Gender inequality - both in space and time - is a latent trait, namely only indirectly measurable through a collection of observable variables and indicators purposively selected. Even if composite indicators are normally used by social scientists, when measuring gender-gap they are known to have case-specific technical limitations. In this paper we propose an innovative approach based on a multivariate Latent Markov model (LMM) for the analysis of gender inequalities as measured by the aforementioned indicators
Bertarelli, G., Crippa, F., Mecatti, F. (2017). A latent markov model approach for measuring national gender inequality. In A. Petrucci, R. Verde (a cura di), SIS 2017. Statistics and Data Science: new challenges, new generations Proceedings of the Conference of the Italian Statistical Society, Florence 28-30 June 2017 (pp. 157-160). Firenze : Firenze University Press [10.36253/978-88-6453-521-0].
A latent markov model approach for measuring national gender inequality
Crippa, FSecondo
;Mecatti, FUltimo
2017
Abstract
Gender inequality - both in space and time - is a latent trait, namely only indirectly measurable through a collection of observable variables and indicators purposively selected. Even if composite indicators are normally used by social scientists, when measuring gender-gap they are known to have case-specific technical limitations. In this paper we propose an innovative approach based on a multivariate Latent Markov model (LMM) for the analysis of gender inequalities as measured by the aforementioned indicators
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