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Service Science, Vol. 1, No. 1, December 2009 1

THE REGIONAL SPECIALIZATION OF SERVICE SECTOR IN - FROM 1993 TO 20061

Jie Zhang Department of Industrial Economics, School of Management, Fudan University, , China, 200433 [email protected]

ABSTRACT Using the Krugman index, we calculate the regional specialization of 29 ‘ service sector in China. Further, we analyze some specific industries of the service sector through the location quotient. Then we compare the degree of specialization of 10 provinces between each other. The main conclusions of this paper are: Firstly, the average specialization of service sector is lower than manufacture sector because of the specific characteristics of service industry; Secondly, the specialization degree of service industry in China has been descending then increasing since 1990; Thirdly, metropolitan areas have remarkable advantages in the developing of producer service industry and knowledge intensive service industry.

Keywords: Service industry, Specialization, Krugman index, Location quotient

1. Introduction

Recently, researchers thought more and more about the manufacture industrial distribution and specialization in China. The related empirical research includes Young (2000), Bai (2004), Fan (2004), Lin (2007), Miao (2007), Xu (2008), etc. But for the service sector, the discussion is not as comprehensive as manufacture sector. There are two probable reasons: One is the un-tradable characteristic of service product which means low fluidity compared with manufacture sector. Service sector mainly provides services for local residents in local market area; therefore, the topic of location choice and specialization is not important. The second reason is accessing statistical data of service industry is difficult for researchers. The classification of service data in yearbook of China (Chinese Statistical Yearbook, 2007) is not well-completed. Service sector is now steadily increasing its importance in the . In 2007, the ratio of agriculture, manufacture, and service sector in the GDP of China is: 11.7%, 49.2%，and 39.1%. In 2008, the ratio turns out to be: 11.3%, 48.6%，and 40.1%. As the industry specialization in the world becomes more and more intensive, the classification of service industry has been much more delicate than ever. For example, the producer service becomes an important component of service sector whose ratio exceeds 70% now. As Krugman(1991) said, some service product is not tradable whose location Gini coefficient is close to zero. The distribution of these service industries is consistent with the demographic distribution of local market; but some kind of service is tradable, for example security, futures, high-tech service and even entertainment service. Their distributions are

1 This work was supported in part by the ―2007 Jin Miao Plan‖ of Fudan University, ―211 Project‖（211XK06）, International Visiting Scholar Program of Harvard Business School. Jie ZHANG is an Associate Professor in Department of Industrial Economics, School of Management, Fudan University, Shanghai, China, 200433. -mail:[email protected]

2 Jie Zhang totally different with un-tradable service. The most remarkable characteristic is agglomeration. For example, the security exchange locates in New York, high tech service in Silicon Valley and Boston‘s Route 128, and movie and entertainment industry in Hollywood of Los Angeles. An important change recently is that accessing of service industry data has become easier. This can be detected through NAICS of 1997 whose most important adjustment is the statistics index of service sector (The North American Industry Classification System (NAICS)). New NAICS system adds some new rising producer service and knowledge intensive industries. In the old SIC systems there are 10 divisions and 5 of them are related with service sectors. In NAICS there are 20 divisions totally, 16 are related with service sectors. In China, new National Economic Industry Classification( GB/T4754-2002) also adds six new divisions including ―information transmission, computer service and software‖, ―hotel and meal‖, ―lease and business service‖, ―water conservancy, environment and public establishment‖, ―education‖, ―international organization‖ (National Bureau of Statistics of China, GBT4754-2002). And in 2006, the National Bureau of Statistics published the statistics data of culture industry in China ( Industry Development Report, 2006). All these indicate that the service sector is becoming a significant part of the economy in China. The detailed research about service industry is urgently needed. We will focus on the regional specialization of service sector in China. Regional specialization is defined as the distribution of the shares of an industry i in total manufacturing in a specific region j compared to a norm. A region j is found to be specialized in a specific industry i if this industry has a high share in the manufacturing employment of region j. The manufacturing structure of a region j is ‗highly specialized‘ if a small number of industries have a large combined share in the total manufacturing (Traistaru and Iara, 2002). To measure the regional specialization, Location Quotient (LQ), is used to measure the ‘revealed’ location advantages of certain regions to attract and develop certain industries (Isard et al. 1960) in spatial economics, using employment data. In fact, employment data are used in a number of studies on the regional specialization of economic activities in the United States (Kim, 1995; Ellison and Glaeser, 1997; Dumais et al., 1997). Bai. etc (2004) construct a Hoover coefficient using output data instead of employment data. A Hoover coefficient of localization can also be constructed from employment data. Krugman Specialization Index is another index to measure the specialization of different region. This index is a relative measure of regional specialization and was first used in Krugman (1991), comparing the industrial structures of the US and Europe. It sums up the absolute difference of the industrial structures of two regions (Traistaru and Iara, 2002). We will give the detail function of LQ and Krugman Index later. Existing research about regional specialization of China are mainly from Cheng and Huang (2005, 2006). In the paper of 2005, they use LQ , RCA and K-spec three indexes to analyze the regional specialization of service industry and its inside sectors in China. They found that there are some essential differences between the service and manufacture sector. It is improper to overemphasize the regional division and specialization of service industry. Huang and Cheng use six most developed provinces in China as research samples, , Shanghai, , , and . Using index of LQ, RCA and K-spec, they find: Inside the service sector, the difference of those traditional service industries among 6 provinces was shrinking while the difference of knowledge intensive service industries was increasing. Using K-spec index, we calculate the specialization of service sector in 29 provinces of China from 1993-2006. The difference between this research and Cheng and Huang is: they calculate the K-spec index of east\middle\west area from 1990 to 2002, but not on the level. Our calculation is based on the province data, and we find the

The Regional Specialization of Service Sector in China 3 trend of specification in service sector is downward firstly, and then upward. We explain this trend. And then we analyze the detailed industries inside the service sector using the Location Quotient. At last, we compare the degree of specialization between each other of 10 provinces which locate in Bohai Rim, River Delta, and Pearl River Delta.

2. Methodology and data

2.1. Methodology The indexes we use to measure the regional specialization are location quotient, Krugman specialization index. These two are the most popular and effective indexed to measure the agglomeration in regional science. 1. Location quotient Location quotient is an index which is in common use to scale the specialization of an area. Its formula is shown below (Cheng and Huang, 2005):

LQ  [e / e ]/[E / E ] ik ik k ik ik k ik

e is the amount of employment of industry k in area i， e is the total employment of area i, E is the ik k ik ik amount of employment of industry k in all over the country, E is the total employment in all over the country. k ik

If the index LQik is bigger than 1, it means that the specialization of industry k in area i is greater than the average level of all over the country. 2. Krugman specialization index Our approach to specialization is to calculate a measure which allows us to compare each province's industrial structure with that of the average of the rest of the other provinces. To construct this measure, referred to as the Krugman specialization index, also called K-spec index, we proceed as follows. For each province, we calculate the share of industry k in that province's total employment, denoted sik . Corresponding to this, we calculate the employment share of the same industry in the production of all other provinces. We then measure the difference between the industrial structures of province i and all other provinces by taking the absolute values of the difference between these shares, summed over all industries (Traistaru and Iara, 2002). Krugman specialization index is calculated as below: first compute the difference of specialization of one area with the other areas in the whole country, and then sum the absolute values of all the differences. This index shows the industry specialization of one area compared with other areas (Miao, 2007).

K  s  s i k ik ik

is the ratio of employment of industry k in area i to all the employment of this area.

s  Eik ik E k ik

sik is the ratio of employment of industry k in all areas except i to all the employment of these areas.

4 Jie Zhang

 Eik s  ji ik E k  ji ik The number of Krugman specific index is between 0 and 2. If it is 0, there is no difference between the specialization of objective area and the average area. Their industry structures are the same. If it is 2, then the objective area has its own unique industry structure which is totally different with others.

If we scale the difference of specialization between two areas directly, we can substitute the sik for another

area‘s s jk ,

E K  Eik  jk ij k Ei E j Then we get the inter-area specialization index. The same as before, if this index equal to 0, there is no difference between area i and j; if it is equal to 2, they are totally different. We use these two indexes to measure which regions and countries have what types of comparative advantages while correspondingly different answers will be given to the question of the most desirable policy response.

2.2. Data We use the employment data of service sector in China and the time period is from 1993 to 2006. There are two reasons for using employment data: one is the data accessibility. The statistics of production value or added value for service sector is cursory compared with statistics of employment. In the yearbook of 2007 for the statistics of value added, service sector is divided into 6 detailed industries, but for the statistics of employment, it is divided into 14 detailed industries; the second reason is that most researchers think the value added of service sector in China is underestimated(Xu, 2004). Compared with the value added data, the employment data is more credible. All the data in this paper is from “China Statistical Yearbook”, from 1994 to 2007.

3. Calculation of regional specialization

We calculate the K-spec index of 29 provinces in China from 1993 to 2006 (The data of miss a lot so we don‘t include Tibet, was separated from Province in 1997, in order to get consistent result, we add Chongqing to Sichuan in the calculation after 1997). We list the result in Table 1 on the next page (Because of the capability of the tabulation, we omit the data of three years, 1994, 2002, 2004).

1. The specialization of service sector in China is lower than manufacture sector. According to the result of Xu (2008) and Miao (2007), the K-spec index of manufacture sector is usually bigger than 0.2. In our result for service industry, a lot of provinces‘ value is smaller than 0.2, some even smaller than 0.1. This indicates that the specialization of service industry is not so distinctly as manufacture industry. Of course this is related with the characteristics of service industry, as we mentioned earlier, a lot of service products is for local market and have no fluidity. 2. We can divide all the 29 provinces into 3 levels according to their specialization data. The first tier is Beijing and Shanghai, who have the highest specialization level in all the provinces. This result meets our expectation.

The Regional Specialization of Service Sector in China 5

Table 1. K-spec index of service sector in China from1993 to 2006

1993 1995 1996 1997 1998 1999 2000 2001 2003 2005 2006

Beijing 0.480 0.603 0.446 0.448 0.466 0.493 0.596 0.606 0.639 0.692 0.702 1.463 0.186 0.322 0.223 0.257 0.227 0.237 0.238 0.255 0.264 0.288 0.301 1.618 0.142 0.222 0.135 0.155 0.140 0.143 0.150 0.133 0.170 0.192 0.193 1.359 0.098 0.198 0.098 0.097 0.101 0.122 0.133 0.127 0.132 0.144 0.146 1.490 Inner 0.102 0.184 0.086 0.105 0.145 0.178 0.178 0.191 0.140 0.183 0.182 1.784 0.157 0.331 0.226 0.225 0.199 0.210 0.213 0.211 0.157 0.180 0.183 1.166 0.155 0.236 0.121 0.136 0.100 0.109 0.112 0.123 0.165 0.156 0.147 0.948 0.225 0.325 0.203 0.193 0.140 0.154 0.157 0.162 0.196 0.198 0.209 0.929 Shanghai 0.327 0.427 0.359 0.392 0.397 0.388 0.401 0.439 0.430 0.474 0.482 1.474 Jiangsu 0.142 0.256 0.157 0.144 0.169 0.176 0.157 0.143 0.127 0.149 0.155 1.092 Zhejiang 0.090 0.207 0.102 0.093 0.117 0.107 0.118 0.172 0.163 0.189 0.194 2.156 0.091 0.176 0.087 0.090 0.113 0.118 0.127 0.138 0.149 0.179 0.196 2.154 0.164 0.293 0.181 0.163 0.153 0.157 0.164 0.155 0.131 0.148 0.147 0.896 0.113 0.207 0.099 0.107 0.125 0.116 0.120 0.143 0.157 0.182 0.184 1.628 Shandong 0.095 0.213 0.126 0.127 0.132 0.136 0.136 0.146 0.165 0.181 0.192 2.021 Henna 0.133 0.247 0.131 0.123 0.117 0.118 0.130 0.161 0.178 0.206 0.202 1.519 0.102 0.210 0.102 0.114 0.102 0.097 0.098 0.099 0.072 0.104 0.089 0.873 0.088 0.192 0.096 0.097 0.130 0.134 0.139 0.165 0.173 0.234 0.235 2.670 Guangdong 0.148 0.234 0.110 0.103 0.127 0.129 0.124 0.148 0.138 0.189 0.192 1.297 0.205 0.324 0.216 0.204 0.167 0.176 0.156 0.163 0.151 0.166 0.168 0.820 0.130 0.218 0.152 0.143 0.166 0.164 0.185 0.154 0.188 0.170 0.169 1.300 Sichuan 0.098 0.211 0.100 0.104 0.167 0.132 0.153 0.164 0.153 0.147 0.153 1.555 0.257 0.378 0.260 0.264 0.224 0.231 0.225 0.228 0.207 0.264 0.271 1.054 0.248 0.349 0.235 0.226 0.185 0.173 0.157 0.161 0.162 0.226 0.219 0.883 0.156 0.262 0.164 0.167 0.156 0.163 0.163 0.151 0.109 0.153 0.157 1.006 0.135 0.208 0.143 0.149 0.110 0.122 0.136 0.115 0.156 0.177 0.178 1.319 0.253 0.251 0.264 0.244 0.219 0.211 0.217 0.260 0.187 0.240 0.232 0.917 0.209 0.247 0.224 0.228 0.153 0.126 0.130 0.113 0.128 0.171 0.170 0.813 0.203 0.274 0.215 0.221 0.178 0.195 0.204 0.218 0.144 0.166 0.174 0.857 Source: Author Calculates according to Chinese Statistical Yearbook, from 1994 to 2007

The second tier includes 15 provinces, Guizhou, Tianjin, Qinghai, Yunnan, Liaoning, Heilongjiang, Xinjiang, Guangxi, Ningxia, Fujian, Hainan, Shanxi, Sichuan, Hebei, (The sequence is from high to low according to average data of every province which is from 0.16-0.26). In all these 15 provinces, most of them are provinces from mid and west except Tianjin, Fujian, Hainan2. This is similar with the result of Xu (2008) whose conclusion is the

2 12 provinces of east include: Beijing, Tianjin, Hebei, Liaoning, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, Guangxi, Hainan; 9 middle provinces include: Shanxi, , Jilin, Heilongjiang, Anhui, Jiangxi, Henan, Hubei, Hunan; 10 west provinces are: Chongqing, Sichuan, Guizhou, Yunnan, Xizang, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang.

6 Jie Zhang manufacture specialization of west provinces is higher than mid and east areas. The explanation is the economic lag of mid and west areas which then engender the number of service divisions in these areas is smaller than east areas, and then their specialization is higher than east areas. The third tier includes Jiangsu, Hunan, Guangdong, Shandong, Gansu, Inner Mongolia, Jilin, Zhejiang, Jiangxi, Anhui, Shanxi (Sequence according to average data of every provinces, all of them is smaller than 0.16 ). What is interesting here is that China has six most developed cities /provinces in China, four of them belong to third tier, just except Beijing and Shanghai. 3. We turn to the progress of every province‘s specialization in these years. Look through tab1, we can find the trends of specialization in all the provinces are the same: upward from 1993 to 1995, and downward from 1995 to 1998, then upward again from 1999. The trend is showed in figure 1 as below. Why do they have turn point in the years of 1995, 1998, 1999? Are there any significant events for these years?

Local Specialization

Time sequence 1993-1995 1995-1998 1999-2006

Figure 1. The basic trend of service specialization in China from 1993 to 2006

The service industry in China didn‘t begin its stable and smooth development until 1990s, especially after 1992 as depicted in Figure 2. In 1992 the State Department of China decided to expedite the tertiary industry. The State Council issued ―Decision of Accelerate the Development of Tertiary Industry‖. In this decision, China announced ―the development of tertiary industry should be faster than the first and second industry‖. After the announcement of the decision, service industry started to grow faster, and the price index of service sector also had risen rapidly during 1992 to 1998. As a result, the nominal development speed of service industry is greater than its actual development speed. This sends us a strong signal that the supply can‘t meet the demand. We can segment our analysis in three period sects, 1990-1994, 1995-1998 and after 1999. Service industry has experienced primary specialization during 1990 to 1994 and set up some basic departmental foundation, and then the service specialization kept rising in these years. During 1995 to 1998, service sector had undergone a rapid development and the reform of university education and medical treatment were implemented in this period. But for every province, the expansion of demand made the service sector under the process of rapid outspreading. And they didn‘t go into the process of integration and specialization. Then the

The Regional Specialization of Service Sector in China 7 specialization index didn‘t make any progress, its value went downward instead of upward which means the service structure of all the provinces tended to be the same. After 1999, the price index became stable and the service industry came into a new period, producer service began to agglomerate in east area. Service industries started their specialization process and the index kept rising again.

Thin line is nominal growth speed, and thick line is actual growth speed. Figure 2. The development of tertiary industry in China: 1979-2006(%) Source: Li, Gu, and Chen (2008), The Development and Characteristics of Tertiary Industry in China

4. Computation of location quotient

Although the specialization of service sector as a whole has experienced downward and then upward since 1993, for producer service, it always kept agglomerating to big cities like Beijing and Shanghai. We compute the location quotient of agriculture, manufacture and service of 29 provinces from 1993 to 2006. We find the ratio of agriculture in provinces of east area is descending rapidly; Manufacture sector is agglomerating in east provinces, especially Jiangsu, Zhejiang, Fujian, Guangdong, Shandong; Traffic and transportation, wholesale and retail, finance and insurance, scientific and technology service converge in Beijing, Shanghai and Tianjin. We list the location quotient of 10 provinces in Table 2 (see next page), Bohai Rim (Beijing, Tianjin, Hebei, Liaoning, Shandong), Yangtze River Delta (Shanghai, Jiangsu, Zhejiang) and Pearl River Delta (Guangdong, Fujian). Beijing is especially good at Scientific Technology service, its LQ index is 6.41 in 1993 and 3.11 in 2006. Financial service of Shanghai is excellent whose LQ index is 2.08 in 2006. Tianjin, Jiangsu, Zhejiang, Fujian and Guangdong are also adept at manufacture sector whose LQ indexes have outstanding performance.

8 Jie Zhang

Table 2. The location quotient of 10 provinces in 1993 and 2006

Hospital,

W and

A M Finance

C O S Transportation Reta W S T Scientific

torage, torage,

ervice

echnology echnology

griculture ommunication

ffice, ffice,

elfare

anufacture

hole hole

Social Social

i

l

S

G

ale and and ale P

ym ym

ost

,

1993 0.21 0.82 0.68 0.88 0.68 6.41 0.93 Beijing 2006 0.16 0.71 1.63 1.64 1.02 3.11 0.77 1993 0.18 1.27 1.06 0.99 0.66 1.31 0.91 Tianjin 2006 0.11 1.46 1.12 1.16 0.78 1.39 0.87 1993 0.41 1.02 0.92 0.92 1.13 0.52 0.87 Hebei 2006 0.47 0.84 1.00 1.17 1.18 0.76 1.04 1993 0.73 1.19 0.89 0.86 0.72 0.71 0.75 Liaoning 2006 1.68 1.01 1.32 0.76 1.09 0.98 1.01 1993 0.22 1.39 1.26 0.89 0.58 1.67 1.03 Shanghai 2006 0.08 1.23 1.86 1.23 2.08 2.44 1.11 1993 0.70 1.23 1.10 1.09 0.87 0.81 0.99 Jiangsu 2006 0.62 1.50 0.92 0.93 0.97 0.68 0.99 1993 0.37 1.20 1.02 1.08 1.29 0.61 1.22 ZheJiang 2006 0.08 1.42 0.62 0.76 1.06 0.67 0.92 1993 0.32 1.08 0.85 1.06 1.07 0.64 1.12 Shandong 2006 0.18 1.34 0.64 0.92 0.78 0.45 0.88 1993 0.76 1.12 0.96 0.81 1.14 0.49 1.01 FuJian 2006 0.44 1.79 0.66 0.61 0.74 0.48 0.64 1993 0.78 0.99 1.09 1.21 1.40 0.55 1.02 Guangdong 2006 0.29 1.42 0.96 0.96 1.10 0.68 0.93 Source: Author calculates according to Chinese Statistical Yearbook, 1994 and 2007, The Bold Faced numbers mean some context we should pay attention to, for example fast increasing or fleetly decreasing.

These 10 provinces are the focus of regional researchers, so we calculate the inter-province service specialization index among them. The result is shown in Table 3 on the following page. According to the data in Table 3, we can find the service industry structure of Beijing is unique one among the 10 provinces. It has big gap with other provinces, especially with Hebei, Shandong and Jiangsu (The index are 0.818、0.794、0.717 separately). Shanghai and Tianjin are the two which are similar with Beijing. This result makes sense. Hebei locates around Beijing, and of course its service firms are attracted by Beijing so that Hebei hasn‘t been able to develop its service sector. Shandong and Jiangsu attracted large amount of Foreign Direct Investment (FDI) and have developed strong manufacture industry in recent years, but they are a little bit lag on the development of the service sector.

The Regional Specialization of Service Sector in China 9

Table 3. K-spec index of 10 provinces in 2006 Beijing Tianjin Hebei Liaoning Shanghai Jiangsu Zhejiang Shandong Guangdong Fujian Beijing 0.000 0.471 0.818 0.674 0.411 0.717 0.632 0.794 0.542 0.674 Tianjin 0.471 0.000 0.412 0.250 0.290 0.301 0.297 0.390 0.246 0.325 Heibei 0.818 0.412 0.000 0.294 0.591 0.157 0.298 0.111 0.303 0.174 Liaoning 0.674 0.250 0.294 0.000 0.383 0.191 0.197 0.286 0.199 0.212 Shanghai 0.411 0.290 0.591 0.383 0.000 0.473 0.397 0.570 0.394 0.477 Jiangsu 0.717 0.301 0.157 0.191 0.473 0.000 0.208 0.159 0.201 0.112 Zhejiang 0.632 0.297 0.298 0.197 0.397 0.208 0.000 0.257 0.142 0.207 Shandong 0.794 0.390 0.111 0.286 0.570 0.159 0.257 0.000 0.289 0.190 Guangdong 0.542 0.246 0.303 0.199 0.394 0.201 0.142 0.289 0.000 0.160 Fujian 0.674 0.325 0.174 0.212 0.477 0.112 0.207 0.190 0.160 0.000 Source: Author calculates according to Chinese Statistical Yearbook, 1994 and 2007.

Tianjin as a municipality is also different with other three provinces of Bohai Rim. The same in Yangtze River delta, municipality Shanghai is dissimilar with Jiangsu and Zhejiang. Other provinces don‘t have significant difference between each other. For example, the index between Guangdong and Fujian is only 0.16. We can draw a conclusion that the municipality has remarkable advantage in specialization of service sector. After the initial adjustment, service sector in every province shows different development direction and speed. Those untradeable sectors still stay in local market and keep the distribution consistent with demographic distribution; but for those tradable sectors such as finance and technology service, they are influenced by the human capital, infrastructure and distribution of manufacture sector. They tend to agglomerate in big cities with good information facilities, frequent market communication, plentiful human capital and high quality science and technology establishment. And because these tradable industries usually have externality, they will tend to congregate more after initial agglomeration.

5. Conclusion and Policy Implication

We calculate the Krugman specialization and location quotient of 29 provinces in China. And we compare the 10 provinces of Bohai Rim, Yangtze River Delta and Pearl River Delta. Our main conclusions are: 1. The degree of service specialization in China is lower than manufacture sector. The different characteristics of inside detailed industries in service sector make some of them will not participate in the specialization and some of them will agglomerate in different areas. 2. The specialization of service industry has experienced downward first and then upward since 1990s. At the beginning of 1990s, blowout of demand hindered the specialization of service sector. After 1999, this industry kept on a normal track of development, and then the specialization speeded its pace. 3. Big cities have advantages in service specialization, especially in the producer service and knowledge intensive service. Beijing, Shanghai and Tianjin are the top-flight areas in service specialization. At the same time, we have some insight for the policy makers and business people. 1. The service sector of China is still under climbing and comparatively undeveloped. Its ratio in GDP is only about 40%, but for USA and most developed countries, the ratio of service sector amounts to more than 80%.

10 Jie Zhang

The reason is that most service industries in China are still included in manufacture sector and don‘t have detailed industrial specialization. After 30 years‘ economic reform, China has started to expedite in the industry specialization. As we can see in the empirical result, economic big provinces like Jiangsu, Zhejiang, Shandong, Guangdong, they are good at manufacture but not service sector. The regional specialization of service sector in these provinces is just at the stage of very beginning. There are a lot of opportunities for business people who are searching for chances in professional services such as legal service, auditing, design, etc. These industries are underway in China, especially in metropolitan cities of China. 2. The most developed parts of China are located around the coast, which are Bohai Rim, Yangtze River Delta and Pearl River Delta. A lot of industries in these three areas agglomerate in one city or province. For example, in Bohai Rim (Beijing, Tianjin, Hebei, Liaoning, Shandong), most professional service industries agglomerate in Beijing (Capital of China). In Yangtze River Delta (Shanghai, Jiangsu, Zhejiang), the Financial service clusters in Shanghai. This means some industries in these developed cities eradiate their service capability to provinces and areas around. For policy makers, it is important to realize the specific function of these metropolitan cities and make well use of the industry radiation, Because of the limit of the data, we don‘t have any in-depth conclusion about a specific industry‘s regional specialization, such as financial service. For business people and policy makers, the conclusion about a detailed and specific industry will be much more revelatory. This is what we want to do in the future work.

Figure 3. Provincial Map of China Source: http://www.chinahighlights.com/map/china-provincial-map/

The Regional Specialization of Service Sector in China 11

Acknowledgement I would like to thank co-editor in chief Minder Chen and two anonymous reviewers for their constructive comments on the earlier version of the manuscript. This work was supported in part by the ―2007 Jin Miao Plan‖ of Fudan University, ―211 Project‖ (211XK06), International Visiting Scholar Program of Harvard Business School.

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