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Getting on your bike: what difference does a migration history make?

A J Bailey

    Tijdschrift Voor Economische En Sociale Geografie = Journal of Economic and Social Geography = Revue De Geographie Economique Et Humaine = Zeitschrift Fur Okonomische Und Soziale Geographie = Revista De Geografia Economica Y Social
    |January 1, 1989
    PubMed
    Summary

    Individuals with prior migration experiences tend to move sooner than first-time movers. This study analyzes migration history and residential duration using longitudinal data, offering a model for migration behavior.

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    Area of Science:

    • Sociology
    • Demography
    • Economics

    Background:

    • Understanding residential mobility patterns is crucial for urban planning and social science research.
    • Previous migration experiences are hypothesized to influence future residential changes.

    Purpose of the Study:

    • To investigate the relationship between migration history and the duration of residential stays.
    • To test the hypothesis that prior migrants exhibit shorter residential durations than non-migrants.
    • To develop and justify a random utility model for residential sojourns.

    Main Methods:

    • Utilized longitudinal data from the U.S. National Longitudinal Survey of Youth.
    • Employed survival analysis techniques to model residential durations.
    • Applied a random utility framework to explain migration decisions.
    Keywords:
    AmericasDemographic FactorsDeveloped CountriesMigrationModels, TheoreticalNorth AmericaNorthern AmericaPopulationPopulation DynamicsResearch MethodologyTime FactorsUnited States

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    Main Results:

    • Individuals with a history of migration were found to have significantly shorter residential sojourns.
    • The model successfully predicted migration behavior based on past experiences.
    • The random utility model provided a robust theoretical justification for observed patterns.

    Conclusions:

    • Past migration behavior is a strong predictor of future residential mobility.
    • The developed model offers valuable insights into the dynamics of residential change.
    • Findings have implications for understanding population movement and its drivers.