One Bad Formula Can Spoil Everything: A Simple Adjustment That Would Improve the UN’s Gender Inequality Index

  • Max McDonald
  • Neal KoblitzEmail author

There can be dangers as well as benefits in using mathematical methods to answer questions that have a large human component. In the middle of the last century, Darrell Huff [5] wrote of the myriad ways that statistics are used in marketing and politics to mislead the public. In our time, Felix Salmon [14] has described how David Li’s mathematical model for collateralized debt obligations was seized upon by Wall Street as a justification for irresponsible investment practices that precipitated the financial crisis of 2008; John Ewing [3] has decried the misuse of mathematics to evaluate teachers in his exposé of value-added models; and Cathy O’Neil [12] has explained many of the ways that data science has been used to undermine democratic values—for example, by reinstituting a type of racial discrimination in lending (called “redlining”) that had supposedly been outlawed in the United States fifty years ago.

Even those who use mathematical methods with the best of intentions to help...



We wish to thank John Sylvester for explaining Tikhonov regularization, Edith Seier and Jorge Estrada Jr. for helpful comments, Ann Hibner Koblitz for editorial assistance, and an anonymous reviewer for useful suggestions.


  1. [1]
    L. Beneria and I. Permanyer, The measurement of socio-economic gender inequality revisited, Development and Change 41 (2010), 375–399.Google Scholar
  2. [2]
    Choe Sang-Hun, South Korea confronts open secret of abortion, International Herald Tribune, 6 January 2010.Google Scholar
  3. [3]
    J. Ewing, Mathematical intimidation: Driven by the data, Notices of the Amer. Math. Soc. 58 (2011), 667–673.MathSciNetGoogle Scholar
  4. [4]
    A. Gaye, J. Klugman, M. Kovacevic, S. Twigg, and E. Zambrano, Measuring key disparities in human development: The Gender Inequality Index, Human Development Research Paper 2010/46, 2010.Google Scholar
  5. [5]
    D. Huff, How to Lie with Statistics, W. W. Norton, 1954.Google Scholar
  6. [6]
    N. Ilsley, Gulf states fail to protect domestic workers from serious abuse, Newsweek, 16 October 2015.Google Scholar
  7. [7]
    J. Kaipio and E. Somersalo, Classical regularization methods, Statistical and Computational Inverse Problems (2005), 7–48.Google Scholar
  8. [8]
    A. Kapiszewski, Nationals and expatriates: Populations and labour dilemmas of the Gulf Cooperation Council states, Berkshire, England: Garnet, 2001.Google Scholar
  9. [9]
    N. Kassebaum, R. Barber, Z. Bhutta, L. Dandona, P. Gething, S. Hay, Y. Kinfu, H. Larson, X. Liang, S. Lim, and A. López, Global, regional, and national levels of maternal mortality, 1990–2015: A systematic analysis for the Global Burden of Disease Study 2015, Lancet 388 (2016), 1775–1812.Google Scholar
  10. [10]
    S. Klasen and D. Schüler, Reforming the Gender-Related Index and the Gender Empowerment Measure: Implementing some specific proposals, Feminist Economics 17 (2011), 1–30.Google Scholar
  11. [11]
    A. H. Koblitz, Life in the fast lane: Arab women in science and technology, Bulletin of Science, Technology & Society 36 (2016), 107–117.Google Scholar
  12. [12]
    C. O’Neil, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, Crown, 2016.Google Scholar
  13. [13]
    I. Permanyer, A critical assessment of UNDP’s Gender Inequality Index, Feminist Economics 19 (2013), 1–32.Google Scholar
  14. [14]
    F. Salmon, Recipe for disaster: The formula that killed Wall Street, Wired 17 (3) (2009).Google Scholar
  15. [15]
    United Nations Development Program (UNDP), Human Development Report, New York: Oxford University Press, 2010.Google Scholar
  16. [16]
    UNDP, Table 5: Gender Inequality Index, Human Development Report (2016), (accessed November 2017).
  17. [17]
    UNDP, Box 1.8: Five misconceptions about women’s economic empowerment, Human Development Report (2016), (accessed November 2017).
  18. [18]
    United Nations Children’s Fund (UNICEF), UNICEF Data: Monitoring the Situation of Children and Women (2015), (accessed December 2017).
  19. [19]
    World Economic Forum (WEF), The Global Gender Gap Report 2017, (accessed December 2017).
  20. [20]
    World Health Organization (WHO), Adolescent Pregnancy (2014), (accessed December 2017).

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Center for Studies in Demography & Ecology, Evans School of Public Policy & GovernanceUniversity of WashingtonSeattleUSA
  2. 2.Department of MathematicsUniversity of WashingtonSeattleUSA

Personalised recommendations