The widening development discrepancy between (urbanized) coastal and (rural) interior regions is now seen as one of the most serious challenges for the Chinese government (Xu, F. et al. 1997). Not surprisingly, a lot has been published about the various aspects of that problem (see: Bibliography). Scientists from many disciplines have contributed to this field of research, including geographers, demographers, regional planners, political scientists, and, most prominently, economists - from agricultural economists to financial specialists in foreign direct investment. In a first overview of the literature, we have identified five core themes that dominate the discussion:
1. There are numerous economic studies on regional disparities, which emphasize the role of differences in economic conditions (Aziz, J. et al. 2001; Chan, R. et al. 1996;
Chen, J. et al. 1996; Fleisher, B. et al. 1997; Jian, T. et al. 1996; Lu, F. 2001; Lu, W.
2001 and 2002; Lyons, T. 1991; Mody, A. et al. 1997; Taube, M. et al. 2002; Tian, X. 1999; Tuan, C. et al. 2002; Zhao, X.1996). Most researchers have used des-criptive statistics at the level of provinces or economic regions to analyze the diverging regional trends in key economic indicators, such as regional GDP,
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industrial output or income level (Knight, J. et al. 1999). There are also analyses of regional differences in public investment programs (Cheung, P. et al. 1998; Nyberg, A. et al. 1999; Fan, S. et al. 2002), which might have contributed to the regional dis-crepancies in economic growth. An important subject of economic research is, of course, the question of poverty reduction in China’s rural areas (Lu, F. 2001; Fan, S.
et al. 2002). Some economists have tried to develop multi-regional models of the Chinese economy or its sub-sectors, such as general-equilibrium models of the Chinese agricultural sector. In these models, regional development disparities are a function of differences in productivity between economic sectors.
2. Some studies have pointed out and analyzed geographical and geophysical factors (such as distance to seaports, difficult terrain, altitude, climate, etc.) that may be responsible for China’s regional development disparities (for instance: Bao, S. et al.
2001; Démurger, S. et al. 2002; Gallup, J. et al. 1999; and Goodman, D. 1989).
Many of China’s rural areas are land-locked, such as the large agricultural basin of Sichuan or the agricultural areas at the upper and middle reaches of the Yellow River. They are far away from potential markets at the population centers on the Chinese East coast. Many rural areas in China are located in arid or semi-arid climate or at very high altitude (such as Tibet). Some authors believe that these natural factors can explain most of the regional development disparities in China.
3. Another field of research deals with demographic and social driving factors of regional disparities in China, such as analyses of the rural population structure (Jing, Y. 1998), or studies of rural unemployment (Yao, Y. 2001; Zhao, Y. 2001). The basic idea is that human resources in lagging rural regions are usually not well developed and thus perpetuate underdevelopment. Not much is available (in English-language literature) on the human resource dimension of regional dis-parities, such as the level of education and training in rural areas (Han, D. 2000). On the other hand, the labor migration to urban areas, the so-called “floating popu-lation”, has received considerable attention (Cai, F. 1999; Fan, C. 1999; Fernandez-Stembridge, L. 1999; Ma, Z. 1999; Roberts, K. et al. 1999; Zhao, Y. 1999 and 2001). Rural-urban migrants are often young and highly motivated to improve their living conditions. Often, only old men and women with children remain in the villages. The increasing loss of economically most active population segments is certainly a handicap for many rural areas. However, rural-urban migration might also have a positive side: Rozelle, for instance, investigated, how the remittances from rural-urban labor migrants can promote rural development (Rozelle, S. et al.
1999). Returning migrants might also bring know-how and new perspectives from the cities back to their village. A special research topic in that context is the unique Chinese household registration, the so-called hukou system, which tends to prevent or discourage rural-urban migration (Chan, K. et al. 1999; Wong, L. et al. 1998).
4. Many authors have mentioned the potential threat of increasing regional disparities to China’s political stability, but few (English-language) studies have systematically investigated consequences for the political system and the stability of the nation.
Typically, the discussion of China’s political dilemmas is at the national and inter-national level - with only limited consideration of the country’s internal political di-versity (see: Fleisher, B. et al. 1997; Lam, W. 1995; Lieberthal, K. 1995; Lu, F.
1999; Nathan, A. et al. 2002, Ogden, S. 2002). We also found only few papers dealing with institutional reform and its impact on regional disparities (Oi, J. 1999).
Table 1: Slected indicators and statistical measures of regional (inter-provincial) diversity in China, 2001
Beijing 0.065 53.1 1.4 0.3 15.1 12.9 25,523 11.2 9.6 130.0 14.1 40.3 n.d. 26.1 5.1
Tianjin 0.028 33.7 2.3 1.0 19.2 13.0 20,154 20.0 2.6 100.3 13.5 27.7 14.1 37.6 11.4
Hebei 0.003 19.1 0.7 0.2 25.1 14.4 8,362 49.6 4.4 61.0 15.6 19.1 66.9 34.6 0.9
Shanxi 0.003 17.9 12.9 0.5 35.3 11.0 5,460 46.9 4.9 79.4 31.3 15.3 13.1 167.0 0.7
Inner Mongolia 0.007 14.3 4.4 1.0 25.2 8.2 6,463 53.9 -0.1 41.9 18.2 8.4 7.2 104.1 7.6
Liaoning 0.068 16.1 4.6 1.6 27.3 10.0 12,041 37.2 7.8 59.3 15.2 11.3 138.3 46.1 10.1
Jilin 0.154 10.5 3.1 0.7 36.5 6.1 7,640 50.7 1.8 60.7 14.5 7.8 3.5 36.7 10.8
Heilongjiang 0.108 10.3 4.3 1.0 18.0 4.8 9,349 49.6 2.1 34.2 12.8 32.2 227.3 20.5 7.8
Shanghai 0.212 58.2 3.4 15.9 n.d. 17.2 37,382 12.5 9.4 256.5 12.0 71.0 15.0 34.9 8.9
Jiangsu 0.018 27.9 2.8 2.1 9.5 16.6 12,922 41.4 24.6 73.4 11.3 38.9 39.1 6.4 5.2
Zhejiang 0.078 42.9 2.4 6.3 1.5 17.3 14,655 35.7 30.1 149.7 12.6 26.7 8,071.8 5.4 1.3
Anhui 0.016 6.5 2.0 1.3 26.1 16.8 5,221 58.7 13.1 47.2 10.9 24.9 263.7 14.5 4.1
Fujian 0.636 36.3 1.5 2.6 1.9 20.6 12,362 45.8 55.0 105.2 10.3 13.2 62.1 3.2 2.5
Jiangxi 0.042 7.5 12.3 4.2 9.2 18.2 5,221 51.6 12.1 43.8 10.2 15.6 126.8 21.4 2.9
Shandong 0.010 13.8 0.1 4.1 17.3 13.9 10,465 52.3 18.1 72.0 11.7 13.2 134.0 33.2 4.9
Henan 0.012 9.2 2.1 0.9 19.0 15.1 5,924 63.1 7.5 44.6 14.3 12.3 8.2 24.4 2.8
Hubei 0.034 10.7 2.8 4.8 34.4 18.0 7,813 48.4 5.0 34.2 11.3 20.3 53.7 12.0 3.1
Hunan 0.073 7.9 3.2 9.8 15.9 17.6 6,054 60.5 24.7 37.2 11.0 17.5 380.8 44.0 3.8
Guangdong 0.138 59.5 3.3 6.5 0.7 22.5 13,730 40.0 566.9 81.6 13.7 10.8 67.2 3.6 3.8
Guangxi 0.097 13.2 7.6 11.8 0.9 20.3 4,668 61.8 35.2 36.6 14.9 64.0 723.1 15.5 6.5
Hainan 0.204 39.0 15.8 5.5 1.4 24.9 7,135 60.3 16.3 30.9 7.9 26.9 15.2 1.2 5.1
Chongqing 0.082 15.4 9.1 n.d. n.d. 18.8 5,654 54.7 2.1 46.6 12.6 8.6 61.6 87.2 9.7
Sichuan 0.037 8.0 13.4 3.6 16.3 17.3 5,250 58.8 16.3 47.5 13.3 8.1 196.9 43.8 13.0
Guizhou 0.028 16.9 26.8 2.4 6.8 14.5 2,895 66.4 11.0 11.5 30.9 1.8 151.8 746.4 2.6
Yunnan 0.016 30.1 26.9 3.6 4.4 16.0 4,866 73.6 33.7 46.8 15.5 25.5 192.2 30.4 7.1
Tibet 0.001 50.8 14.7 2.8 2.8 8.8 5,307 71.8 0.9 30.7 n.d. n.d. n.d. n.d. 33.4
Shaanxi 0.014 18.0 4.9 0.5 18.2 15.0 5,024 55.7 1.7 37.3 17.4 4.9 108.0 41.5 2.9
Gansu 0.004 14.6 6.5 1.4 17.0 11.0 4,163 59.4 6.3 31.6 28.5 9.6 1,117.2 51.2 17.7
Qinghai 0.006 23.8 27.7 3.1 14.5 6.0 5,735 60.0 2.0 31.6 37.2 8.5 n.d. 38.0 28.6
Ningxia 0.007 28.5 22.8 0.2 12.6 10.1 5,340 56.5 0.2 242.7 50.9 22.9 0.4 106.3 4.4
Xinjiang 0.008 49.9 20.1 0.7 8.2 7.7 7,913 56.6 3.9 57.0 13.3 20.4 13.2 74.7 12.8
Minimum Value 0.001 6.5 0.1 0.2 0.7 4.8 2,895 11.2 -0.1 11.5 7.9 1.8 0.4 1.2 0.7
Maximum Value 0.636 59.5 27.7 15.9 36.5 24.9 37,382 73.6 566.9 256.5 50.9 71.0 8,071.8 746.4 33.4
Range 0.635 53.1 27.6 15.7 35.8 20.0 34,487 62.4 567.0 244.9 43.0 69.2 8,071.4 745.2 32.7
Average 0.071 24.6 8.6 3.3 15.2 14.3 9,377 50.5 30.0 69.8 16.9 20.9 438.3 63.7 7.8
Skewness 3.8 0.9 1.2 2.0 0.4 -0.1 2.6 -1.2 5.4 2.3 2.3 1.8 5.1 4.9 2.2
Kurtosis 16.9 -0.5 0.2 4.2 -0.6 -0.5 7.6 1.6 29.9 5.2 5.3 3.5 26.4 25.3 5.3
Diversity Index 20.6 0.4 1.4 6.1 -0.2 -0.4 10.1 2.8 35.3 7.5 7.5 5.3 31.5 30.2 7.5
Diff Max/Min in % 55,108 821 27,610 8,302 4,881 413 1,191 556 809,943 2,124 547 3,775 2,017,850 60,008 4,539
Source: China Statistical Yearbook, 2002 (Beijing)
*1 Liaoning province includes city data for Shenyang and Dalian, Shandong includs city data for Jinan and Qingdao, and Guangxi includes city data for Nanning and Guilin.
Environment Human Dimension Natural Dimension Economic Dimension Infrastructure
A few studies of regional and rural development in China have also included practi-cal suggestions or even detailed concepts on how to achieve a better regional balance in China’s development process. A most prominent example is the Western Development Program of the Chinese government (British Consulate-General, 2001; Filson, G. 2001).