Income Disparities within Provinces and their Changes

Due to the large land and population size in the provinces, natural endowments, economic and social conditions, and the culture of various regions within a province also differ greatly. The income disparity within provinces could be a serious problem. In this section we use the data of prefectures and counties to analyze the income disparity within provinces.

E. Degree of Income Disparities within Provinces

In order to analyze income disparities within provinces, we examine indicators of per capita GDP at the prefecture level. Based on the PRC’s administration framework, a province is generally composed of around 12 regional districts. The data listed in Table 6 represent the ratio of maximum to minimum per capita GDP at the prefecture level within each province during the period 1997–2005.

The ratio of maximum to minimum per capita GDP at prefecture level demonstrates obvious gaps within each province. In 2005, the ratios ranged from 2.6 to 10.4, and the average was 5.6. Gansu province had the biggest gap. In 2005, per capita GDP of Jinchang prefecture was 24,950 yuan, while that of Dingxi prefecture was 2,394 yuan (the lowest in the PRC), the former being 10.4 times the latter. In Guangdong province, per capita GDP of Shenzhen prefecture was 60,801 yuan, which is 8.1 times of that of Heyuan prefecture.

Figure 18 [ PDF 136.1KB | 1 page ] illustrates the results of decomposition of income disparity among 28 provinces (excluding Beijing, Tianjin, and Shanghai) with that within the provinces. In terms of the spatial decomposition of the Theil index of regional disparity, the level of disparity within the provinces is even higher than the level of disparity among the provinces. As Figure 18 shows, compared with the consideration given only to inter-province disparity, interprefecture disparity increased significantly. In 2005 for example, the value of the Theil index among the provinces is 0.098, but when the disparity between prefectures within provinces is taken into consideration, the overall value of the Theil index increased to 0.241. The latter value is 2.5 times the former. Looking at the share of disparity within and among the provinces in overall disparity, the share of disparity within the provinces is higher than the share among the provinces. From 1997 to 2005, disparity within the provinces had a share around 57.2% to 61.6% of the total value of disparity. It has surpassed the disparity among the provinces. The decomposition of the Theil index shows that intra-province disparities are even more significant than inter-province disparities.

Generally speaking, intra-province disparities are larger than inter-province gaps in many places, which can be reflected from the ratio of maximum to minimum per capita GDP (MMR) within and across provinces. Table 6 [ PDF 117.4KB | 1 page ] shows that in 2005, 20 provinces among the 28 had MMRs larger than the national inter-province MMR (that is, 5.5).

Considering the changes of disparity within provinces over time, from 1997 to 2005, the regional disparities within most of the provinces widened. The MMR of 18 provinces (see last column of Table 6) increased during that period; it remained stable in one province, and declined in 9 provinces. Appendix C provides Theil indexes based on prefecture-level data in each province. Similarly to the MMR, the Theil indexes of 19 provinces increased in 2005 compared with 1997, and decreased in 9 provinces. These facts demonstrate that intraprovince disparity in income of most provinces has widened in recent years. Compared with the inter-province Theil indexes, we could conclude that in most of the provinces, internal disparities in income among prefectures within provinces are more significant than interprovince income disparities.

If we consider the indexes at the county level, intra-province disparities should become more obvious. Table 7 [ PDF 136KB | 1 page ] gives the ratio of maximum to minimum per capita GDP at the county level cross all the provinces (excluding Beijing, Tianjin, and Shanghai). The ratio in Hainan province was the lowest (2.2), and the ratio in Jiangsu province was the highest (25.8). In 2005, per capita GDP in Kunshan county, Jiangsu province was 113,025 yuan, which is 25.8 times that in Guanyun county (4,379 yuan) in the same province. Further, if we consider the data of urban areas in big cities, intra-province disparity could be larger. For example, the MMR of Guangdong province is 9.5, which will increase to 16.4 if we include the data of Shenzhen.

F. Relationship between Intra-province Disparities in Income and Economic Development Level

The relationship between intra-province gaps and economic development is an interesting and important issue. According to the inverted U-shaped hypothesis (Williamson, 1965), residents of developed areas pay more attention to regional gaps than do residents of less developed areas because the local governments in developed areas have more financing power to balance the development across areas. Therefore, developed areas are less likely to suffer from large regional disparities.

Figure 19 [ PDF 97.1KB | 1 page ] illustrates the relationship between economic development level (value of per capita GDP) and intra-province disparities in 2005 (by Theil indexes at the prefecture level within provinces, excluding Beijing, Tianjin, and Shanghai). Overall, there is no significant relationship between these two. In some less developed provinces, intra-province disparities are insignificant, like in Guangxi and Guizhou. In other less developed provinces, these disparities are salient, like in Gansu. Similarly, some of the developed provinces, like Zhejiang, have smaller intra-province gaps, whereas in Guangdong and Jiangsu, these disparities are much larger.

Figure 20 [ PDF 97.1KB | 1 page ] demonstrates the relationship between provincial economic development level and intra-provincial disparities at the county level. Because counties are at a lower administrative level than prefectures, differentiating the data of the counties from one another could indicate intra-province disparity more accurately. Similarly to the results of the prefecture level data, we found no significant relationship between regional disparities and economic development level.

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