator of the province. The core explanatory variable distance is a measure of GDP per capita in the city center with the change of the degree of geographical distance on the periphery of urban per capita GDP of influencing variables. In addition to the core explanatory variable, the empirical model also includes a set of variables that characterize city economic growth, namely, real GDP (rgdp), total population (pop), the rate of investment (inv), the rate of population growth (n), the rate of capital depreciation (δ) and the rate of technical advance (γ). In the empirical analysis, we suppose γ i t − 1 + δ i t − 1 = 1 . η i and λ t represent city and year fixed effects respectively. ε i t represents the random error term.
In order to examine the impact of the radiation effect of the central city on the economic growth of the peripheral city, we conducted a regression test based on the above empirical model.
Variables | OLS | OLS | FE | FE | |
---|---|---|---|---|---|
(1) | (2) | (3) | (4) | ||
distance | 0.9458*** | −0.1373*** | 1.8952*** | 1.4991*** | |
(0.073) | (0.033) | (0.236) | (0.210) | ||
l_lnrgdp | 0.8464*** | 0.4468*** | |||
(0.015) | (0.085) | ||||
l_lninv | 0.1571*** | 0.1587*** | |||
(0.030) | (0.038) | ||||
l_lnpop | −0.8041*** | −0.4491*** | |||
(0.025) | (0.070) | ||||
l_ln(n + γ + δ) | −0.7008*** | 0.5808 | |||
(0.251) | (0.381) | ||||
City FE | N | N | Y | Y | |
Year FE | N | N | Y | Y | |
N | 655 | 600 | 655 | 600 | |
R2 | 0.174 | 0.927 | 0.951 | 0.963 | |
a. Robust standard error in parentheses. *, **, and *** are statistically significant at the significance levels of 10%, 5%, and 1%, respectively.
coefficient of the core explanatory variable distance is significantly positive. In column 2, after adding a number of control variables, we find that the coefficient of the core explanatory variable distance is significantly negative at the 1% statistical level. We control the city and year fixed effects in column 3. The coefficient of the core explanatory variable distance is significantly positive at the 1% statistical level. In column 4, after adding the control variables and the city and year fixed effects, the core explanatory variable distance is still significantly positive at the 1% statistical level. The results show that under the empirical framework of standard economic growth model, the economic growth of the central city significantly stimulates the economic growth of the peripheral cities.
Further, we conduct several robustness tests based on the baseline regression results. First, in the previous baseline regression, we only set the geographic radius of the central city within a radius of 150 kilometers. To test whether this setting is robust, we try to extend the radiation radius of the central city to 200,250 and 300 kilometers.
Variables | 150 km | 200 km | 250 km | 300 km | |
---|---|---|---|---|---|
(1) | (2) | (3) | (4) | ||
distance | 1.4991** | 1.3552*** | 1.1875*** | 1.1932*** | |
(0.499) | (0.380) | (0.351) | (0.328) | ||
l_lnrgdp | 0.4468** | 0.5801*** | 0.6060*** | 0.6642*** | |
(0.176) | (0.126) | (0.122) | (0.128) | ||
l_lninv | 0.1587** | 0.1576** | 0.1322** | 0.0891*** | |
(0.051) | (0.050) | (0.043) | (0.026) | ||
l_lnpop | −0.4491*** | −0.5463*** | −0.5630*** | −0.5817*** | |
(0.078) | (0.074) | (0.078) | (0.088) | ||
l_ln(n + γ + δ) | 0.5808 | 0.4962 | 0.3529 | 0.2790 | |
(0.397) | (0.305) | (0.280) | (0.222) | ||
City FE | YES | YES | YES | YES | |
Year FE | YES | YES | YES | YES | |
N | 600 | 909 | 1134 | 1417 | |
R2 | 0.963 | 0.962 | 0.961 | 0.958 | |
a. Robust standard error in parentheses. *, **, and *** are statistically significant at the significance levels of 10%, 5%, and 1%, respectively.
radius of radiation to 200,250, and 300 kilometers, respectively. The results show that as the radius of radiation extends, the value of the coefficient of the core explanatory variable distance decreases, but it is still significantly positive at 1% level.
In addition, the empirical strategy also has some endogenous problems. In other words, the peripheral city which the economy scale is close to the central city may reversely have an effect on the economic growth of the central city. To solve the endogeneity, we try to calculate the average GDP of the central city and the peripheral city within the sample time period, and then compare the absolute value of the two cities one by one. The peripheral city which the average GDP is more than half or two thirds of the central city will be dropped from the sample.
The development of urban agglomerations reflects space agglomeration of global economic activity. It is also an important way to accelerate the process of urbanization in China. Based on the agglomeration effect and positive spatial externalities of urban agglomerations, the economic growth of the central city within
Variables | 150 km | 200 km | 250 km | 300 km | |
---|---|---|---|---|---|
(1) | (2) | (3) | (4) | ||
distance | 1.3873** | 1.2159*** | 1.0837** | 1.0970*** | |
(0.455) | (0.367) | (0.350) | (0.311) | ||
l_lnrgdp | 0.5040** | 0.6173*** | 0.6437*** | 0.7010*** | |
(0.174) | (0.120) | (0.114) | (0.115) | ||
l_lninv | 0.1395** | 0.1369** | 0.1106** | 0.0720*** | |
(0.047) | (0.042) | (0.037) | (0.020) | ||
l_lnpop | −0.5515*** | −0.6431*** | −0.6623*** | −0.6757*** | |
(0.091) | (0.072) | (0.066) | (0.060) | ||
l_ln(n + γ + δ) | 0.6613 | 0.5177 | 0.3722 | 0.2856 | |
(0.392) | (0.296) | (0.276) | (0.217) | ||
City FE | YES | YES | YES | YES | |
Year FE | YES | YES | YES | YES | |
N | 588 | 885 | 1086 | 1369 | |
R2 | 0.963 | 0.962 | 0.959 | 0.956 | |
a. Robust standard error in parentheses. *, **, and *** are statistically significant at the significance levels of 10%, 5%, and 1%, respectively.
urban agglomerations will have potential impact on the economic growth of peripheral cities. This paper exploits panel data of city level from 2000 to 2012 and empirically examines the influence of the economic growth of the central city on the economic growth of the peripheral cities within the urban agglomerations using the two-way fixed effects regression model. The study indicates that the economic growth of the central city has a significant positive effect on the economic growth of peripheral cities in urban agglomerations.
The findings of this paper have some policy implications. First of all, the policymakers should realize that the central city plays an important role in driving the overall economic development of urban agglomerations and coordinating regional economic integration, therefore they should further promote the agglomeration of capital, labor and other production factors to central city and improve the labor productivity of the city which will allow the central city to stimulate the economic growth and the economic structure upgrading of the peripheral cities. Secondly, it is necessary to attach great importance to the connectivity between the central city and the peripheral cities, strengthening the infrastructure construction and the provision of public services. Finally, based on the comparative advantages of cities, it is essential to reinforce the overall integration function of the core industries of the central city and lead the industries of peripheral cities in division and collaboration.
This paper also has some limitations. First, it only considers the situation of single-center city in the empirical analysis but ignores the situation of dual-center of multi-center cities. Secondly, this paper does not further explore the possible mechanisms underlying the positive radiation effect of the central city on the peripheral cities. The above limitations will become the direction of further research.
Wu, Z.Q. (2018) Do Central City Promote Economic Growth of Peripheral City? Evidence from Urban Agglomeration in China. Open Journal of Social Sciences, 6, 120-132. https://doi.org/10.4236/jss.2018.65010