A latent class growth model for migrants’ remittances: an application to the German Socio-Economic Panel
We 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 differe...
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| Veröffentlicht in: | Journal of the Royal Statistical Society. Series A, Statistics in society Statistics in society, 2019-10, Vol.182 (4), p.1607-1632 |
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| container_issue | 4 |
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| container_title | Journal of the Royal Statistical Society. Series A, Statistics in society |
| container_volume | 182 |
| creator | Bacci, Silvia Bartolucci, Francesco Bettin, Giulia Pigini, Claudia |
| description | We 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. |
| doi_str_mv | 10.1111/rssa.12475 |
| format | Article |
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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. 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| identifier | ISSN: 0964-1998 |
| ispartof | Journal of the Royal Statistical Society. Series A, Statistics in society, 2019-10, Vol.182 (4), p.1607-1632 |
| issn | 0964-1998 1467-985X |
| language | eng |
| recordid | cdi_proquest_journals_2308421127 |
| source | Wiley Online Library Journals Frontfile Complete; Business Source Complete; JSTOR Archive Collection A-Z Listing; Oxford University Press Journals All Titles (1996-Current) |
| subjects | Algorithms Ascription Concomitant variables approach Economic models Economic theory Growth models Latent class analysis Latent class model Latent trajectory model Longitudinal data Migrants Original Articles Remittances Subgroups |
| title | A latent class growth model for migrants’ remittances: an application to the German Socio-Economic Panel |
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