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Related Experiment Videos

A method of fitting the gravity model based on the Poisson distribution.

R Flowerdew, M Aitkin

    Journal of Regional Science
    |May 1, 1982
    PubMed
    Summary

    This study introduces a new gravity model fitting method, treating interaction variables as a discrete probability process. This approach is ideal for count data, especially with sparse inter-pair movements.

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    Statistics in medicine·1999

    Area of Science:

    • Spatial interaction modeling
    • Econometrics
    • Demography

    Background:

    • Traditional gravity models may not accurately represent count data, particularly when few interactions occur between certain locations.
    • Existing methods can be insufficient for analyzing migration flows and other count-based spatial interactions.

    Purpose of the Study:

    • To propose and illustrate an alternative method for fitting the gravity model.
    • To adapt the gravity model for count data by treating interaction as a discrete probability process.

    Main Methods:

    • The interaction variable is modeled as a discrete probability process.
    • The mean of this process is a function of size and distance variables.
    • The method is applied to migration data between labor market areas in Great Britain (1970-1971).
    Keywords:
    Demographic FactorsDeveloped CountriesEuropeLabor ForceMathematical ModelMigrationMigration, InternalModels, TheoreticalNorthern EuropePopulationPopulation DynamicsResearch MethodologyUnited Kingdom

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    Main Results:

    • The proposed discrete probability approach offers advantages for count data, especially with sparse inter-pair flows.
    • Demonstrates the model's applicability to real-world migration data.

    Conclusions:

    • The alternative gravity model fitting method provides a more appropriate framework for count-based spatial interaction data.
    • This approach enhances the analysis of migration patterns and similar flow data.