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 Statistics and Data Science: new challenges, new generations Proceedings of the Conference of the Italian Statistical Society (pp.157-160). Firenze : Firenze University Press.
Citazione: | Bertarelli, G., Crippa, F., & Mecatti, F. (2017). A latent markov model approach for measuring national gender inequality. In Statistics and Data Science: new challenges, new generations Proceedings of the Conference of the Italian Statistical Society (pp.157-160). Firenze : Firenze University Press. |
Tipo: | slide + paper |
Carattere della pubblicazione: | Scientifica |
Presenza di un coautore afferente ad Istituzioni straniere: | No |
Titolo: | A latent markov model approach for measuring national gender inequality |
Autori: | Bertarelli, G; Crippa, F; Mecatti, F |
Autori: | CRIPPA, FRANCA (Secondo) MECATTI, FULVIA (Ultimo) |
Data di pubblicazione: | 2017 |
Lingua: | English |
Nome del convegno: | SIS 2017 Statistics and Data Science: new challenges, new generations June 28-30 |
ISBN: | 978-88-6453-521-0 |
Appare nelle tipologie: | 02 - Intervento a convegno |