中文摘要：

在分析了变异系数、基尼系数、综合熵指数、塞尔指数和艾克森指数等不同区域差异测度方法在构造上的差异之后,通过计算不同测度方法所描述的1980～2002年间我国农村人均纯收入差距的变动轨迹,发现它们对较长时段不平衡性变动的描述是比较一致的,但对较短时段存在差别;对不同测度指数的进一步分解,从理论和实际应用两方面探讨了不同测度方法的适用范围及其在区域差异分析中的优势和局限.

英文摘要：

Regional inequality is one of the major jor concern to the Chinese government. On the subjects of research on China, and is a mabasis of analyzing the structure differences of some major indexes for measuring regional inequality, the rural regional inequality changes in China at provincial level from 1980 to 2002 is described by different methods respectively. It is found that the changes of different indexes show the same trend in a longer period of time, but some in a shorter period. All the methods showed that China＇s rural regional inequality has an overall increasing trend with a short period of decreasing in the whole process of reform. However, the decomposition of the Theil＇s regional inequality reveals that since 1987, the interregional inequalities among the eastern, central and western regions have been more serious than the provincial inequality within regions. The further factor decomposition of the Gini index shows that farmers＇ wage component contributes more than 66% to the total inequality index and is the most important factor resulting in rural total regional inequality. It is proposed that any conclusions from a short period of data analysis are inadeguate. When analyzing driving forces of regional inequality, long-term data should be used. The further decomposing analysis of different indexes shows that each method has its own advantages and disadvantages. The Gini index is suitable for factor analysis but cannot be decomposed by regions. The greatest advantage of the Theil＇s index is that it can be decomposed by different levels of regions and is very useful for different spatial scale analyses of regional inequality. Standard Deviation is more suitable for simple analysis of regional inequality in China. Compared with the above three indexes, the Atkinson index is rarely used. But when regional inequality is very small, it is the only one that can be used for analysis.