Globalization and the dominance of large cities in contemporary China

doi:10.1016/S0264-2751(03)00031-3

Cities, Vol. 20, No. 4, p. 265–278, 2003  2003 Elsevier Science Ltd. All rights reserved. Printed in Great Britain 0264-2751/03 $ - see front matter

www.elsevier.com/locate/cities

Globalization and the dominance of large cities in contemporary China Simon X.B. Zhao* Department of Geography and International Centre for China Development Studies, 3/F Hui Oi Chow Science Building, The University of Hong Kong, Pokfulam Road, Hong Kong

Roger C.K. Chan Center for Urban Planning and Environmental Management, The University of Hong Kong, Pokfulam Road, Hong Kong

Kelvin T.O. Sit Department of Geography, The University of Hong Kong, Pokfulam Road, Hong Kong

Since the introduction of the economic reforms in late 1978, the Chinese urban system has experienced spectacular growth, accompanied by a rapid rise of urbanization from about 20% to more than 36%. Although restricted by government policy, the development of large cities prevailed in the 1980s, as shown in a previous study (Zhao and Zhang, 1995). This process of predominantly large cities growth appeared to continue in the 1990s, as is shown with further analysis and update on the issue, within the framework of globalization and other economic theories. Based on newly published demographic and economic data, the paper depicts the growth and concentration of population, foreign direct investment and employment availability in the large cities in contemporary China. This paper argues that in this globalization process, in which the fundamental economic rationales of increasing returns, urbanization economies and urbanization agglomeration prevail, large cities will continue to outperform the small cities and so the dominance of large cities will continue.  2003 Elsevier Science Ltd. All rights reserved. Keywords: Globalization, dominance, large cities, China

Introduction

from about 20% to more than 36% (Zhang and Zhao, 1998). In the 1980s, in the face of strong pressures for urban in-migration due to the relaxation of ruralurban migration control, policy was strictly controlling the size of large cities, rationally developing medium-sized cities, and vigorously developing small cities (Zhao and Zhang, 1995). However, in reality, China’s policy of controlling large city growth has not been effectively implemented, and large cities grew at a much faster pace in the past decade. Large city growth remains appreciable, due largely to these economic policies favouring large cities (Wei, 1997).1 We should take another perspective when looking

Urbanization—the concentration of population in centres—has accompanied economic development in many countries during their early stage of industrialization (Davis, 1968; Meyer, 1986). Chinese urban growth is unique, large and complex, and has provoked much scholarship. Before the period of economic reforms, China seemed to be in a stage of under-urbanization. By previous assessments, its urban development has been greatly influenced by national political ideologies and development strategies (Kirkby, 1985; Chan, 1994). Since the introduction of economic reforms in 1978, the Chinese urban system has experienced spectacular growth, accompanied by a rapid rise of urbanization levels

1 Wei (1997) suggests that urban reforms, open door policy, decentralization, uneven regional development policy and the development of the socialist market economy have all weakened the Chinese government’s ability to control over the growth of large and super-large cities.

∗ Corresponding author. Tel.: +852 2859 2838; fax: +852 2559 8994; e-mail: [email protected]

265

Globalization and the dominance of large cities in contemporary China: Simon X B Zhao et al.

at the progress of urban development in China in the 1990s—the continual unendorsed development of large cities under the effects of globalization. This paper provides a shift in theoretical framework from earlier work (e.g. Zhao and Zhang, 1995), to the study of the dominance of large cities under the framework of globalization and economic integration. With newly published demographic and economic indicators, collected from the China Urban Statistics Yearbook (Zhongguo Chengshe Tongji Nianjian), it is inferred that urban and economic development in China is concentrated in large cities. This paper will depict this newly emerging pattern of China’s urban development in the 1990s with detailed demographic and economic examinations. It argues that globalization results in urban agglomeration, leading to the concentration of people and firms in the largest cities. These play a leading role in the demographic and economic development of China.

Theoretical framework There are many theories assessing why large cities have advantages over smaller cities, but so far, few scholars have assessed that it is the ongoing globalization process that is contributing to the rise of large cities. The latter strengthens the increasing returns of production, allowing firms to produce proportionately more of the input injected into a production process, and strengthens urbanization economies, where firms in the large cities establish large scale production and lower their costs. Such lowering, and the increasing returns for firms, results in the agglomeration of people and firms in the large cities. At the same time, globalization results in the emergence of a knowledge based economy, where the implementation of new skills and technology in a production process results in increasing returns. The better opportunities for higher education in large cities also contribute to development. The impacts of globalization are increasingly extremely significant in contemporary urban development. It basically refers to the integration of national economies (OECD, 2000), and has brought about significant transformations of the old order (Scott et al., 2001). The elements of globalization which affect urban development are of: 앫 The globalization of business locations and production, 앫 The advancement in infrastructure for the transmission of information, 앫 The ease and convenience of processing financial transaction globally and the global transfer of capital, 앫 The importance of bringing in technological progress in the development of urban areas, and 앫 The huge and ever-increasing amounts of economic activity [that] now occur in extensive crossnational borders (Scott et al., 2001). 266

Firms, especially Multi-National Enterprises (MNEs), once they sell their products globally, will establish production plants in places where there is a significant demand for products, to reduce the reliance on production in the home country. It also reduces production and transportation costs. Firms choose to establish in a city where the highest competitive advantage can be achieved—that is, the ability to produce the most output at the lowest possible cost. Both an efficient labor force at the lower cost per output, and the good and adequate provision of infrastructure at the lowest cost, are prerequisites for cities to become globally competitive. This is part of the development of a global strategy for such firms, and MNEs especially give preference to cities that have international attachments. Large cities compete to achieve the highest competitive advantage and level of international attachment. Large cities under globalization can achieve increasing returns relative to smaller cities, when large-scale machinery or investment can be run more efficiently in a large city. The principle of indivisibility applies here, as, for example, the large-scale investment and infrastructure needed to establish telecommunications facilities will put small cities at a disadvantage. Large cities should have the resources to allow firms to establish large-scale plant and investments, as doubling the plant or investment should produce more than twice the output, therefore reducing average costs of production. A small city could not offer firms the land for plants or an investment environment suitable for large-scale investment. Large cities tend to provide the infrastructure, land, investment environment, and especially well-educated and skilled personnel, as they are the places where human capital accumulates (Lucas, 1988). These factors attract firms to establish their operations in the larger cities, at the expense of smaller cities. The increasing return to scale for firms located in the big cities also allows them to develop technology within the firms themselves. As Krugman (1991) has suggested, in a technology-driven world, technical progress will increase the scale of production, allowing even more profitability. Large cities are, therefore, clusters of activities generating a host of synergetic effects: agglomeration and urbanization economies, which cumulatively enlarge the population (Camagni, 2001). At the same time, globalization processes generate urbanization economies from economies of scale for firms. They occur when the average cost of a unit of production decreases as a firm increases its input of production. As large cities have a diversified and large labor force, with adequate resources and infrastructure, they can fully utilize all the resources needed in a production process. Firms establish in large cities where urbanization economies take effect, benefiting from a massive range of general services at a lower cost than smaller cities provide. Firms located in cities

Globalization and the dominance of large cities in contemporary China: Simon X B Zhao et al.

with urbanization economies will also benefit from Verdoorn’s Law, suggested by Kaldor (1966, 1978). This states that the greater the rate of increase of output inside a firm, the greater the increase in productivity. Firms located in large cities not only benefit from urbanization economies, but gain experience in technical production, further decreasing production costs per unit. Krguman (1991) has also suggested a synergy effect where related industries attract each other in the same city, forming clusters that are interconnected, while externalities across industries, which are essential in economic development, often lead to economic growth (Porter, 2001). The contemporary rise of importance of the financial sector has resulted in a bigger impact of globalization on urban development, that is, given the choice, investors of all nationalities will seek out the lowest cost and most liquid markets (OECD, 2000); people will be able to process their financial transactions anywhere as long as it is cheap. Therefore, the provision of cheap and mobile information infrastructure allows global investors to deal with their financial transactions in those cities; large cities can offer lower costs on financial transactions, and the easier movement of information due to good informational infrastructure. At the same time, as Krugman (1991) suggested, increasing returns of scale will bring technological innovation in production within the firm, i.e. endogenously. Firms that emphasize technological progress prefer to locate in large cities, as innovations tends to be facilitated by the agglomeration of industries (Porter, 2001). As large cities are clusters of large scale business operations, this encourages technological progress and subsequently increasing returns. In order to achieve technological progress endogenously, firms will choose to establish, set up and expand in large rather than in smaller cities. As the competitiveness of a city becomes an important factor in its development, and as infrastructure is central to the development of the competitiveness of a city or region (Sassen, 2001), large cities tend to have advantages, because urbanization economies allow the efficient and effective use of infrastructure, especially transportation infrastructure. Consequently, they usually became the nodes of international transportation systems. Such large-scale infrastructural investments in large cities can attract further—especially foreign—investments, again resulting in the agglomeration of firms. Firms would tend to locate to cities where they can obtain a wide range of labor in different specializations, with good supporting facilities and infrastructure. Large cities are able to provide and attract a large pool of labor, as a result of superior infrastructural provision and other life-supporting amenities, in both quantity and quality. The more firms invest in large cities, the more labor, resources and investment will move there. Globalization also results in the emergence of the knowledge based economy. The emerg-

ence accelerates the development of cities possessing easy and convenient information flow, which comes from the provision of good information infrastructure, which includes telecommunications facilities, institutions of higher education and the availability and accessibility of information channels. In summary, large cities are not only the place wherein growth occurs, but are the engines of growth itself. (Duranton, 2000). Moreover, globalization speeds up such agglomeration. A recent study conducted by Lin (2001) propounds dual-track urbanization and remarks that cities in China under socialism are more than economic growth engines, and are at the same time centers of economic and social transformation engineered by the state (Lin, 2002, p299). He concludes that large and extra-large cities remain prominent in capital investment and production, which may undermine the earlier claims of the dual-track thesis (Lin, 2002, p34). This is exactly what we argue for, insofar as an assessment of the system as a whole may point to a different conclusion. Our study aims to portray the major patterns of the urban system for China from the urban system perspective and for the country as a whole. Details of the methodology and the analysis are to be elaborated in the following sections.

Development of the urban system in China Sources and usage of the indicators In order to grasp the effects of globalization and the economic theories of urbanization agglomeration on urban development, and to show the dominance of large cities in urban growth patterns in China, it is necessary to draw from a wide range of demographic, economic, employment and living standards indicators. They show that large cities have dominated the demographic, economic, employment and social development in China in the 1990s. The indicators are drawn from the Urban Statistics Yearbook of China of 1991 (for 1990) and 2000 (for 1999) respectively. The non-agricultural population in urban areas is being used in this paper, even though that may have underestimated the actual figures (e.g., the exclusion of the informal migrant population), because the other figures tend to overestimate the urban population insofar as they may include the population engaged in agriculture yet living in urban areas. Therefore, comparatively, the use of the figures for the non-agricultural urban population reflects a more accurate picture. Four classes of cities are included in this analysis. Class 1, which represents cities possessing a population of 1 million or over; Class 2, which represents cities possessing a population of 500 000 to 1 million people; and Class 3, which represents cities possessing a population of 200 000–500 000. The paper focuses on growth patterns of cities with a population of over 200 000, and excludes the Class 4 cities for statistical consistency. The exclusion is due to the fre267

Globalization and the dominance of large cities in contemporary China: Simon X B Zhao et al.

quent changes in administrative districts and the lack of clarity in the classification of boundaries and the various difficulties in the calculation of the exact population in the smallest cities. Moreover, the 2000 Class 4 data do not account for all small cities—therefore such figures are of little use. [It is to be noted that even if the figures for the small cities are included, the results remain unchanged. A similar study conducted by the authors, using the demographic and economic indicators between 1990 and 1997 (which included the figures for small cities) drew the same conclusions]. Growth of population Distribution of cities in city categories: Non-agricultural population More than one in two persons is now living in the large cities (Class 1 and Class 2). In Table 1, in terms of the inner-city non-agricultural population, there was a 6.2% AGR in Class 2 cities, which was the highest, and Class 1 recorded the second largest rate of 3%, cf. 4% in super large cities. The share of total non-agricultural population in Class 2 cities grew from 16.1% in 1990 to 21.1% in 1999, while the share of Class 1 in the same category rose from 41.6–42%. The AGR in non-agricultural population for Class 3 was only 1.3% and constitutes only half of the overall average of 2.9%. Class 3 were the only cities to record a drop in the share of the nonagricultural population. In 1999, nearly one-third of the non-agricultural urban population lives in the super large cities. The adjusted non-agricultural population figures: Change of population in the same set of cities In order to show that urbanization agglomeration is a sign of the growth of the large cities itself, and not because of the growth of small and medium sized cities, a more accurate measurement can be used. That is, assuming any city would not be downgraded to a lower category of cities throughout the 1990s, two population figures of different categories from a base and a destination year are compared. We calculate the population figures of the destination year, subtract those population figures previously in the lower cate-

gory of cities, and add back those population figures in the higher categories in the destination year. The figures derived form such calculations tell us the changes of the population of the exact same cities under the same category between 1990 and 1999. The above measurements have eliminated the fluctuations of population from the ‘upgrade’ effect. Table 2 shows this, where 1990 is the base year and 1999 is the destination year. The table shown that Class 1 cities, have the highest positive AGR (2.3%), while the Class 3 cities recorded negative AGR. This is the result of growth in the Class 1 cities, and not from the growth of Class 3 cities into Class 1 or Class 2 cities. These data show agglomeration, and not the upward movement of the medium-sized and the small-sized cities; the large cities are the magnets of people, firms, capital and technology. Distribution of cities in city categories: Built-up area In Table 3, from 1993–1999, Class 1 cities had a built-up area of 180.2 m2/person, the highest built up area per capita in 1999. Class 1 has the largest change of share of built up area in 1999, an increase of 3.6% (3.3% in the extra large cities). The large built-up area for Class 1 cities represents intensive urban agglomeration. Economic factors supporting rapid growth in large cities Fixed asset investment Fixed assets are infrastructure and so forth that cannot be moved and cities with better infrastructure produce urbanization economies. Table 4 shows the fixed asset investment by city size. The growth rate of fixed asset investment per capita in Class 1 cities was 20.6%, the highest among all classes of cities. The super-large cities showed even more, with 23.2% of fixed asset investments. The total investments and the growth rate per capita in Class 2 cities and Class 3 cities were below average, for Class 3 cities it is just 40% of the rate for Class 1 cities. The fixed asset investment per capita in 1999, which stands at 7457.9 yuan/person in Class 2 and 7620.3 yuan/person for Class 3, were much below that of Class 1, which was 18315.7 yuan/person, overall, the

Table 1 Non-agricultural population, by city size, from 1990–1999 (10 000 persons) Year

1990

City size

Number

Class 1 Super large cities Extra large cites Class 2 Class 3 Total

6263.9 3450 2813.9 1899.4 3644.4 11807.7

1999

Share (%) 53.1 29.2 23.9 16.1 30.9 100

AGR (%)

Number

Share (%)

8174.4 5021.3 3153.1 3289.3 4110.9 15574.6

52.5 32.2 20.3 21.1 26.4 100

3.0 4.2 1.3 6.2 1.3 2.9

Share change (%) (1998–1990)

⫺0.6 +3.0 ⫺3.6 +5.0 ⫺4.5

Source: Computed from Urban Statistical Yearbook of China 1991 & 2000. AGR = Annual Growth Rate. Class 1 = population size over 1 million in a city, Class 2 = population size from 0.5–1 million in a city, Class 3 = population size from 0.2–0.5 million in a city.

268

Globalization and the dominance of large cities in contemporary China: Simon X B Zhao et al. Table 2 The adjusted non-agricultural population (actual growth of population of cities lies in the same category) in 1990 and 1999 (10 000 persons) City Size

Population (1990)

Population (1999)

Class 1 Super Large Cities Extra Large Cities Class 2 Class 3

6137.84 3444.34 2813.90 1899.40 3644.39

8174.4 5021.3 3153.1 3289.3 4110.9

PIALC (1990–1999) 631.6 879.7 631.6 1548.8 3506.29

PIAHC (1990–1999)

ANAP (In 1999)

AGRPITSCOC (%)

N/A N/A 879.7 631.6 1548.8

7542.8 4141.6 3401.15 2372.11 2153.39

2.3 2.1 2.1 2.5 ⫺5.7

Source: Computed from Urban Statistical Yearbook of China 1991 & 2000. PIALC = Population of 1998 In A Lower Category in 1990. PIAHC = Population of 1999 In A Higher Category in 1990.ANAP = Actual Non Agricultural Population. AGRPITSCOC= Annual Growth Rate of Population In The Same Category of Cities.

Table 3 Built-up area, by city size, from 1993–1999 Year

1993

1999

AGRBPANAP (%)

City size

BAPNAP

SBA (%)

BAPNAP

SBA (%)

Class 1 Super large cities Extra large cites Class 2 Class 3 Total

143.44 59.32 84.12 98.0 98.9 340.34

42.2 17.4 24.8 28.8 29.0

180.2 69.5 110.7 101.6 112.0 393.8

45.8 17.7 28.1 25.8 28.4

Share change (%) (1999–1993)

+3.6 0.3 3.3 ⫺3 ⫺0.6

2.6 1.8 3.1 0.4 1.3 1.4

Source: Computed from Urban Statistical Yearbook of China 1993–94 & 2000. BAPNAP = Built-up Area per Non-agricultural Person (sq. m/person). SBA = Share of Built-up Area. AGRBAPNAP = Annual Growth Rate in Built-up Area Per Non-agricultural Person. Note: The starting year for this statistical item is 1993, due to difficulties in the investigation of this data ranked according to urban population size prior to 1993.

Table 4 Fixed asset investment of city, by size, between 1993–1999 City size

Class 1 Super large cities Extra large cities Class 2 Class 3 Total

FAI in 1993 (100 FAI in 1999 (100 AGRFAI (%) million yuan) million yuan) 2536.6 1550.4 986.2 1096.2 1989.6 6357.8

7796.1 5432.4 2363.7 2453.1 3132.6 13638.6

+20.6 +23.2 +15.7 +14.4 +7.9 +8.9

FAIPC in 1993 (yuan/person) 6417.7 3692.4 2725.3 3175.6 3272.4 15355.1

FAIPC in 1999 (yuan/person) 18315.7 10819..0 7496.7 7457.9 7620.3 34239.4

AGRFAIPC (%)

+12.3 +12.7 +11.9 +10.0 +9.84 +9.3

Source: Computed from Urban Statistical Yearbook of China 1993–1994 & 2000. FAI = Fixed Asset Investment. AGRFI = Annual Grow Rate of Fixed Asset Investment. FAIPC = Fixed Asset Investment Per Capita. AGRFAIPC = Annual Growth Rate of Fixed Asset Investment Per Capita. Note: The starting year for this statistical item is 1993, due to difficulties in the investigation of this data ranked according to urban population size prior to 1993.

Class 1 cities exceeds the Class 2 and Class 3 cities by a factor of 3 and 2.5 times respectively. Foreign investments Foreign investment is significant in the development of a city in the era of globalization. In Table 5, the 1998 foreign investments are used to reflect a more accurate picture, as the overall amount of foreign investment was dramatically lowered in 1999 due to the Asian crisis. Although overall foreign investment in 1998 is lower than in 1990, foreign investment in Class 1 cities was significantly higher than the others, and the AGR is approximately 7 times the average. In terms of the AGR per capita,

Class 1 cities outperformed 5 times the other cities. As for the extra large cities category alone, this was 20 times more than the nearest category of city, the Class 3 cities. In the amount of total foreign investment, Class 1 almost tripled that of Class 2 and 3, while the super large cities itself is double that of Class 2 and 3. In terms of the total foreign investment per capita category, the figures of Class 1 cities nearly doubled, and were double the figures for Class 2 and Class 3 cities respectively. The share of fixed asset investment and foreign investment Table 6 illustrated that the Class 1 cities had 269

Globalization and the dominance of large cities in contemporary China: Simon X B Zhao et al. Table 5 Foreign investment of city, by size, between 1993–1998 City size

Class 1 Super large cities Extra large cities Class 2 Class 3 Total

FI in 1993 (US$ 100 million) 120.9 85.0 35.9 71.2 91.2 309.8

FI in 1998 (US$ 100 million) 170.5 134.3 36.2 76.8 75.2 329.7

AGRFI (%)

FIPC in 1993 (yuan/person)

FIPC in 1998 (yuan/person)

AGRFIPC (%)

7.1 9.6 0.2 1.5 ⫺3.8 1.4

348.4 223.3 125.1 288.8 192.7 898.9

392.9 275.8 117.1 245.0 194.8 848.9

+ 2.4 + 4.3 + 1.33 ⫺3.23 + 0.22 ⫺1.1

Source: Computed from Urban Statistical Yearbook of China 1993–1994 & 1999. FI = Foreign Investment. AGRFI = Annual Grow Rate of Foreign Investment. FAIPC = Foreign Investment Per Capita. AGRFAIPC = Annual Growth Rate of Foreign Investment Per Capita. Note: The starting year for this statistical item is 1993, due to difficulty in the investigation of this data ranked according to urban population size prior to 1993.

Table 6 The share of non-agricultural population, fixed asset investment & foreign investment in city size categories between 1993– 1999 (%) SFAI in 1993

SFAI in 1999

39.9 24.4 15.5 17.2 31.3 100

57.8 39,8 17.3 18.0 23.0 100

City Size Class 1 Super large cities Extra large cities Class 2 Class 3 Total

Share change (1993–1999) +17.9 +15.4 +1.8 +0.8 ⫺8.3 –

SFI in 1993

39.0 27.4 11.6 23.0 29.5 100

SFI in 1999

58.3 40.6 17.7 18.3 23.4 100

Share change (1993–1999) +19.3 +13.2 + 6.1 ⫺4.7 ⫺6.1 –

Source: Computed from Urban Statistical Yearbook of China 1993–1994 & 2000. SNAP = Share of Non-agricultural Population. SFAI = Share of Fixed Asset Investment. SFI = Share of Foreign Investment. Note: The starting year for this statistical item is 1993, due to difficulty in the investigation of this data ranked according to urban population size prior to 1993.

the largest increase and it has the controlling majority (more than 50% in foreign investment, and 60% in fixed asset investment) of both the share in fixed assets and the share in foreign investments in 1999. Class 1 cities, especially the super large cities, have by far the biggest increase in the share of fixed asserts investment and foreign investments between 1993 and 1999. The super large cities constitute 80 and 90% of the increase in the share of fixed asset investment and foreign investment respectively. On the other hand, Class 3 has shown decline in the shares of all categories. Industrial and commercial tax revenue The amount of industrial and commercial tax revenue generated per capita reflects not only the efficiency of economic activities but also the capacity of re-investment. Large cities collected large amounts of taxes and have the higher AGR in taxes. In Table 7, Class 1 had a marked increase of 10.7% which is around 8 times the average. The super large cities alone had an increase in AGR of 6.7%, which is 3 times more than the overall average. Class 3 cities have a decrease in their AGR and had the largest decrease in tax revenue collected. The statistics may have reflected the inability of the authorities in Class 3 cities to curb tax evasion, but most importantly, many businesses and talented personnel have left the Class 3 for the Class 1 cities. 270

Number of persons employed Large numbers of workers were sacked from the SOEs as a result of the state enterprise restructuring in the 1990s. In Table 8, the overall employment figures for all cities in 1999 are only 40% of those in 1990. However, such restructuring did not seem to affect the employment opportunities for Class 1 cities. The super large cities in Class 1, with an increase of 0.5%, is the only increase in employment, all other categories reported negative figures. The reforms do hit Class 3 cities severely; they lost slightly more than half of their employment, compared to 1990. As for the change of share for the number of persons employed, Class 1 gained an astonishing 8.8%, which is about 1.7 times higher than the second highest increase, which is from Class 2 cities. Share of secondary and tertiary industry In Table 9, in terms of the share of secondary and tertiary occupations, Class 1 and Class 2 cities outperformed Class 3 cities. In the AGR of the tertiary industry category, Class 1 outperformed the others, where the rise was 29.1%. Class 3 cities received lower increases (26.5 and 8.2%) in their secondary and an 18.6 and 17.3% of growth in their tertiary sectors respectively, lower than for Class 1 cities. As tertiary industry became much more significant under globalization, the large cities in China will be able to outperform all the other

Globalization and the dominance of large cities in contemporary China: Simon X B Zhao et al. Table 7 Industrial and commercial tax generated per capita, by city size, from 1990–1998 (yuan /person) City size

1990

Class 1 Super large cities Extra large cities Class 2 Class 3 Total

1267 1220 1253 1221 977 4394

1998

AGRTGPC

2850 1835 1015 1333 826 5091

10.7 6.3 ⫺2.6 1.1 ⫺2.1 +1.9

Source: Computed from Urban Statistical Yearbook of China 1991 & 1999. AGRTGPC = Annual Growth rate of Tax Generated Per Capita. Note: The starting year for this statistical item is 1993, due to difficulty in the investigation of this data ranked according to urban population size prior to 1993. The 1998 figure is used due to statistical difficulties in compiling the 1999 figure of industrial and commercial tax.

Table 8 Employment of city, by size, from 1990–1999 (10 000 persons) 1990

City size

Employment

Class 1 Super large cities Extra large cities Class 2 Class 3 Total

4790.57 2456.07 2334.5 1492.64 4326.92 10610.13

1999

Share (%) 45.2 23.2 22.0 14.1 40.8 100

AGR (%)

Employment

Share (%)

3898.74 2573.12 1325.62 1419.77 1896.32 7214.83

54.0 35.7 18.4 19.7 26.3 100

⫺2.0 +0.5 ⫺6.1 ⫺0.6 ⫺8.8 ⫺8.9

Share change (%) (1999–1990)

+ 8.8 + 12.5 ⫺3.6 + 5.6 + 4.5 /

Source: Computed from Urban Statistical Yearbook of China 1991 & 2000. AGR = Annual Growth Rate.

Table 9 Economic structure of urban employment, by city size, from 1990–1999 (10 000 persons) 1990

1999

Share change (%) (1999–1990)

City size

SSO

STO

SSO

STO

SSO

STO

Class 1 (Average) Super large cities Extra large cities Class 2 Class 3

18.25 19.0 17.5 12.0 25.6

18.45 20.2 16.7 10.0 22.9

49.25 45.3 53.2 35.0 52.1

47.55 50.6 44.5 41.1 41.5

+31.5 +26.3 +35.7 +23 +26.5

+29.1 +30.4 +27.8 +31.1 +18.6

Source: Computed from Urban Statistical Yearbook of China 1991 & 2000. SSO = Share of Secondary Occupation. STO = Share of Tertiary Occupation.

categories, by having a relatively larger tertiary sector. Other socioeconomic indicators Various socio-economic indicators are also important in looking at whether a city attracts people and firms to stay. They are the average growth in wages, a factor indicating the economic well-being of cities; the number of hospital beds, a quality of life factor indicating how attractive the cities are to its people and to firms; and the number of books in public libraries, indicating its preparation for the challenges of the knowledge-based economy. The large cities have performed better in all categories, showing their superior standard of living. Class 3 cities did below average, and even recorded negative figures in two categories.

Table 10 shown the rate of change in the three indicators between 1993 and 1999 and Table 11 shows the share change of those indicators between 1990 and 1999. The two tables suggested that the provision of infrastructure in the Class 3 cities is poor. Class 1 dominated the number of hospital beds nationwide, and especially the number of books in libraries; the increase in share for Class 1 cities is an astonishing figure of 33.9%, with the super large cities increasing 27%.

Meaning and implications of the empirical findings From the tables above, we draw some conclusions on the way in which ongoing processes of globalization, 271

Globalization and the dominance of large cities in contemporary China: Simon X B Zhao et al. Table 10 Other socioeconomic indicators between 1990 and 1999, by city sizes (%) Socioeconomic indicator Annual growth rate of worker Annual growth rate of of books in the public Annual growth rate of of hospital beds

wage per number library number

Class 1 (average) 14.35

Super large cities

Extra large cities

Class 2

Class 3

14

11.2

14.0

14.7

4

6.4

1.6

0.9

⫺0.5

1.7

2.9

0.4

2.0

⫺1.7

Source: Computed from Urban Statistical Yearbook of China 1991 & 2000. Table 11

The share change of socioeconomic indicators of city sizes (%)

City size

BIL (1999–1993)

Class 1 Super large cities Extra large cities Class 2 Class 3

+33.9 +27.2 +6.7 ⫺9.9 +2.1

HB (1999–1993) +15.5 +10.8 +4.7 +6.6 +1.6

AWPW (1999–1993) +3.0 +1.2 +1.8 +1.0 ⫺1.9

Source: Computed from Urban Statistical Yearbook of China 1993–1994 & 2000. AWPW=Average Wages Per Worker. HB= Hospital Beds.BIL= Books in Library. Note: The starting year for this statistical item is 1993, due to difficulty in the investigation of this data ranked according to urban population size prior to 1993.

urbanization economies, increasing returns and urbanization agglomeration have contributed to the dominance of the large cities in contemporary Chinese urban development. The effects, reflected by the amount of fixed asset investments, the amount of tax revenue, the amount of built-up land and the provision of life-supporting amenities in such cities, are assessed below. The fixed asset investment level indicated whether the city could attract firms to the city or further investment. As large cities are able to achieve urbanization economies and increasing returns, it would encourage firms to inject massive amounts of fixed assets there, and government would invest in more infrastructure, which would leverage even more private fixed asset investments. Tables 4 and 5 illustrated increasing returns for firms investing in large cities: Between 1993 and 1999, Class 1 cities had an average growth rate of fixed asset investment of 20.6%, for super large cities the figure was 23.2%, significantly higher than all other city categories. As for the average growth rate per capita, Class 1 cities indicated an increase of 12.3%, (super large cities, 12.7%), also significantly higher than all other categories. The figures suggest that firms and governments continue to increase their fixed asset investment in large cities. The tax revenue figure in Table 7 reflects economic progress. More tax revenue is collected, due to firms locating in large cities, leading to a strengthening in profitability. The largest increase in tax revenue was in Class 1 cities (10.7%), which is around 8 times the average. The super large cities alone had an increase of 6.7% (three times the overall average). The total amount of tax income generated per capita for the super large cities is twice the figure in Class 3. 272

Large cities have large administrative areas, and have room for further growth. In Table 3, Class 1 cities hold the largest share of built-up area, with 40.8% of the total, and with an AGR of built-up area per capita of 3.7% for the super large cities. The high and increasing figures for built up area in the large cities of China suggests further urbanization agglomeration. In Table 1, super large cities have a high AGR of population of 4.2%, a quarter of the total non-agricultural urban population; in Table 2, Class 1 cities have the highest AGR calculated from the adjusted non-agricultural population table, which suggests that the agglomeration of population of Class 1 is within the cities themselves. This is a significant finding because the large cities in China are the magnet for people, firms, funds, goods and technology. The figures confirm urbanization agglomeration in China, especially in super large cities. The large cities tend to provide better provision of daily needs and better wages per worker. In Table 10, the AGR of the number of hospital beds for the super large cities in Category 1 is 6.4%, the biggest increase amongst all categories, which is 4 times higher than the AGR in the extra large cities category. The Class 1 cities have the highest increase of the growth rate of wage per worker, which is 14.35%. In Table 11, Class 1 cities have the largest increase in share of 15.5% in the number of hospital beds from all categories, while super large cities constitutes an increase of 10.8% alone, which comprised two thirds of the increase. The share of average wages paid for the super large cities category have increased by 3%, the highest amongst all categories. As urban wages increase with skill (Jayet, 2000), the increase in wages in the large cities reflects the increase of skills of the

Globalization and the dominance of large cities in contemporary China: Simon X B Zhao et al.

workers there; Class 1 cities have the highest concentration of skilled personnel, thus attracting firms. The substantial flow of foreign investment towards the large cities accelerates their growth, a result of the substantial rise of cross-border trade under globalization. This is a result of competitive advantage held in the large cities. Tables 4 and 5 and 6 show the amount of total foreign investment in Class 1 cities rose by 7.1% on average per year, and their share for foreign investment rose from less than 40% in 1993, to more than half in 1999. As for the super large cities alone, the share of foreign investments rose from just over a quarter in 1993 to 36% in 1998, and its annual growth rate (AGR) per capita rose by an astonishing 9.6 and 4.3% respectively. Foreign investments in China accelerate the development of recipient cities. A substantial amount of foreign investments went to infrastructure developments, which increases competitiveness. This is evident by Gu et al’s (1999) assumption that those cities with foreign investment will tend to perform better than those cities which find support strictly from town and village enterprises (Gu et al, 1999, 164). Yao (1997) stated that in Shanghai during 1993, 44% of the total of foreign investments went to infrastructure projects and changes in industrial technique (Yao, 1997, 65). The foreign investment volume is now a determining factor in urban development in China. As China follows the global norm, firms, especially MNEs, will include China as a significant part in their global strategies. They would probably choose to establish production plants in China to ensure low cost domestic supply of their products. Firms worldwide may find the large cities in China have better competitive advantage, due to the provision of globally competitive support industries (banking, finance, insurance, logistics, legal), infrastructure (especially logistics and information infrastructure), and human resources of different sectors and different expertise. Above all, as shown in Table 1, over half of the population in China are in Class 1 cities alone (between Class 1 to Class 3 cities); such population agglomeration provides a large potential market for the products of the MNEs, and therefore, encourage the MNEs to produce locally to save logistical and production cost. As a result, globalization encourages the concentration of resources, fixed asset investment and foreign investment in the large cities. It would also accelerate industrial and population migration from small to large cities. Investments from MNEs in the large cities require highly educated personnel, with adequate knowledge in information technology, a global outlook and other desired skills. A good provision for learning is therefore important. People in large cities in China have more chance of acquiring knowledge, through the better provision of libraries. As for higher education, the best universities are concentrated in the super large cities, and they attract talented people nationwide. Graduates from the best universities in the large cities,

would likely to seek work in the same city, reinforcing the agglomeration of the highly educated. The globalization of production and business locations has resulted in industrial agglomeration in large cities, cf. Table 8, where the Class 1 cities have the highest scale of increase of foreign investment. The development of Economic Open Zones (EOZ, jingji kaifa qu), with a substantial amount of foreign investment, will be the main basis for foreign investments after China’s entry to the WTO. They are the direct products of industrial agglomeration, and most of these EOZs are located in the large cities. Of 109 state class (guojia ke) EOZs, 50% are located in the extra large cities of population of 1 million. (Gu et al, 1999, 129). Globalization results in the growing importance of the financial sector in urban economies. China’s large cities, where such channels are located, are able to benefit from this wave, as reflected in the amount of fixed asset investments (Table 4). They dominated in tertiary occupations. As shown in Table 9, Class 1 cities recorded a 26.8% increase in tertiary occupations, (30.4% for super large cities). Most of the tertiary operations in China are in the large cities (Chan and Yao, 1999). Globalization results in the desire for the free flow of human resources, goods, resources and capital, especially by foreign firms. Good transportation and infrastructure is needed for such provision. China’s large cities possess a stronger position than their counterparts in the development of such infrastructure; as shown in Tables 4 and 5, the large cities in China shared and had the most fixed asset investments and especially foreign investments (in both AGR and per capita terms). A substantial part of such investments went to the development of transport infrastructure, strengthening the international attachment of large cities. Beijing and Shanghai have frequent contacts with the rest of the world, while Guangzhou and Shenzhen, with proximity to Hong Kong, have even more contacts. These cities are now have a significant role in the global urban hierarchy. We believe a new mode is responsible for the urban development of some extra large cities in contemporary China. That is, a concentric development of production zones, where the manufacturing production by multinational corporations is agglomerated, located in the rural or fringe areas along with one global city in the core. This new mode of urban development would eventually grow into metropoles that feature a unique urban form, a distinguished world city surrounded by a vast production base. The four urban agglomerates in China today are the result of such a new mode of development. They are the Pearl River Delta, the Northeast, Beijing-Tianjin-Tsingtao and Shanghai-Suzhou-Nanjing agglomerations. The Pearl River Delta agglomeration is composed of the core cities of Hong Kong, Shenzhen, Guangzhou and its surrounding areas, with a population of 40 million, mostly with massive investments from Hong Kong 273

Globalization and the dominance of large cities in contemporary China: Simon X B Zhao et al.

and Taiwan. The forces behind such development are the geographic proximity and cultural and ethnic ties, which led to the concentration of investment from Hong Kong in the region (Sun, 1998). At the same time, the largely export-oriented investment from Hong Kong and Taiwan, using the abundant and cheap resources, requires the locations of investment to be close to main seaports in order to reduce transaction costs (Sun, 1998), which transformed the Pearl River Delta as one of the most economically well-off regions in China. As for the investments in the other two major areas, the Shanghai-Suzhou-Nanjing agglomeration on the Yangzi River Delta and the Beijing-Tianjin-Tsingtao agglomeration along the Bohai Wan area, in contrast with the Pearl River Delta region, came from a diverse range of countries, including Japan, South Korea, the US, Europe and Singapore (in Suzhou), where they have used relatively advanced technologies and mainly target Chinese domestic markets. Therefore, their investments have been located in major cities where population and better developed industrial facilities fit their models for both production and marketing (Sun, 1998). Finally, the Northeastern agglomeration comprises the core cities of Dalian and Shenyang, surrounding by the Liaodong Peninsula, where Japanese and South Korean investments dominate; it combines the labor intensive investment of export-oriented manufacturing seen in the Pearl River Delta Region and the capital intensive investment of advanced technologies seen in the Yangzi River Delta agglomeration and the Bohai Wan agglomeration. This new mode of urban agglomeration is fueled by foreign capital, investment and technology. A full theoretical elaboration on this new mode of development is beyond the scope of this paper, but we shall elaborate this in great detail in our next study.

and the Yangtze Delta regions. The eastern region housed 87.8% of the total FDI in China (OECD, 1999). Out of that, 29.1% went to the Guangdong provinces, 11.9% went to the Jiangsu province and 8.6% went to the Shanghai, representing the Pearl River Delta regions and the Yangtze Delta respectively. The area is the engine for employment, industrial development and trade in such areas, and therefore, it results in the concentration of urbanization. A strong correlation between foreign investment and urban population growth has resulted. In this section, we test further the role of globalization in China’s urban development and larger city dominance. These tests constitute: 1) The analysis of correlation and regression between FDI and foreign industrial output (FIO) volume and the growth of urban population; 2) The identification of the four regional clusters that experienced rapid growth of GDP, FDI and urbanization in the country; 3) A close-up ofo the Pearl River Delta region, the country’s most globalized, industrialized and urbanized region.

Statistical test of the role of globalization

where FDI= foreign direct investment; FIO = foreign industrial output (gross value); GDP= gross domestic production; and PT = population of urban district within the city. In order to measure directly the impact of the independent variables on the dependent variables in terms of percentage change, the three equations can be expressed in logarithmic form:

We have indicated the impact of globalization based on empirical analysis. In this section, we would like to further demonstrate such impact through statistical analysis, from the national and macro economic perspectives. Foreign capital, particularly FDI, has been increasingly playing an important, even dominant role in China’s economy. China is the second largest FDI recipient in the world, next only to the US and the largest among the developing countries. China’s volume constitutes about 1/3 of total FDI among third world countries, 10% of direct investment worldwide, and over 50% of all such investments between all Asian countries. In terms of the national economy, it contributed 37% of total GDP, 31.5% of total exports and 47.7% of total imports, 18.9% of the total industrial output and 13.2% of total employees employed in the country (Sun, 1998; Luo, 2000). At the same time, the FDI is concentrated predominantly in the eastern coastal areas, particularly the population agglomeration areas, such as the Pearl River Delta 274

The correlation/regression model In this section, a regression model is used to test the impacts of foreign direct investment and foreign industrial output (gross value) on economic growth and urban growth pattern of cities in China. Economic growth can normally be expressed as the growth of GDP while urban growth can be expressed as the growth of population. The equations are specified respectively as follows: GDP = f(FDI, FIO) P = f(GDP) P = f(FDI, FIO)

ln GDP = a0 + a1 ln FDI + a2 ln FIO ln P = b0 + b1 ln GDP ln P = c0 + c1 ln FDI + c2 ln FIO where a0, b0 and c0 are the estimated intercepts respectively for the equations. The estimated elasticity coefficients a1 and a2 in the first equations in the second equation measure the percentage change in GDP in response to a one percent change in FDI and FIO respectively. Similarly, b1, c1 and c2 in the other two equations measure the percentage change

Globalization and the dominance of large cities in contemporary China: Simon X B Zhao et al.

in population in response to a one percent change in GDP, FDI and FIO respectively. The hypothesis to be tested is: 1) FDI and FIO positively influenced economic growth of cities; 2) economic growth (GDP) of cities would positively stimulate its population growth within the area; FDI and FIO positively contribute to the increase of population of a city. Therefore, the expected signs of the parameters for independent variables in three equations are positive. This hypothesis can be tested by t test and the estimated regression coefficients. The data used in this analysis is cross-section data in 1999 within urban district proper (excluding counties and towns), which have FDI and FIO. The data source is Urban Statistical Yearbook 2000. There are 218 cities that have FDI and 223 cities that have FIO, altogether 236 cities are studied. In Table 12, the regression result for the first equation shows that increases in foreign direct investment (FDI) and foreign industrial output (FIO) positively and significantly contribute to GDP growth of cities. A one percent increase FDI and FIO would result in a 0.171 and 0.223% increase in GDP of cities. The result for the second equation illustrates a positive and statistically significant impact of economic growth (GDP) on urban population. A one percent increase in GDP tends to give rise to a 0.56% increase in urban population of a city. The result for the third equation indicates that increases in FIO significantly and positively contributes to population growth within the urban district of the cities. A one percent increase in FIO would give rise to a 0.122% increase in urban district population. Also, the effect of FDI on population growth within a city is positive and statically significant at 10% level in this equation. Therefore, a one percent increase in FDI would give rise to a 0. 05218% increase in urban district population. However, when testing the impact of FDI on population growth in a linear regression equation, it presents a positive and correlated relationship between each other, and its coefficient is statistically significant at the 5% level. Table 12

The four clusters of concentration From the correlation and regression, we identify four clusters of GDP, FDI and urban population in China (see Table 13 below). These four clusters all recorded the highest growth rate in urban population, due to their rapid growth of GDP and FDI inflow, when compared with the national figure. These clusters have further substantiated the correlation between FDI and urban growth in China. The hypothesis of an increasing FDI leading to an increase in urban population can be illustrated explicitly from the case of the Central region: before 1995, it only accounted for a very insignificant share of China’s FDI. But Table 13 reveals that, through 1995 and 2000, it has recorded the highest growth rate for both the FDI volume and urban population. This finding has again shown that the larger the FDI volume flowing into a region, the faster the pace of the population growth. The Pearl River Delta case The Pearl River Delta is ideal to further demonstrate both the role of globalization and the dominance of large cities in China’s urbanization process. The region has the largest concentration of FDI in China,

Regression result

Equation

Independent variable

lnGDP = a 0 + a 1 lnFDI + a 2 lnFIO

LnFDI LnFIO Constant

0.171 0.223 9.952

LnGDP Constant

0.560 ⫺3.293

R 2 = 0.604 lnP = b 0 + b 1 lnGDP R 2 = 0.623 lnP = c 0 + c 1 lnFDI + c 2 lnFIO R 2 = 0.237

The correlation and regression models have articulated, in a clear and explicit manner, that the level of foreign direct investment is strongly and positively correlated to the growth of the urban GDP and population. That is, the first equation shows a growth in FDI injected to a particular urban area, or an increase in foreign industrial output, will induce growth of urban GDP of that particular area, a positive link between foreign investment and the performance of the urban economy. The second equation shows a strong FDI inflow into certain urban areas will also indicate a strong growth in the urban population of those areas. The two combined have revealed that the level of FDI injected has direct and tremendous impacts on the development of both the urban economy and the urban population.

LnFDI LnFIO Constant

Estimated coefficients

0.05218 0.122 2.649

t-ratio

Significant

Standardized coefficients

Partial correlation

5.167∗ 6.773∗ 41.64∗

0.000 0.000 0.000

0.357 0.468 –

0.340 0.428 –

19.565∗ ⫺8.376∗

0.000 0.000

0.789 –

0.789 –

1.594 3.743∗ 11.165∗

0.113 0.000 0.000

0.153 0.359 –

0.111 0.253 –

∗The coefficients are statistically significant at 5% level (for a one tailed test). Source: Compiled from the data from Urban Statistical Yearbook of China, various years.

275

Globalization and the dominance of large cities in contemporary China: Simon X B Zhao et al. Table 13

The four clusters of concentration (in %) GDP (1995–2000)

FDI (1990–1996 and 1995–2000)

Urban populationa (1995–1999)

Regions

Average share

Growth rate

Average share

Growth rate

Average share

Growth rate

Bohan Wan area∗ Yangtze River Delta region Pearl River Delta region Central region Sum of the average share National average of growth

19.07 19.52 13.53 13.32 65.44

76.30 74.18 80.49 72.69

91.05 65.62 46.97 91.39

9.59 6.13 5.6 7.66 28.98

13.2 19.2 18.74 20.84

17.18 25.53 37.29 5.06 85.06

67.70

73.77

10.57

∗The Bohai Wan area comprises Beijing, Tianjin, Hebei, and Shandong; the Yangtze River Delta region comprises of Shanghai and Jiangsu; the Pearl River Delta region comprises Guangdong and Fujian; the Central region comprises Henan, Hubei, Hunan.Source: China Urban Statistical Yearbook, various years; Statistical Yearbook of China, various years; China Population Yearbook, various years. a It refers to the non-agricultural population living in the urban areas of a city. Table 14 Population movements in the 5 highest populated cities in the Pearl River Delta (PRD) region (in million) Cities

Guangzhou

Shenzhen

Foshan

Dongguan

Population in 1990 Population in 2000 Growth (in %)

5.94 9.94 67.3

0.88 7.00 695.4

0.3 5.3 1666

1.3 6.4 392.3

Huizhou

The whole PRDa

0.2 3.2 1500

19 40 211

Source: Guangdong Statistical Yearbook, various years; China Urban Statistics Yearbook, various years; China Population Statistics Yearbook, various years. a The PRD region comprises of the following twelve cities: Guangzhou, Shenzhen, Zhuhai, Foshan, Huizhou, Shaoqin, Jiangmen, Dongguan Zhongshan, Shunde, Nanhai and Panyu.

which accounts for almost 40% of China’s FDI inflow. The region as a whole saw its population increase more than twofold, from 19 million in 1990 to 40 million ten years later. However, the cities with a strong presence of FDI in the region grew in an even larger rate. In 1990, the population for Guangzhou, Shenzhen, Dongguan, Foshan and Huizhou, the five cities with a larger amount of FDI inflow than the other cities in the region, were just 5.94, 0.88, 0.3, 1.3 and 0.22 million respectively. Ten years later, the populations for these cities have been increased to 9.94, 7, 6.4, 5.3 and 3.2 million. All have grown into large and super large cities. The population of these cities, apart from Guangzhou, far exceeds the growth rate for the whole region (see Table 14). The population growth of the larger cities in the PRD region has recorded substantial higher percentage than the region as a whole. For example, the population of Shenzhen, Foshan and Huizhou has increased 7, 16.7 and 15 times respectively. This finding has substantially differentiated from the conclusion stated in Lin (2001) and Sit and Yang (1997), that foreign investments have not led to the growth of large cities. From the PRD case, we can justify our claim that urban population growth in China is much more prominent in the larger cities.

Conclusion: Implications for Chinese urban development in the age of globalization This paper has assessed the continuous pattern of dominance of large cities in the development of 276

China, under the framework of globalization. It has drawn on various population, economic and standard of living indicators to show the dominance of large cities. The most significant finding is that the indicators show the demographic and economic development is driven within the large cities themselves, and not because of the growth of small or medium sized cities into large cities. Globalization, especially the effects from the globalization of business locations and the globalization of production, strengthens the growth of large cities in China The advantageous position of an easy information flow hold by the latter, due to the existence of a well-run transportation and logistics infrastructure, also contributes to their domination. Globalization accelerates financial flows; large cities possess a strong competitive advantage over the smaller cities due to their superior information infrastructure. Our empirical tests of correlation between FDI and urban growth, and its subsequent substantiation by the data of the four regional clusters and the Pearl River Delta case, have further confirmed our claim for the positive and tight link between foreign investments and the urban population growth in the large cities in China under the effects of globalization. The larger cities in China are therefore the magnet for foreign investment, thus leading to the emergence of the centers of financial flows. They will be leading in the ongoing process of China becoming a major player in globalization. Globalization has also brought about the population, industrial and capital agglomeration in large

Globalization and the dominance of large cities in contemporary China: Simon X B Zhao et al.

cities. Such agglomeration is caused by urbanization economies, competitive advantage, and increasing returns. Globalization strengthens urbanization economies in large cities, due to the availability and allocation of productive resources. Urbanization economies result in increasing returns, and both they and increasing returns strengthen the competitive advantage of large cities, so eventually, the effects from these factors have resulted in the agglomeration of people, firms and capital. The findings of this study do not contradict Lin’s dual-track system of China’s urbanization and urban development, characterized by the coexistence of large and extra-large cities at the one end, and small cities and towns at the other (Lin, 2002). Rather, this study confirms and enhances this dual-track’s one leg, that the intrusion of global market forces has helped reconsolidate the dominance of the eastern coast in China’s urban development (Lin, 2002, p1). We completely concur with Lin’s viewpoint that China’s urban development over the past decades has been the direct outcome of national political strategizing, state articulation and reconfiguration, and the shifts in global capital accumulation (Lin, 2002). However, both Lin’s and our studies acknowledge the picture unfolding clearly underscores the growing importance of large cities and that large cities have remained the most efficient and productive economic centers for capital investment and production. Furthermore, we both share the same view that this dominance of large and extra large cities was, essentially driven by the global shifts of foreign capital, mainly FDI in the coastal region. Thus, special attention will have to be paid to the growth of large and extra large cities in the era of globalization (Lin, 2002, pp. 311⫺314). This is the exact central point of this study. It is also interesting to see that two different studies on urban development in two periods (1980s and 1990s), with different perspectives, have drawn the same conclusion, that large cities dominated urban development in China. The first one, produced in the early 1990s, was mainly based on urban theory and domestic or indigenous factors in its analysis (Zhao and Zhang, 1998). This study is completely based on economic theories, the globalization processes and factors. However, the findings and conclusions of both studies are about the same—the domination of large cities development in China. Based on findings of these two studies, as well as the findings of Lin (2002), can we generalize that the dominance of large cities is not only an occasional but a general phenomenon? Is it not a coincident case but an inevitable principle in urban growth and development process? In our final argument, the quest to unfold the patterns of urban system and urban development seems to converge at the point with dominance of the large and extra large cities. We are content with the general consensus of this finding. This domination is, as we have argued, prompted by the synergy of the internal constraints of the Chinese economic system and its

greater participation in the global production machinery.

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