Abstract
Spatio-temporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focusing on internal (i.e. domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e. cells of size 500×500 m) for the entirety of the country, and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a distance of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a circle of radius ≈1 km.
Highlights
Demography, spatial patterns of population changes, has been a target of intensive research because of its economical and societal implications, such as difficulties in upkeep of infrastructure [1,2,3], policymaking related to city planning [1,2] and integration of municipalities [3]
These and other factors are often non-randomly distributed in space, creating spatial patterns of 2 migration and population changes over time
Our analysis suggests that aggregating nearby cells around either the source or destination of migration seems to improve the explanatory power of the gravity model (GM)
Summary
Demography, spatial patterns of population changes, has been a target of intensive research because of its economical and societal implications, such as difficulties in upkeep of infrastructure [1,2,3], policymaking related to city planning [1,2] and integration of municipalities [3]. A key factor shaping spatial patterns of demographic dynamics is migration. [4,5,6] These and other factors are often non-randomly distributed in space, creating spatial patterns of 2 migration and population changes over time. A number of models have been proposed to describe and predict spatio-temporal patterns of human migration [7,8,9,10,11,12,13]
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