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Journal of the Royal Statistical Society Series A (Statistics in Society)
Article . 2019 . Peer-reviewed
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A Latent Class Growth Model for Migrants’ Remittances: An Application to the German Socio-Economic Panel

A latent class growth model for migrants' remittances: an application to the German socio-economic panel
Authors: Bacci Silvia; Bartolucci Francesco; Bettin Giulia; Pigini Claudia;

A Latent Class Growth Model for Migrants’ Remittances: An Application to the German Socio-Economic Panel

Abstract

SummaryWe propose a latent class mixture growth model with concomitant variables to study the time profiles of international remittances sent by first-generation migrants in Germany from 1996 to 2012. The latent class approach enables us to identify homogeneous subgroups of migrants associated with different trajectories for their remitting behaviour, which can be interpreted in the light of the theoretical economic background. In addition, the inclusion of concomitant covariates allows us to uncover whether the assignment of migrants to a specific subgroup can be ascribed to their observable characteristics (e.g. their intention to return home), as conjectured by the theoretical models. The model proposed is easily estimated through an expectation–maximization algorithm. Results show that migrants can be clustered in three groups, two of which reflect the evolution of remittances predicted by economic theory.

Country
Italy
Keywords

Concomitant variables approach; Latent class model; Latent trajectory model; Longitudinal data; Remittances, longitudinal data, latent trajectory model, concomitant variables approach, remittances, Applications of statistics, latent class model

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
hybrid