Modeling China's Province-to-Province Migration Flows using Spatial Interaction Model with Additional Variables
AbstractThe purpose of this paper is to model China's province-to-province migration flows using spatial interaction models. To date, conventional, gravity-type, spatial interaction models have typically employed information only on the number of movers and on the distances between places. This paper employs a new, multivariate approach to such interaction modeling by entering additional variables into the traditional modeling framework. In this particular application, two variables are added, namely, a measure of past migration, called migrant stock, and another measure of annual average total investment. The empirical verification of the models employs two interprovincial migration data sets for China. These involve the 1982-87 and 1985-90 migration flow data, consisting of two 28 x 28 data matrices. The results of the calibration show that the models with the additional variable(s) are capable of distributing migration flows with a much-improved degree of accuracy, in comparison with the conventional model. The calibration therefore provides empirical support for the validity of the multivariate approach to the spatial interaction modeling of migration flows.
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