Extension of Generalized Lorenz Dominance Criterion to Multivariate Attributes
Extension of Generalized Lorenz Dominance Criterion to Multivariate Attributes
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发表时间：
2012
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通讯作者：
Kazuyuki Nakamura
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作者：
Kazuyuki Nakamura
本文将广义Lorenz优势准则推广到多元属性情形。基于Kolm（1977）的一致优化，我们提出了一种广义优化的扩展形式，我们称之为一致超优化，它允许属性具有不同的均值。证明了均匀超优化与均匀优化对福利序有相似的意义。此外，我们表明，该标准可以用于比较分布的不平等的人口。我们还提供了一个程序的实证调查，这是在标准形式的线性规划问题。关键词：广义Lorenz优势，多维不等式，一致优控制. JEL代码：D31，D63
This paper considers an extension of generalized Lorenz dominance (GL) criterion to the case of multivariate attributes. Based on the uniform majorization of Kolm (1977), we propose an extended version of GL which we call uniform supermajorization which allows for attributes with different means. It is verified that uniform supermajorization has similar implications as uniform majorization for welfare ordering. Furthermore, we show that this criterion can be used for comparison of distributions of unequal populations. We also provide a procedure for empirical investigations which is in the standard form of linear programming problems. key words: Generalized Lorenz dominance, Multidimensional inequality, Uniform majorization. JEL code: D31, D63