A Narrower Perspective? From a Global to a Developed-Countries Gender Gap Index: a Gender Statistics Excercise

Authors

  • Silvia Caligaris Università degli Studi di Milano-Bicocca
  • Fulvia Mecatti Università degli Studi di Milano-Bicocca
  • Franca Crippa Università degli Studi di Milano-Bicocca

DOI:

https://doi.org/10.6092/issn.1973-2201/4138

Abstract

In this paper, we focus our attention on a particular composite index of gender equality, the Global Gender Gap Index (GGGI), highlighting problematics and weaknesses and proposing a different approach structured in four steps. The starting point of our analysis is to narrow the research to a small group of OECD countries: in this way it is possible to lower the gender analysis in a homogeneous socio-cultural framework and introduce a fifth dimension related to the time use. Next, to explore which variables have a greater impact on the gender gap persistence among these countries, we propose a different weighting method, based on the structural equation modeling (SEM). Through the study of official data, the effects of these steps on the final ranking of countries were then analyzed, allowing reflections from both the methodological and socio-cultural point of view.

References

K.BARNES, N. BOUCHAMA (2011). Shifting wealth, shifting gender relations? Gender inequality and social cohesion in a converging world. http://www.oecd.org/dev/perspectivesonglobaldevelopment/48619715.pdf

K.A. BOLLEN, (1989). Structural Equations with Latent Variables. Wiley, New York.

S. CALIGARIS, F. MECATTI (2011). Quel certo genere di statistica. Sis-Magazine. www.sis-statistica.it/magazine/

P.M. BENTLER, D.G. BONETT, (1980). Significance tests and goodness-of-fit in the analysis of covariance structures. Psychological Bulletin, no. 88, pp. 588-600.

B. CHIANDOTTO, (1992). Errori nelle variabili e variabili latenti in modelli strutturali stocastici. Statistica, no. 52 (3).

D. A. KENNY, (2003). Effects of the number of variables on measures of fit in structural equation modelling. Structural Equation Modeling, n. 10, pp. 333-3511.

F. MECATTI , F. CRIPPA, P. FARINA, (2012). A Special Gen(d)re of Statistics: Roots, Development and Methodological Prospects of a Gender Statistics. International Statistical Review, no. 80, pp. 452-467.

Y. ROSSEEL, (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, no. 48(2), pp. 1-36.

H.-R. TYSON, L.D. ZAHIDI, (2011). The Global Gender Gap Report 2011. World Economic Forum, www.weforum.org

OECD,(2008). Handbook on Constructing Composite Indicators: methodology and user guide. www.oecd.org/publishing/corrigenda; http://lavaan.ugent.be/; www.oecd.org/social/family/database; http://apps.who.int/gho/data/

Downloads

Published

2013-03-30

How to Cite

Caligaris, S., Mecatti, F., & Crippa, F. (2013). A Narrower Perspective? From a Global to a Developed-Countries Gender Gap Index: a Gender Statistics Excercise. Statistica, 73(2), 267–287. https://doi.org/10.6092/issn.1973-2201/4138

Issue

Section

Articles