Results

Table 1 [ PDF 44.6KB | 1 pages ] shows the overall results of the Regional Development Index. It indicates that the three large cities, Shanghai, Beijing, and Tianjin, ranked at the top among the 31 provinces. This is partly due to the fact that they have only limited rural areas, whereas all other provinces have broad rural areas that are normally less developed. Amongst these three cities, Shanghai is more advanced than Beijing and Tianjin.

Fourth place belongs to Guangdong province, which experienced more rapid economic development than other provinces during the 1980s and 1990s, being a pioneer province in the early stage of economic reform. It also benefited from its geographic proximity to Hong Kong. Zhejiang and Jiangsu, two southeast coast provinces in the Yangzi River delta region, both with good economic performance, ranked at fifth and sixth places. Liaoning, Shandong, Fujian and Hebei (seventh to tenth place) are also coast provinces of the PRC.

At the low level of development are Tibet, Guizhou, Qinghai, Gansu and Ningxia (31st - 27th), etc. They are either southwestern or northwestern provinces. In the middle, there are a number of northeast, central and western provinces.

Figure A1 [ PDF 71.5KB | 1 pages ] (see Appendix) more clearly illustrates the relative position of provinces in overall development. In general, there is a clear link between the level of development and geographic location. Ten of the 11 east coast provinces (except Hainan) ranked in the top ten places. Ten of the 12 western province plus two central provinces ranked in the lowest twelve places.

The ten field indices and one reference index are illustrated in Figures A2 – A12 in the Appendix. For Economic Development (Field 1), the ranks are close to those of the overall index ( Figure A2 [ PDF 71.5KB | 1 pages ]). The two series of scores have a high correlation coefficient, equal to 0.917 (see Table 2 [ PDF 44.4KB | 1 pages ] for the correlation coefficient matrix), although all ten field indices are equally weighted for overall development. This indicates that economic development grasps a large part of the common features of other development indicators. Nevertheless, we can also see that economic development does not cover everything.

Again, in economic development, Shanghai, Beijing Tianjin, Zhejiang, Jiangsu and Guangdong held the top six places, although their ranks are slightly different from the overall index. It is somewhat surprising that Guangdong has been surpassed by both Zhejiang and Jiangsu, considering that previously it was the leading province in economic development outside of the three large cities. In terms of GDP per capita, urbanization and industrialization, Zhejiang and Jiangsu now have higher indicators than Guangdong. Their rural income per capita is also higher than the latter.

Five western provinces—Yunnan, Guizhou, Gansu, Ningxia and Sichuan—ranked low in economic development. Guizhou had the lowest levels of GDP per capita and income per capita, and Yunnan had the lowest level of development in terms of urbanization and industrialization. Tibet ranked much higher than them, in 18th place. This is mainly due to its relatively high urban income and urbanization rate, perhaps partially as a result of subsidies from the central government and financial aid from other provinces. Nevertheless, it is notable for its low rural income and level of industrialization.

For Productivity and R&D ( Figure A3 [ PDF 71.5KB | 1 pages ]), Tianjin, the third largest city in the eastern PRC, had the highest score, possibly thanks to the foreign-funded enterprises that have located there in recent years. Surprisingly, Yunnan, a less developed southwest province, is ranked second, holding a place among economically far more developed cities and provinces. This is largely due to its profitable tobacco industry. Xinjiang, an autonomous region in the far west, and Heilongjiang, a northeastern province, also ranked relatively high (sixth and eighth places, respectively). These two provinces have a very high proportion of crude oil production in their industrial value-added, and their capital productivity and capital contribution figures are much higher than many other provinces because of the high oil prices. This does not reflect their real productivity, however. Thus the figures for the two provinces have been replaced with the provincial averages.

For Human Development ( Figure A4 [ PDF 71.6KB | 1 pages ]), Fujian, another coastal province, ranked first, above Beijing and Shanghai. Its scores in all the three sub-indices are not the highest, but are all above average. By contrast, Beijing received the highest score for population mobility, but the lowest for human safety, due to its high rate of fires. Hubei and Sichuan, two less developed central and western provinces, ranked fourth and sixth places, above Guangdong and a number of other more developed provinces. This is mainly because of their low natural population growth rates and more balanced sex ratios, along with lower traffic and fire accident ratios.

For Education ( Figure A5 [ PDF 71.6KB | 1 pages ]), Liaoning, Jilin (both northeastern provinces), Shaanxi and Shanxi (central and western) have relatively high ranks (fourth to seventh), following Beijing, Tianjin and Shanghai. This was mainly driven by their relatively high literacy rates and years of schooling. Economically more developed Guangdong, Fujian and Shandong ranked relatively low, due to either lower years of schooling or lower rates of tertiary and vocational secondary school students in the population.

For Social Equity ( Figure A6 [ PDF 71.6KB | 1 pages ]), Beijing, Shanghai, Jilin, Chongqing and Hebei hold the top five ranks. Beijing’s score for income disparity is only average in level, but it has a low unemployment rate and relatively high sex equality ratio. Shanghai has low income disparities and a high sex equality ratio, but its unemployment rate is relatively high. Jilin, Chongqing and Hebei all benefited from their low income disparities and high sex equality, although their unemployment rates were below average.

Does social equity relate to the level of economic development? Figure 1 [ PDF 44.6KB | 1 pages ] indicates that there is a positive relationship between the two, although not necessarily, as Kuznets suggested, in an inverted U shape curve (between income and income inequality).

For Public Services ( Figure A7 [ PDF 71.6KB | 1 pages ]), Beijing, Xinjiang, Tianjin, Shanxi and Shaanxi ranked high. They all have relatively high school completion ratios for primary and junior secondary students. Their public expenditures on education and public health, as ratios to GDP, were also relatively high. Ningxia and Tibet also hold good positions (seventh and eighth). Tibet’s school completion ratio is still low, but it has a high proportion of government spending on education and public health. Guangxi, Sichuan, Chongqing (all in the southwest) and Anhui ranked low, because of their low government spending on public services.

For Social Security ( Figure A8 [ PDF 71.5KB | 1 pages ]), Shanghai, Tianjin, Jiangsu, Guangdong and Liaoning are the top five. Beijing, although being the capital city, ranked very low (30th), only above Tibet. Its coverage rates of basic pension insurance and unemployment insurance are very low, and its basic medical insurance is below average.

For Infrastructure ( Figure A9 [ PDF 71.6KB | 1 pages ]), not surprisingly, the three large cities of Shanghai, Beijing and Tianjin have the highest ranks. Following them are Guangdong, Liaoning, Jiangsu and Shandong, all east coast provinces. There is a high correlation between infrastructure and economic development (corr=0.912, see Table 2). Quizhou and Tibet have the lowest scores, due not only to their low achievements in economic development (thus lower demand for infrastructure and lower financial capability), but also their unfavorable geographic situations, which make highway and railway construction difficult. Heilongjiang ranked also low, partially because of its low rate for villages connected with highways.

Environment Protection ( Figure A10 [ PDF 71.6KB | 1 pages ]) has no significant correlation with economic development (corr=0.287). The top six are Fujian, Hainan, Jiangxi, Zhejiang, Guangdong and Tibet. Beijing and Shanghai ranked in the middle tier, at 12th and 20th. High-ranked provinces are of two different types: some more economically developed provinces with a high proportion of treatment of waste water and solid wastes, and some less developed provinces with a good environment and little pollution. However, low ranking provinces are mostly in the western region, and have low levels of economic development. The bottom six are Ningxia, Shanxi, Inner Mongolia, Xinjiang, Gansu and Guizhou. Their rankings are heavily affected by the low forest coverage rate. Inefficient consumption of energy and little treatment of wastewater and solid wastes also contributed to some of their low rankings.

For Institutional Development ( Figure A11 [ PDF 71.7KB | 1 pages ]), the top six provinces are Shanghai, Zhejiang, Guangdong, Fujian, Jiangsu and Beijing. They are economically developed. Quizhou, Shanxi and a few northwestern provinces with a low level of economic development ranked low. These provinces have low scores for both marketization and legal environment. Some also have low efficiency of government, high intervention by the government in enterprises, or a high financial burden on farmers and enterprises. This implies that there is a correlation between economic development and institutional development. However, further research is needed on the causalities between these two variables: is the low achievement in economic development the reason for the low achievement of institutional development, or is it rather the result of the latter?

For Natural Resources and Geographic Allocation ( Figure A12 [ PDF 71.4KB | 1 pages ]), the ranks are significantly different from most of the other field indices. The correlation coefficients of its scores with most of other field indices are insignificant and have negative signs (see Table 2). This indicates that natural endowment is not a major determinant for development, although it can be an important contributor. In addition, it does not indicate the level of development. This is why it is considered only as a reference index and excluded from the overall index in this study. Some central and west provinces, i.e., Inner Mongolia, Tibet, Shanxi, and Heilongjiang ranked at the top, but for different reasons. Inner Mongolia benefited from its high per capita area of cultivated land and energy resources. Tibet benefited from its large per capita water and forest resources, although it has a disadvantage in terms of distance to the coast. Shanxi is rich in coal reserves, and Heilongjiang’s cultivated land area per capita is high.

Some structural characters of the regions are also excluded from this index system, although they may be important for development. For instance, foreign trade has played an important role in the development of many provinces, and the ownership structure and industrial structure may be also important characteristics for certain provinces. However, these structural characters themselves do not indicate the level of development, and neither are they targets of development. In Tables A1-A3 in the Appendix, some structural indicators for all the provinces are listed as references.

Download this Discussion Paper [ PDF 222.9KB| 32 pages ].

Comment(s)

There are [0] comment(s) for this entry. Post a comment.