Resumen

EL objectivo de este trabajo es evaluar La precisión empirica del Modelo de MobiLidad Cornell. Se describe La migración. como un proceso estocástico governado por probabilidades no-estacionarias: durante un intervalo de tiempo dado, se presume que un individuo está expuesto a un riesgo de migrar, y que éste decrece a medida que él continúa viviendo en la misma comunidad. Entonces, la hipótesis principal es que la propensión de una persona a mobilizarse declina a medida que aumenta la duración de su residuencia.

Una hipótesie secundaria propane que la edad interviene en esta relación. Datos longitudinales, (5,000 historias residenciales del sistema de registros de población de los Paises Bajos, fueron analizados y traducidos en probabilidades prospectivas específicas por edad y duración.

Ambas hipótesis fueron verificadas. Específicamente, la rolación. es negativa, curvilinear, y varía significativamente con la edad, Para facilitar el análisis de simulación del modelo, las relaciones encontradas en los datos estan resumidas en un conjunto de ecuaciones logarítmicas de predicción.

Los hallazgos de este trabajo enfatizan la limitación fundamental de los modelos de probabilidad estacionaria para describir la migración y sugieren que la alternativa no-estacionaria es una formulación. más precisa. En general, los proceeos de cambia que sólo tienen una semejanza formal con la migración, por ejemplo un cambio de nombre o de actitud, pueden ser gobernados también por un principio de estabilidad acumulativa. La evidencia justifica major investigación sobre la aplicabilidad del modelo a ostros procesos sociales en los que operan factotes de tipo inercia.

Summary

The objective of this paper is to evaluate the empirical accuracy of the Cornell mobility model. Migration is formulated as a stochastic process governed by non-stationary probabilities: during a given interval of time, an individual is presumed to undergo a risk of migrating that decreases as he continues to reside in the same community. The major hypothesis, then, is that a person’s propensity to move declines as his duration of residence increases.

A secondary hypothesis proposes that age interacts with this relationship. Longitudinal data (5,000 residential histories from the Netherlands system of population registers) were analyzed and translated into prospective probabilities that are age- and duration-specific.

Both hypotheses were substantiated. Specifically, the relationship is negative, curvilinear, and varies significantly by age. To facilitate simulation analysis of the model, the relationships found in the data are summarized in a set of logarithmic prediction equations.

The findings of this paper underscore the fundamental limitation of stationary probability models in portraying migration and suggest that the non-stationary alternative is a more accurate formulation. More generally, processes of change which bear only a formal resemblance to migration (for example, brand switching or attitudinal change) may be governed by a principle of cumulative stability too. The evidence warrants further inquiry into the applicability of the model to other social processes where inertialike factors operate.

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