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A mixture growth model for migrants' remittances: An application to the German Socio-Economic Panel

Author

Listed:
  • Silvia Bacci

    (Universita' di Perugia (IT))

  • Francesco Bartolucci

    (Universita' di Perugia (IT))

  • Giulia Bettin

    (Universita' Politecnica delle Marche and MoFiR (IT))

  • Claudia Pigini

    (Universita' Politecnica delle Marche, MoFiR)

Abstract

We propose a bivariate 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 allows us to identify homogeneous sub-groups of migrants associated with different trajectories for their remitting behavior, which can be interpreted in the light of the theoretical economic background. In addition, the latent class model combined with the concomitant variable approach allows us to uncover whether the assignment of migrants to a specific sub-group can be ascribed to their observable characteristics, namely their return intention, as conjectured by the theoretical models.

Suggested Citation

  • Silvia Bacci & Francesco Bartolucci & Giulia Bettin & Claudia Pigini, 2017. "A mixture growth model for migrants' remittances: An application to the German Socio-Economic Panel," Mo.Fi.R. Working Papers 145, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
    • Handle: RePEc:anc:wmofir:145
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    References listed on IDEAS

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    Cited by:

    1. David Aristei & Silvia Bacci & Francesco Bartolucci & Silvia Pandolfi, 2021. "A bivariate finite mixture growth model with selection," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(3), pages 759-793, September.

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    More about this item

    Keywords

    Bivariate model; Concomitant variables approach; Latent class model; Latent trajectory model; Longitudinal data; Remittances;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • F22 - International Economics - - International Factor Movements and International Business - - - International Migration
    • F24 - International Economics - - International Factor Movements and International Business - - - Remittances

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