Polarization measurement for ordinal data

被引:22
|
作者
Kobus, Martyna [1 ]
机构
[1] Polish Acad Sci, Inst Econ, PL-00330 Warsaw, Poland
关键词
Polarization; Inequality measurement; Ordinal data; Atkinson's Theorem; Dominance; INEQUALITY DECOMPOSITION; POPULATION SUBGROUPS; HEALTH; HAPPINESS;
D O I
10.1007/s10888-014-9282-y
中图分类号
F [经济];
学科分类号
02 ;
摘要
Atkinson's Theorem (Atkinson J. Econ. Theory 2, 244-263, 1970) is a classic result in inequality measurement. It establishes Lorenz dominance as a useful criterion for comparative judgements of inequality between distributions. If distribution A Lorenz dominates distribution B, then all indices in a broad class of measures must confirm A as less unequal than B. Recent research, however, shows that standard inequality theory cannot be applied to ordinal data (Zheng Res. Econ. Inequal. 16, 177-188, 2008), such as self-reported health status or educational attainment. A new theory in development (Abul Naga and Yalcin J. Health Econ. 27(6), 1614-1625, 2008) measures disparity of ordinal data as polarization. Typically a criterion used to compare distributions is the polarization relation as proposed by Allison and Foster (J. Health Econ. 23(3), 505-524, 2004). We characterize classes of polarization measures equivalent to the AF relation analogously to Atkinson's original approach.
引用
收藏
页码:275 / 297
页数:23
相关论文
共 50 条
  • [1] Polarization measurement for ordinal data
    Martyna Kobus
    The Journal of Economic Inequality, 2015, 13 : 275 - 297
  • [2] Multidimensional polarization for ordinal data
    Kobus, Martyna
    Kurek, Radoslaw
    JOURNAL OF ECONOMIC INEQUALITY, 2019, 17 (03) : 301 - 317
  • [3] Multidimensional polarization for ordinal data
    Martyna Kobus
    Radosław Kurek
    The Journal of Economic Inequality, 2019, 17 : 301 - 317
  • [4] Inequality with Ordinal Data
    Cowell, Frank A.
    Flachaire, Emmanuel
    ECONOMICA, 2017, 84 (334) : 290 - 321
  • [5] Efficiency measurement in data envelopment analysis in the presence of ordinal and interval data
    Bohlool Ebrahimi
    Madjid Tavana
    Morteza Rahmani
    Francisco J. Santos-Arteaga
    Neural Computing and Applications, 2018, 30 : 1971 - 1982
  • [6] Efficiency measurement in data envelopment analysis in the presence of ordinal and interval data
    Ebrahimi, Bohlool
    Tavana, Madjid
    Rahmani, Morteza
    Santos-Arteaga, Francisco J.
    NEURAL COMPUTING & APPLICATIONS, 2018, 30 (06) : 1971 - 1982
  • [7] Comparing distributions of ordinal data
    Jenkins, Stephen P.
    STATA JOURNAL, 2020, 20 (03) : 505 - 531
  • [8] Inferring inequality: Testing for median-preserving spreads in ordinal data
    Abul Naga, Ramses H.
    Stapenhurst, Christopher
    Yalonetzky, Gaston
    ECONOMETRIC REVIEWS, 2024, 43 (2-4) : 156 - 174
  • [9] Conducting Measurement Invariance Tests with Ordinal Data: A Guide for Social Work Researchers
    Bowen, Natasha K.
    Masa, Rainier D.
    JOURNAL OF THE SOCIETY FOR SOCIAL WORK AND RESEARCH, 2015, 6 (02) : 229 - 249
  • [10] Inequality decomposition by population subgroups for ordinal data
    Kobus, Martyna
    Milos, Piotr
    JOURNAL OF HEALTH ECONOMICS, 2012, 31 (01) : 15 - 21