Abstract: Analyzing regional inequality is of great significance to both academic enquiry and government policy. The recent literature on economic geography implies that scale has been playing a significant role in the economic geographical processes. Although regional inequality in China has also attracted tremendous scholarly interests since China started to implement policies of economic reforms in the late 1970s, the current work ignores the scalar effects in studying the regional inequality. With the increasing availability of data, this paper employs Coefficient Variance, Theil Index, spatial autocorrelation and scale variance based on the per capita GDP to examine the changing trends and spatial patterns of regional inequalities in China at four different spatial scales, i.e. region, province, prefecture and county. First, we use CV, Theil Index and Moran's I to explore the changing trends of regional inequalities in China and find that they all experienced increasing regional inequalities and significant spatial autocorrelation in regional development at all the four scales. Both of the prefecture and county levels have experienced a process of intensifying spatial autocorrelation. Second, with the scale variance and its component statistic techniques, we discover that there is an increasing sequence according to the scale variances and their components, i.e. county, prefecture, province and region, which indicates that the scalar variance is lower at the smaller scale and the regional inequality at smaller scale contributes more to the whole regional inequality. Third, by using spatial analysis techniques, we find that local spatial autocorrelation patterns have been stable since 1998. The HH type units tend to concentrate in the east coastal area of China. And the significant spatial autocorrelation is largely due to the concentration of LL clusters in central and western China. This paper also concludes that the regional inequality in China merits more investigation at the county level as the county unit is the most stable one in the history of China's regional administrative system.

Key words: regional inequality, different scales, spatial analysis, China