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在存在多个分类信息的情况下测量社会经济健康不平等。

Measuring socioeconomic health inequalities in presence of multiple categorical information.

作者信息

Makdissi Paul, Yazbeck Myra

机构信息

Department of Economics, University of Ottawa, 120 University (9008), Ottawa, Ontario, Canada, K1N 6N5.

School of Economics, 612- Colin Clark (39) Building, University of Queensland, Brisbane, QLD 4072, Australia.

出版信息

J Health Econ. 2014 Mar;34:84-95. doi: 10.1016/j.jhealeco.2013.11.008. Epub 2013 Dec 8.

Abstract

While many of the measurement approaches in health inequality measurement assume the existence of a ratio-scale variable, most of the health information available in population surveys is given in the form of categorical variables. Therefore, the well-known inequality indices may not always be readily applicable to measure health inequality as it may result in the arbitrariness of the health concentration index's value. In this paper, we address this problem by changing the dimension in which the categorical information is used. We therefore exploit the multi-dimensionality of this information, define a new ratio-scale health status variable and develop positional stochastic dominance conditions that can be implemented in a context of categorical variables. We also propose a parametric class of population health and socioeconomic health inequality indices. Finally we provide a twofold empirical illustration using the Joint Canada/United States Surveys of Health 2004 and the National Health Interview Survey 2010.

摘要

虽然健康不平等测量中的许多测量方法都假定存在一个比率尺度变量,但人口调查中可用的大多数健康信息都是以分类变量的形式给出的。因此,著名的不平等指数可能并不总是易于应用于测量健康不平等,因为这可能导致健康集中指数值的随意性。在本文中,我们通过改变使用分类信息的维度来解决这个问题。因此,我们利用这些信息的多维度性,定义一个新的比率尺度健康状况变量,并制定可以在分类变量的背景下实施的位置随机优势条件。我们还提出了一类参数化的人口健康和社会经济健康不平等指数。最后,我们使用2004年加拿大/美国健康联合调查和2010年国家健康访谈调查提供了一个双重实证说明。

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