The aim of this study is to explore the adoption of a joint modelling framework for dealing with dyadic and monadic count outcomes with excess zeros simultaneously via a common latent structure. As a case study we consider the problem of identifying the different push and pull factors of cross-border forced migration and internal displacement. We consider a full panel data analysis and estimate a random effects joint hurdle model following the Bayesian paradigm; the resultant posterior is approximated through the Integrated Nested Laplace Approximation.
Conigliani, C. (2024). Joint modelling of dyadic and monadic count outcomes: an application to modelling forced migration flows. STATISTICAL MODELLING [10.1177/1471082X241302176].
Joint modelling of dyadic and monadic count outcomes: an application to modelling forced migration flows
Caterina Conigliani
2024-01-01
Abstract
The aim of this study is to explore the adoption of a joint modelling framework for dealing with dyadic and monadic count outcomes with excess zeros simultaneously via a common latent structure. As a case study we consider the problem of identifying the different push and pull factors of cross-border forced migration and internal displacement. We consider a full panel data analysis and estimate a random effects joint hurdle model following the Bayesian paradigm; the resultant posterior is approximated through the Integrated Nested Laplace Approximation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.