### Paper Menu >>

### Journal Menu >>

Modern Economy, 2010, 1, 206-211 doi:10.4236/me.2010.13023 Published Online November 2010 (http://www.SciRP.org/journal/me) Copyright © 2010 SciRes. ME Study the Doub le - Transfer Pa th o f Gu a ngdong Province on Gravity Model and Cluster Analysis ——Taking Foshan’s Ceramics Industry as an Example Yun Liang1, Xiaode Zuo2 1Guangdong University of Financ e, Guangzhou, China 2Management School, Jinan University, Guangz hou, China E-mail: tliangy5@163.com, tzuoxd@jnu.edu.cn Received September 12, 2010; revised October 15, 2010; accepted October 18 Abstract Gravity model and system cluster method are integrated in this paper to generate a regression analysis on the gravity of many transferees of Foshan’s ceramics industry, which are discussed under the background of the industry and human resource transfer practice. Also the value and role orientation of the industries, enter- prises and governments in the transfer process are explored, which provides theoretic guidance to the transfer practice. The analyzing results show us, the gravity of transferees in Guangdong province is bigger when compared to other areas. Keywords: Industry Transfer, Gravity Model, Cluster Analysis, Regression Analysis A large scale of enterprises has emerged since china’s reform and opening up, which constitute to a certain in- dustry structure. Along with the spread of financial crisis, the mode of export-oriented economy confronts great difficulties that never seen, putting the industry structure upgrading and transformation at the edge. The concept of “Double- transfer” was created in Guangdong Province of China, which contains industry transfer and labor transfer, means that the labor-intensive industry will transfer from Pearl River Delta to east, west and north Guangdong; while the labor of east, west and north Guangdong will transfer to local secondary and tertiary industry, some of qualified ones will transferred to Pearl River Delta area. Transfer from advanced economies to developing ones is the basic path of industry transfer, with the aim of shortening regional economic gap and promoting harmo- nious development. Lots of factors can affect industry transfer, natural resource, labor, capital, technology, in- frastructure, geographical location, cultural environment, policy environment, market environment and so on. The following questions come whether double-transfer will successfully carry out. What kinds of industries and labor should be transferred? Where should they be transferred? This paper applies the gravity model and cluster analysis to industry transfer, tries to evaluate the influen- tial factors to them, calculates every city’s gravity through cluster analysis, whose outputs would be taken as the inputs to do the electrometrical analysis, through which all factor’s parameters can be decided, providing theoretical guidance to the double- transfer practice. 1. Descriptions to the Gravity Model The gravity model is based on the theory of Universal Gravitation Principal. It goes that, the gravity between two objects obeys to the function: 12 2 ij M M ij D FG (1) while i M , j M means the mass of the two objects, ij is the distance between them, and is the gravity con- stant. D G Ever since 1960s, some scholars began to use gravity model to research bilateral trade volume [1,2]. Reference [3] used GDPs of two countries to replace the objects’ mass, and the distance between two countries to that be- tween the objects. The logarithm form was adopted to make the model linear. He analyzed bilateral trade data of 15 developed countries and 3 developing countries of year 1959 and found out that, the bilateral trade flow is greatly dependent on the economic scales of two coun- tries and the geographical distance between them. Al- most at the same time, German economist Poyhonen (1963) [4] studied bilateral trade with gravity model. Y. LIANG ET AL. 207 Trading gravity model can be simply expressed as ij ij ij YY TD [5]. while is the trade volume be- ij T tween two countries, i and Y j Y are GDPs of country and country , ij is the distance between the two countries, and ij D is a constant. From the model, the bilateral trade volume is positively related to economic scales of the two countries and negatively related to the distance between them. Gravity model improves itself along with its wide ap- plication. For example, Linnemann added population as a new explanatory variable to the model. While in 1970s, many variables such as virtual variables, non-tariff cov- erage index, bilateral exchange rate, income per capita, common language, population intensity and so on were introduced into the model. Although it is been doubted and criticized for lacking of theoretical foundation, it has won big success in practical use. [6-11]. However, grav- ity model is seldom seen to be used in studying industry transfer. Reference [12] conducted a research on the transfer of Electronic and communication equipment manufacturing industry between 2001 to 2003. System cluster is the most widely used cluster method. Its basic concept lies in, take each sample as a cluster, combine the closest ones according to the sample’s simi- larity, and calculate the distances between the combined clusters, then combine them as above. Continue the process until all the samples become one cluster. Among them, the square of Euclidean distance is used to evalu- ate the similarity among clusters, and averaging method is used as cluster method. 2. Model Descriptions 2.1. Set up the Model Every industry has its own characteristics and different influential factors. Here ceramic industry of Foshan city is chosen to illustrate the application of gravity model. First the model brought by Tinbergen, 3 12 4 0iji jij ij X YY DP , is written into the form of natural logarithm: 01234 i lnln +ln+ ln+ln+ lnP iji jij XYYD j (2) Some of the parameters are re-defined according to industry transfer practice. 1) i = 1, 2……n, indicates the cities that an industry transfer from, j = 1,2……m，indicates the cities that an industry transfer to. ij X means the gravity between two cities. 2) i, j demonstrate industry outputs of city i and city j. The bigger the output is, the stronger the gravity to an industry. Y Y 3) ij is the economic distance between the two cit- ies, whose value is obtained from two time’s weighting to their physical distance. The function of economic dis- tance can be expressed as: D ij DD (3) D is the geographical distance, is the geographic weight, Which decided by the transportation situations between two cities, is the economy weight decided by the ratio of GDP per capita of the transferee and transferor cities. Table 1 shows how the economic dis- tance is calculated. 4) ij is the transferring parameter between two cities, measured by two governments’ beneficial policies to the certain industry. The gravity will be bigger if the gov- ernments offer some convenience. Here in the double- transfer practice, ij P = in Guangdong province, and 0 in other regions. P 1 5) the labor volume is inneglectable, rich human re- source is an important attractions to industry transfer, the permanent residence is used in this function. 6) special resource gift of transferee areas. The devel- opment of a certain industry relies on certain resources, such as land, energy and so on. Therefore, if the region possesses resource, it has a value of 1, 0 if it doesn’t. Table 1. Parameters of economic distance. Geographical distance weight Transportation tool train van ship Train and vanTrain and shipVan and ship Train, van and ship 1 1.2 1.5 0.7 0.8 1.1 0.5 Economic distance weight GDP per capita that industry transfers from/GDP per capita that industry transfers to > 70% 70% ≥ ratio ≥ 45% < 45% 0.8 1.0 1.2 Copyright © 2010 SciRes. ME Y. LIANG ET AL. Copyright © 2010 SciRes. ME 208 Based on the above description, the new model can be written as 01 23 45 ln+ln +lnln ijj ijj jij F YD la Presj b (4) We can conclude 5 factors that affect a city’s gravity to an industry, they are industry output, economic dis- tance, labor volume, beneficial policies and natural re- source gift. The data of these 5 factors are used to cluster analysis to measure each city’s gravity. 3. Double Transfer of Foshan’s Ceramics Industry 14 cities are selected as potential areas that the industry will transfer to: Qingyuan, Zaoqing, Heyuan, Jiajiang, Jingdezhen, Gaoan, Fengcheng, Liling, Huanggang, Zibo, linyi, Faku, Jinjiang, and Yining. First we calculate the economic distance between the above cities and Foshan, the results are shown in Table 2. Other parameter’s values are shown in Table 31: SPSS16.0 is adopted to do the cluster analysis. Stan- dardize all variables and make them easy to be com- pared. The classfing results are shown as in Figure 1 and Figure 2: Dendrogram using Average Linkage (Between Groups) Figure 2 shows the situations when the 14 cities been classified to 2, 3, 4, 5 and 6 clusters. It is quite obvious that if been classified by gravity, from bottom to up, to 2 clusters, Faku and Yining are in one cluster and the other 12 cities in the other group; if been classified into 3 clus- ters, Yining in one cluster, Faku another, and the remain- ing cities the third. If 6, Yining the first cluster, then Faku, Linyi the third, Jingdezhen the forth, Huanggang, Jiajiang, Liling, Jinjiang, Gaoan, Fengcheng and Zibo the fifth, and Qingyuang, Zaoqing Heyuang the sixth cluster. Only four factors’ influences have been considered in the model. After cluster analysis, the industry transferring direction is quite clear and practical: the potential areas with biggest gravity are in group one, Qingyuang, Zaoqing and Heyuang. That is because of short economic distance and governments’ great push on double-transfer policy. Jiajiang and Liling have sound transportation conditions and are rich in resources, some places such as Gaoan and Fengcheng have already formed the ceramics industry chain. While with a long distance from Foshan, weak transportation situation and low GDP level, Yining has little gravity to the ceramics industry even it possess many natural resources and has a great market coverage. It is noted that, although Jingdezhen is a famous city with de Table 2. Economic distance between Foshan and potential cities. No. Potential cities D (km) Dij 1 Qingyuan74.06 Train, van 0.7 1.20 62.2104 2 Zaoqing 70.35 train, van 0.7 1.20 59.094 3 Heyuan 185.73train, van 0.7 1.20 156.0132 4 Jiajiang 1210.15train, van 0.7 1.20 1016.526 5 Jingdezhen804.7 train, van 0.7 1.20 675.948 6 Gaoan 641.97van 1.2 1.20 924.4368 7 Fengcheng629.71train, van 0.7 1.20 528.9564 8 Liling 516.39train, van 0.7 1.20 433.7676 9 Huanggang845.96van 1.2 1.20 1218.182 10Zibo 1611.15train, van 0.7 0.80 902.244 11Linyi 1431.44train, van 0.7 1.20 1202.41 12Faku 2367.24van 1.2 1.20 3408.826 13Jinjiang 590.52Van, ship 1.1 1.00 649.572 14Yining 3714.63Van 1.2 1.20 5349.067 Table 3. Parameter’s value of potential areas. No. Potential cities Y (100 million Yuan) Dij (km) Lab (1000 per)Pij Res 1 Qingyuan21.86 62.2104 365.87 1.50 2 Zaoqing 9.01 59.094 375.20 1.50 3 Heyuan 6.14 156.0132 281.82 1.50 4 Jiajiang 50.00 1016.526 35.00 1 0 5 Jingdezhen42.00 675.948 155.44 1 0 6 Gaoan 12.46 924.4368 80.80 1 1 7 Fengcheng10.00 528.9564 133.30 1 0 8 Liling 90.00 433.7676 98.39 1 0 9 Huanggang8.00 1218.182 666.70 1 0 10Zibo 18.00 902.244 419.59 1 0 11Linyi 17.00 1202.41 1027.50 1 0 12Faku 113.40 3408.826 45.00 1 1 13Jinjiang 70.00 649.572 158.70 1 0 14Yining 3.00 5349.067 44.22 1 1 1Data of GDP per capita and labor volume are from statistical yearboo k of 2008. Y. LIANG ET AL. 209 Rescaled Distance Cluster Combine 6 ─┬─────┐ 7 ─┘ ├───┐ 9 ───┬───┘ │ 10 ───┘ ├───────┐ 8 ─┬─┐ │ │ 13 ─┘ ├───────┘ ├─┐ 4 ───┘ │ │ 5 ───────────────────┘ ├───────┐ 2 ─┐ │ │ 3 ─┼───────────────────┘ ├───────────────────┐ 1 ─┘ │ │ 11 ─────────────────────────────┘ │ 12 ───────────────────────────────┬─────────────────┘ 14 ───────────────────────────────┘ Figure 1. Cluster tree chart. Cluster Membership Case 6 Clusters 5 Clusters 4 Clusters 3 Clusters 2 Clusters 1 1 1 1 1 1 2 1 1 1 1 1 3 1 1 1 1 1 4 2 2 1 1 1 5 3 2 1 1 1 6 2 2 1 1 1 7 2 2 1 1 1 8 2 2 1 1 1 9 2 2 1 1 1 10 2 2 1 1 1 11 4 3 2 1 1 12 5 4 3 2 2 13 2 2 1 1 1 14 6 5 4 3 2 Figure 2. Cluster membership. -veloped ceramics industry, it is catalyzed into the third group for resource, policies reasons. Based on the result of cluster analysis, evaluate the gravity of different group in an up-down order as 6, 5, 4, 3, 2, 1. Then do an electrometrical analysis to the influential factors in Function 3. Regression based on Least Squares method is adopted and Eviews 5.0 is used. The regression results are shown in Table 4. From the table, R2 = 0.914419, the adjusted R2 = 0.860930, which tells that the variables we chose can explain more than 86% of the gravity. F = 17.09564, which is bigger than critical value 2.73. to every single variable, it is found that t-Statistic is not significant, such as Res. That probably because ceramics industry doesn’t rely on resources very much. So the variable Res is kicked out, and regression is done again as shown in Ta- ble 5: R2 of this time is 0.914054, and the adjusted one is 0.875856, the value of F is 23.91928, bigger than F’s value last time, which means the explaintory variables has a better explantation to the explained variable. a new function can be obtained based on function 3: ln6.0267520.007076 ln0.00917 ln 0.001140 ln0.534150 j ij j F jY lab Pj D (5) Here are the explanations: 1) the ceramics industry output is negatively related to the gravity, which is quite reasonable since a big output means a full covered mar- ket, providing great barrier to new entrants; 2) economic distance’s effect is negative, but the parameter’s value is small. It’s easy to understand since with the improve- ments of transportation and economy, economic distance has little effect on ceramics industry, especially this in- dustry doesn’t need much physical transfer, most of the cases are building factories and purchasing equipments in the places that will transfer to. What transfer in the process are just technologies, capital and expertise. Also, economic gap is just a compe concept which can arativ Copyright © 2010 SciRes. ME 210 Y. LIANG ET AL. Table 4. Regression analysis of ceramics industry. Dependent Variable: F Method: Least Squares Date: 07/04/09 Time: 01:34 Sample: 1 14 Included observations: 14 Variable Coefficient Std. Error t-Statistic Prob. C 6.036283 0.423007 14.26993 0.0000 Y –0.007120 0.005169 –1.377319 0.2057 DIJ –0.000893 0.000176 –5.080806 0.0010 LAB –0.001187 0.000668 –1.777148 0.1134 P 0.538737 0.424937 1.267804 0.2405 RES –0.113089 0.612503 –0.184635 0.8581 R-squared 0.914419 Mean dependent var 4.500000 Adjusted R-squared 0.860930 S.D. dependent var 1.506397 S.E. of regression 0.561767 Akaike info criterion 1.982066 Sum squared resid 2.524653 Schwarz criterion 2.255948 Log likelihood –7.874465 F-statistic 17.09564 Durbin-Watson stat 2.171311 Prob(F-statistic) 0.000435 Table 5. Regression results without Res. Dependent Variable: F Method: Least Squares Date: 07/04/09 Time: 14:39 Sample: 1 14 Included observations: 14 Variable Coefficient Std. Error t-Statistic Prob. C 6.026752 0.396677 15.19312 0.0000 Y –0.007076 0.004879 –1.450367 0.1809 DIJ –0.000917 0.000114 –8.057946 0.0000 LAB -0.001140 0.000585 –1.950037 0.0830 P 0.534150 0.400801 1.332708 0.2154 R-squared 0.914054 Mean dependent var 4.500000 Adjusted R-squared 0.875856 S.D. dependent var 1.506397 S.E. of regression 0.530766 Akaike info criterion 1.843461 Sum squared resid 2.535412 Schwarz criterion 2.071696 Log likelihood –7.904230 F-statistic 23.92918 Durbin-Watson stat 2.082530 Prob(F-statistic) 0.000082 Copyright © 2010 SciRes. ME Y. LIANG ET AL. Copyright © 2010 SciRes. ME 211 make up by beneficial policies and low costs; 3) Human resource, replaced by permanent residence, also has a negative but small effect on the gravity, which is quite understandable since ceramics industry doesn’t need large number of qualified labor, making every city’s hu- man resources are sufficient for this industry; 4) gov- ernment policy plays an important role here with a coef- ficient of 0.538737. industry transfer has great influence on both regions that transfers from and transfers to, which deeply relied on goverments’ policies. From this, the importance of Guangdong’s double-transfer to pro- mote industry transfer is quite obvious. 4. Conclusions The influential factors are decided through gravity model, which are taken as the input to cluster analysis, whose results are given different group values as the value of different gravity levels. Then Eviews 5.0 is used to do the regression analysis. The following conclusions are drawn: 1) governments’ beneficial policies play impor- tant roles in industry transfer process, that’s why recipi- ent governments enacted all kinds of polices to attract industries transferring in; 2) as to economic distance, its role in industry transfer is reduced since great improve- ment of transportation and economy conditions national wide; 3) Only five variables are considered in the model and cluster analysis, which maybe cannot explain the real situation sufficiently. Some variables are just hard to be quantified but still have huge influences on industry transfer; 4) also just the ceramics industry of Foshan has been studied in this paper, which is a small fraction of Guangdong’s industry transfer business, more industries’ practice can be research further. Moreover, some of data used in this paper are not so precise because of hard ac- cess. 5. References [1] Anderson and E. A. James, “Theoretical Foundation for the Gravity Equation,” The American Economic Review, Vol. 69, No. 1, 1979, pp. 106-116. [2] D. J. Peng. “Ethnic Chinese Business Network and the Asia Pacific Economic Integration,” Journal of Asian& African Studies, Vol. 35, No. 2, 2000, pp. 229-250. [3] J. Tinbergen, “Shaping the World Economy: An Analysis of World Trade Flows,” New York Twentieth Century Fund, Vol. 5, No. 1, 1962, pp. 27-30. [4] P. Poyhonen, “A Tentative Model of the Volume of Trade between Countries,” The American Economic Re- view, Vol. 2, 1963, pp. 93-99. [5] S. Bin and M. Z. Liao, “Trade Volume and Export Poten- tial of China,” World Economy, Vol. 2, 2004, pp. 3-12. [6] J. H. Zhang, “Study on Investing Country Characteristics and Investment Intensity to China,” World Economy, Vol. 1, 2004, pp. 16-22. [7] X. Ruan and J. H. Zhao, “FDI Location Selection from the View of Gravity Model,” world Economy, Vol. 2, 2004, pp. 67-71. [8] C. C. Zhang, “Analysis on Investment Environment Fac- tors That Affect FDI,” Management World, Vol. 2, 2002, pp. 32-41. [9] K. J. Gu, “International Economics’ Development and Application on the Gravity Model,” World Economy, Vol. 2, 2001, pp. 14-25. [10] H. X. Shi and S. F. Liu, “Study on the transfer of elec- tronic and communication equipment industry based on gravity model,” Industry Technology Economics, Vol. 8, 2008. [11] W. Sun, “Cluster Analysis on Equipment Manufacturing Industry in 29 Provinces of China,” China Technology Forum, Vol. 6, 2005. [12] D. R. Cheng and J. Li, “Study on the Interactivity of City Economics under Mulnucipal Economic Cycles Con- struction,” Technology and Economics, Vol. 2, 2007, pp. 42-44. |