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.
2024
Conigliani, C. (2024). Joint modelling of dyadic and monadic count outcomes: an application to modelling forced migration flows. STATISTICAL MODELLING [10.1177/1471082X241302176].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/493236
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