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A zero-inflated Poisson model of migration frequency
International Regional Science Review
|January 1, 1996
Summary
Migration frequency is best modeled using a zero-inflated Poisson process, which improves prediction accuracy. Frequent movers are often white, nonunionized individuals with fewer children and less stable marriages.
Area of Science:
- Sociology
- Economics
- Statistical Modeling
Background:
- Modeling migration frequency presents challenges due to a high prevalence of nonmigrants (zeros).
- Traditional models may produce biased coefficients and poor predictions when applied to migration data.
Purpose of the Study:
- To identify the most effective statistical model for analyzing migration frequency.
- To assess the predictive performance of a zero-inflated Poisson process for migration behavior.
Main Methods:
- Utilized data from the U.S. Panel Study of Income Dynamics (1977-1987).
- Applied a zero-inflated Poisson regression model to account for excess zeros in migration data.
- Compared model performance against traditional methods.
Main Results:
- The zero-inflated Poisson process significantly enhances the accuracy of migration prediction.
- Frequent movers were identified as white, nonunionized individuals with fewer children and less stable marriages.
- Frequent occupational changes were also associated with higher migration frequency.
Conclusions:
- A zero-inflated Poisson model is superior for analyzing migration frequency data with many nonmigrants.
- Understanding the characteristics of frequent movers can inform social and economic policies.
- The study highlights the importance of appropriate statistical methods in migration research.
Keywords:
AmericasCultural BackgroundDemographic FactorsDeveloped CountriesEthnic GroupsFamily And HouseholdFamily CharacteristicsFamily SizeMigrantsMigrationModels, TheoreticalNonmigrantsNorth AmericaNorthern AmericaPopulationPopulation CharacteristicsPopulation DynamicsResearch MethodologyTemporary MigrationUnited StatesWhites
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