2017 4th Internatonal Conference on Busness, Economcs and Management (BUSEM 2017) Study on the economc dsparty and convergence of urban agglomeraton n the mddle reaches of the Yangtze Rver Chao Wen, Jngjng Chen Department of Fnance and Economcs, Guangdong Unversty of Scence and Technology, Dongguan, Chna Keywords: The Mddle Reaches Of The Yangtze Rver Cty Group; Economc Gap; Convergence; Exploratory Spatal Data Analyss; Spatal Error Model. Abstract. The economc gap s an mportant ndcator of a regonal economc development. Ths paper s about 31 ctes n the mddle reaches of the Yangtze Rver Cty Group years from 2003 to 2013, a total of 11 years of data as the bass, usng spatal dfference ndex to analyss the gap between the economcs of developng ctes. Whle ntroducton of a spatal error model and a spatal lag model of the spatal regresson analyss to provde theoretcal support for the convergence of ts economc development. Comprehensve measure the economc development coordnaton of the mddle reaches of the Yangtze Rver Cty Group n the past 10 years to development the regons better n the future. Introducton So far, there s no specalzed research for the dsparty and convergence of the mddle reaches of the Yangtze Rver cty group. Ths paper wll analyss the gap between the level of regonal economc development, ntegrated by spatal dfference analyss, such as Coeffcent of Varaton, Thel Entropy Index, Hrfndhal-Hrschman ndex and Gn coeffcent. Then ntroduce a spatal error model and a spatal lag model of the spatal regresson analyss to provde a theoretcal support for the convergence of the regonal economc development. Measure the balance of the economc development n the mddle reaches of the Yangtze Rver Cty Group n the past 10 years, for the future development of the regon. Method Knds of spatal ndexes utlze on the study of the economc dsparty. There are many ndexes n measurng regonal economc development gap. The most commonly used are Coeffcent of Varaton (CV), Thel Entropy Index (TEI), Hrfndhal-Hrschman Index (HHI) and Gn coeffcent (Gn). In order to comprehensvely measure the economc development gap between the Yangtze Rver cty group, the economc gap wll be ntegrated wth the four ndcators all above to measure the area, n order to reflect the real stuaton n the regon. Comparson of spatal error model and a spatal lag model of regonal to measure the spatal correlaton and convergence characterstcs. Introduces the spatal econometrcs model to accurately assess the mddle reaches of the Yangtze Rver cty group economc gap s convergence or not n the past ten years. Startng from the analyss of the regonal spatal autocorrelaton, then compare the use of spatal error model (SEM) and spatal lag model (SLM) to analyze the convergence characterstcs of the regonal economy. General Measurement Model (GMM). The form of the GMM s as follows: y ln T = α + β ln ( yo ) + ε Ⅰ yo Copyrght (2017) Francs Academc Press, UK 214
In the model Ⅰ, y T for the cty of fnal per capta natonal ncome level, y O for the cty of begnnng per capta ncome level. Ths model reflects the relatonshp between the ndependent yt varable y O and the dependent varable, f the coeffcent β s postve, the dvergence of yo regonal economc development s postve, and the negatve s convergent. Spatal Error Model (SEM). The spatal error model s constructed as follows: y T λn = α + ρwy + β λn( yo ) + ε yo (Ⅱ) ε = λw ε + µ In the model Ⅱ, λ s the error term of the spatal autoregressve coeffcent, W ε s spatal error spatal lag vector, µ s not related, mean value s 0, wth the same varance of the error term. Ths model s added spatal weght matrx and the spatal error effect, ts postve and negatve coeffcent β also reflects the gap between the regonal economc dvergence or convergence. Spatal Lag Model (SLM). Constructon of the Spatal Lag Model s as follows: y T ln = α + ρwy + β ( yo ) + ε y ln (Ⅲ) O Wy In the model Ⅲ, s due to the varable spatal lag vectors, whch s an endogenous varable, the coeffcent ρ reflects the effect of neghbors on the regon tself, the other coeffcent same model Ⅰ and Ⅱ. Results General development level and gap of the regon. Compared wth the manstream analyss methods at home and abroad, we learn from We Houka (1997) usng the per capta GDP as an ndcator to measure the convergence of Chna's regonal economy. To collect the data of per capta GDP of the urban agglomeraton n the mddle reaches of the Yangtze Rver, 2003-2013, the mddle reaches of the Yangtze Rver Cty Group n 2003 and 2013 dfferences n per capta GDP spatal structure dagram, as follows: PCGDP spatal dfference chart n 2003 PCGDP spatal dfference chart n 2013 Fgure 1: Comparson the per capta GDP spatal dfferences of urban agglomeraton n the mddle reaches of the Yangtze Rver n 2003 and 2013 Accordng to the above s not dffcult to fnd, compared to 2003, n 2013 the Yangtze Rver mddle reaches of urban agglomeraton economc spatal development more balanced. Such as Changsha, the radaton effect s more obvous, the surroundng ctes get better development, formaton of Chang-zhu-tan urban agglomeraton. Another example s Hube Provnce, n addton to Wuhan, grow out of Ychang as the second development poles to promote the development of the surroundng ctes. In Jangx Provnce, such as Nanchang, Xnyu, Yngtan, Jngdezhen and other 215
ctes have started the sgns of development, the future wll form a new growth pole, multple ponts to promote the common development of the surroundng ctes. All of the above shows that the overall economc development gap narrowng n the past 10 years, cultvate a number of new growth poles to promote the common development of the surroundng ctes, showng sgns of convergence of economc development of the mddle reaches of the Yangtze Rver cty group. Measure the development trend of regonal economc dsparty. In order to determne the gap of regonal economc development more accurately, we use the R language calculated the ndexes of economc development level n the mddle reaches of the Yangtze Rver cty group, the result of the Coeffcent of Varaton (CV), Thel Entropy Index (TEI), Hrfndhal-Hrschman Index (HHI) and Gn coeffcent (Gn) showed n the followng table: Table 1 The ndexes of per capta GDP 2003-2013 Gn Thel var hh 2003 0.2655 0.1160 0.5157 0.0408 2005 0.2388 0.0928 0.4528 0.0388 2007 0.2420 0.0936 0.4518 0.0388 2009 0.2536 0.1060 0.4893 0.0399 2011 0.2463 0.0973 0.4604 0.0390 2013 0.2395 0.0914 0.4452 0.0386 From the calculaton results of the Gn coeffcent, Thel Index, Coeffcent of Varaton and Hrfndhal-Hrschman Index, the economc development of the urban agglomeraton n the mddle reaches of the Yangtze Rver shows a certan degree of dfference n each year. They have changed over the years, but the overall evoluton has a downward trend. From the vew of the trend of the change of the four, ts trajectory s also qute consstent n the undulatng stage. Presents the frst ncreased and then decreased the nverted "U" - type movements, the nflecton pont occurred n 2009, especally the Thel ndex s partcularly evdent. In ths note, the economc gap of the mddle reaches of the Yangtze Rver cty group before 2009 s a dvergent trend. In recent years, the trend s convergent, suggestng that regonal economc coordnaton s gettng better and better n recent years, as t shown n fgure 2: Fgure 2. Trajectory of four knds of gap ndexes 216
Dscusson General measurement model and test. In order to further measure the convergence of the economc development level of the urban agglomeraton n the mddle reaches of the Yangtze Rver, we ntroduce an general measurement model Ⅰ. Accordng to the model above, the results of the analyss usng R software are as follows: Table 2 The general measurement model estmaton results Estmate Std.Error t value Pr(> t ) α 3.6478 0.8301 4.395 0.0001 β -0.2370 0.0911-2.602 0.0144 standard error 0.2347 R 2 0.1893 Adjusted R 2 0.1613 F-statstc 6.77 0.0145 Results from the convergence analyss can be found that the regresson coeffcent s -0.2370, the p value s 0.0144, whch s sgnfcant at the 0.05 level. Ths ndcates that the economc development speed of the urban agglomeraton n the mddle reaches of the Yangtze Rver s negatvely related to the begnnng of the perod. In fact, judgng from the varous ndcators of regonal economc development gap, ther average trend n the year of the survey s also declnng, as shown n fgure 2. At the same tme, we found that the development of the urban agglomeraton n the mddle reaches of the Yangtze Rver may be related to the spatal correlaton, the calculaton model of the Moran's I. It can be found that Moran's I = 0.3683, P = 0.0002, s very sgnfcant, whch ndcates that there s a certan spatal autocorrelaton n the economc development of the urban agglomeraton n the mddle reaches of the Yangtze rver. Takng nto account the possble exstence of spatal lag or spatal error n the model, contnung to analyze wth the spatal error model as follows. 4.2 Spatal error model analyss and verfcaton The constructon and sgnfcance of spatal error model are found n the model Ⅱ above. Accordng to the above model, the results of the analyss usng R software are as follows: Table 3 Spatal error model estmaton results Estmate Std.Error z value Pr(> z ) α 2.5536 0.6827 3.7406 0.0002 β -0.1129 0.0738-1.529 0.1263 λ 0.5940 0.0329 std.error 3.626 0.0003 Wald statstc 13.148 0.0003 Log lkelhood 4.2538 AIC -0.5075 It can be found that compared wth the results of general econometrc model to the explaned varable of the spatal error model return coeffcent also s negatve, and the nterpretaton of the results s the same. Spatal autoregressve coeffcent λ =0.5940, P value =0.0003, sgnfcant. At the same tme, the Akake Informaton Crteron (AIC) of the spatal error model s -0.5075, whch s less than the AIC value of the OLS estmaton model 2.044. After addng the spatal error, the model can be mproved, the only problem s that the P value of the model s not very sgnfcant. Spatal lag model analyss and verfcaton. Try to mprove the model I wth the spatal lag model Ⅲ, and see f we can get a better result. Accordng to the above model Ⅲ, the results of the analyss usng R software are as follows: 217
Table 4 Spatal lag model estmaton results Estmate Std.Error z value Pr(> z ) α 2.2204 0.7533 2.9475 0.0032 β -0.1720 0.0757-2.2708 0.0232 ρ 0.5679 0.0081 A std.error 0.1586 0.0003 Wald statstc 12.818 0.0003 Log lkelhood 5.4860 AIC -2.972 test value 0.3276 0.5671 It can be found that the regresson coeffcents of the model explanatory varables are equally sgnfcant. The regresson coeffcent of log (Y2003) was -0.1720, and the p value was 0.0232, whch was sgnfcant. Spatal autoregressve coeffcent ρ =0.5679, P-value=0.0003, are very sgnfcant too, whch ndcates that there s a strong spatal auto regresson n the urban agglomeraton n the mddle reaches of the Yangtze Rver. At the same tme, the Akake Informaton Crteron (AIC) of the spatal error model s -2.972, whch s less than the AIC value of the OLS estmaton model 2.044. After addng the space lag varable, the model can be mproved effectvely. Concluson Through the spatal exploraton of graphc analyss. After the emergence of the development pole drve, the dffuson effect that the surroundng common development s obvous, such as Chang-zhu-tan cty group. As well as, foster the development of a new growth pole to drve growth developments, such as the rse of Ychang. In the comprehensve survey of the regonal economc growth, and fond the area have the obvous spatal correlaton. The convergence of economc development of the urban agglomeraton n the mddle reaches of the Yangtze Rver s explaned. To compare measure spatal lag model and spatal error model. The regresson coeffcent shows that the economc growth rate s negatvely correlated wth the total economc output n the ntal years, that s, the regonal economc development convergence. In fact, from spatal exploraton of graphc analyss and regonal economc dspartes of varous ndcators, have confrmed the convergence characterstcs of the regonal economc development n the mddle reaches of the Yangtze Rver Cty Group n the past 10 years.. References [1] Q Shaozhou,Yun Bo,L Ka. An Internatonal Comparatve Analyss on Chna's Economc Growth and the Convergence n Energy Intensty Gap and Its Economc Mechansm[J]. Chnese Journal of Populaton,Resources and Envronment,2011,02:65-75. [1] Guo Jqang. Measurement and decomposton methods of ncome gap (Englsh). Socal Scences n Chna [J]., 2011,03:181-202. [3] Xe Hualn, Wang We. Chna's major economc cty ndustral zone wth spatal and temporal dfferences n effcency and convergence analyss (Englsh) [J]. Journal of Geographcal Scences, 2015,10:1183-1198. 218