2 8 6 28 No. 6 Vol. 2 0 0 8 1 2 SC IENTIA GEOGRAPH ICA SIN ICA Dec., 2 0 0 8 1, 2, 3 (1., 100101; 2., 100049; 3.,, 130024) : ; 1990, ;, - ;, - : ; ; ; ; : F119. 9 : A : 1000-0690 (2008) 06-0722 - 07, M itchelson R L [ 1 ], [ 2 5 ] [ 6 8 ], [ 9 ] ;, [ 10 ] [ 11, 12 ] [ 13 ],, ;,, 1990, [ 14 ], GIS, 1 1. 1 1990 1995 2000 2005 GDP GDP, 2005, 2005 1. 2 3,, (Wolfson index) ( Tsui - W ang index), : : 2007-07 - 18; : 2007-12 - 14 : (40571050) : (1980 - ),,, GIS E - mail: lixw. 06b@ igsnrr. ac. cn :,,E - mail: xiucl@nenu. edu. cn
723 6 : G = 1 2n 2 u j 6n = 1 i 6n Y j - Y i (1) = 1 : 0 Y j - Y i 0, n, u ( inequality), ( clustering), ( disappearing m iddle class), ( cluster) ( group ),, (polariza2 tion) [ 2, 15 ], [ 5 ] : W = 2 (U 3 - U 1 ) /M (2) : U 3, U 3 = (1 ) ; U 1 1 /2 ; M ( TsuiKai - yuen W angyou - qiang) Wolfson, ( increased bipolarity and in2 creased sp read), Tsui - W ang ( TW, ) [ 16 ] : TW = N 6 k i =1 i y i - m m r (3) : N, i i, k, y i i (1) (2) (3),, m, 1990 2005, r (0, 1), = 0. 5, r = 0. 5 ( 1), 34 ( 0 ( ), ) 1 () ( ), 1. 3 ( GlobalMoran I( GM I) ) ; 2000 Local Moran I(LM I) [ 17, 18 ],,, ;, GM I : 2. 2 n 6 6 n I = n w ij ( x i - x) ( ( ) x j - x) i j i (4) ; S 0 ( x i - x) 2, 6 n i : n, x i x j i j ( GDP GDP), x i, w ij ( n n), S 0 w ij Moran I d,moran I,, GM I,, LM I : I = 6 w ij Z i Z j (5) : Z i Z j, w ij ( p 0. 05 ), I i Z i, i, (HH ) ; I i Z i, i,(hl ) ; I i Z i, i, (LL) ; I i Z i, i, (LH) 2, 1990 2005 2. 1
7 24 28 1 1990 2005 ( ) Fig. 1 Inequality and polarization of economy in municipal jurisdictions in 1990-2005 1990 2005 ; GDP, 2000 ( 2) 2 1990 2005 ( ) Fig. 2 Inequality and polarization of economy in city districts 2. 3 in 1990-2005 148 ( ), 3 ;, ; 2000 2. 4 20 90,, 3 1990 2005 Fig. 3 Inequality and polarization of economy in counties in 1995-2005,,,, 1 2, ; 1 2, ( cluster),, 3,, 3. 1 100 km, GDP GDP, 1, 2 1 GDP Moran I, 1990 2005 GDP,, ( ) GDP
725 6 : 1100 km GDP Moran I ( E ( d) = - 0. 005) Table 1 Moran I ( GM I) of GDP by different spatial adjacency matrix based on topological adjacency and adjacency distance of 100 km ( E ( d) = - 0. 005) 100km I( d) 0. 05 0. 12 0. 03 0. 04 0 0. 02-0. 02 0 Z Score 1. 24 3. 02 0. 84 1. 14 0. 05 0. 17-0. 10 0. 05 2100 km GDP Moran I ( E ( d) = - 0. 005) Tab. 2 Moran I ( GM I) of per cap ita GDP by different spatial adjacency matrix based on topological adjacency and adjacency distance of 100km ( E ( d) = - 0. 005) 100 km I( d) 0. 05 0. 08 0. 08 0. 1 0. 02 0. 24 0. 32 0. 53 Z Score 1. 47 2. 46 0. 48 2. 61 0. 18 1. 74 2. 08 3. 12,, 2 GDP Moran I, GDP 1990 2005,,, 3. 2 GDP GDP Moran I (LM I),, 4 GDP LM I HH 1990,,,,, 1995,, HH HL,,,,,, LL 2000, HH HL, 2005, HH HL,,, 1990 2005, 5 GDP LM I 1990, GDP, 1995, HH, HH ; HH, HH 2000, HH HH, LL ; HH 2005, HH, HH, GDP -,,, GDP
7 26 28 4 1990 2005 GDP LM I Fig. 4 Scatter map s of LocalMoran I (LM I) of GDP in 1990-2005 5 1990 2005 GDP LM I Fig. 5 Scatter map s of LocalMoran I (LM I) of per cap ita GDP in 1990-2005 -, 4 1) 1990,,, 2) ( ),,, -, -, - 3),,, ( ) 4),, GDP, HH, -,
727 6 : 5) : ; ( ); -,,,, 2000,, : [ 1 ] M itchelson R L,Wheeler J O. The flow of information in a global economy: the role of the American urban system in 1990[ J ]. An2 nals A ssociation of American Geographers, 1994, 84 ( 1) : 87-107. [ 2 ] Fedolov Leonid. Regional inequality and polarization in Russia [ J ]. World Development, 2002, 30 (3) : 443-456. [ 3 ] Fritzell J. Income inequality trends in the 1980 s: a five - country comparison. Acta Sociologica, 1993, 36: 47-62. [ 4 ] Fan C C. The temporal and spatial dynam ics of income and pop2 ulation growth in Ohio, 1950-1990 [ J ]. 1994, 28 (3) : 241-258. Regional Studies, [ 5 ] M ichael C, Wolfson. Concep tual issues in normative measure2 ment when inequality diverge [ J ]. The American Econom ic Re2 view, 1994, 84 (2) : 353-358. [ 6 ] Sassen S. The global city[m ]. Princeton, NJ: Princeton Uni2 versity Press, 1991: 156-158. [ 7 ] Fainstein S S. D ivided cities: New York and London in the con2 temporary world[m ]. Oxford: B lackwell, 1992: 123-125. [ 8 ] Marcuse P, R Van Kempen. Globalizing cities an new spatial or2 der? [M ] Oxford: B lcakwell, 2000: 110-113. [ 9 ],. [ J ]., 2000, 20 (5) : 404 410. [ 10 ],.., 2004, 59 (5) : 791 799. [ 11 ],. [ J ]., 2003, 25 (6) : 1 7. [ 12 ]. [ J ]., 2001, 20 (1) : 31 39. [ 13 ],. [ J ]., 2004, 59 (5) : 446 454. [ 14 ],,. [ J ]., 2004, 24 (3) : 320 325. [ 15 ] Xiaobo Zhang, Ravi Kanbur. W hat difference do polarization measures make? An app lication to China [ J ]. The Journal of Development Studies. 2001 (37) 3, 85-98. [ 16 ] W ang Youqiang, Tsui Kai - yuen. Polarization O rdering and New Classes of Polarization Indices [ J ]. Journal of Public Eco2 nom ic Theory. 2000, 3 (2) : 349-363. [ 17 ] CliffA D, O rd J K. Spatial Processes, Models and Applications. London: Pion, 1981. [ 18 ] Anselin L. Local indicators of spatial association: L ISA [ J ]. Ge2 ographical Analysis, 1995, 27: 93-115. New Pa ttern of Reg iona l Econom ic Polar iza tion in the Three Prov inces of Northea st Ch ina L I Xiu2wei 1, 2, X IU Chun2liang 3 ( 1. Institute of Geographical Sciences and N atural Resources Research, Chinese A cadem y of Sciences, B eijing, 100101; 2. Graduate U niversity of the Chinese A cadem y of Sciences, B eijing, 100049; 3. School of U rban and Environm ental Sciences, N ortheast N orm al U niversity, Changchun, J ilin 130024) Abstract: This paper exam ines the spatial polarization of regional economy in the three p rovinces of Northeast China. M unicipal jurisdiction, city p roper and county were respectively used as the basic units of analysis, for each of which the GDP and per cap ita GDP as collected or calculated. The degrees of inequality and polarization
7 28 28 of regional economy for the years of 1990, 1995, 2000 and 2005 were evaluated w ith Gini Coefficient, Wolfson Index, and TW Index. Spatial autocorrelation analyses were emp loyed to identify the hot p laces of econom ic development, and exp lore the patterns of polarization of regional economy, of which city p roper and county were basic units. The research reveals that the polarization of regional econom y p rogresses in each of the three units mentioned above in Northeast China since 1990, and the city district economy is the most polarized among them. A spatial trend has been exhibited for econom ic center of gravity to move southward. The areas w ith high value in spatial autocorrelation analysis have been turning from scatters to axial and p lanar distributions. Dalian, Sheny2 ang, Changchun and Harbin, are high polarizing points, and discontinuous polarizing axes are along Har2 bin2dalian and M anzhouli2harbin2suifenhe railroad. The area w ith H igh value covers all the M iddle2and2south L iaoning, meanwhile, low value areas extend in North Heilongjiang, East and W est J ilin, and W est L iaoning, and becom e more continuous. The polarization results in that in Northeast China, regional econom ic system tends to becom e less hierarchical, and the econom ic grow th among p refectural cities, w ith the Four Cities excluded, tends to become equality. The polarization also brings varying degrees of developments to M iddle2and2south L ia2 oning Econom ic Region, Harbin2Changchun Region (Harbin, Daqing, Q iqihar, Songyuan, Changchun, and J i2 lin C ity), M anzhouli2harbin2 Suifenhe Econom ic Axial Belt, the major structures of regional economy in North2 east China. Key words: regional economy; spatial polarization; polarization index; spatial autocorrelation analysis; North2 east China