Spatial Variations in Fertility: Geographically Weighted Regression Analyses for Town-and-Village-Level TFR in Japan
Kenji Kamata, National Institute of Population and Social Security Research, Japan
Kimiko Tanaka, University of Wisconsin at Madison
To re-examine previous research on fertility variations in Japan and to assess heterogeneity of the relationships between regional fertility rates and their covariates, we estimated geographically weighted regression models that allows us to take spatial autocorrelation into account. Our analytical samples are 2,311 towns and villages based on 2005 administrative boundaries. Our explanatory variables include socio-economic conditions, female labor participation, political measures on childcare, and household structure, that come from a database based on census. The result suggests that most coefficients for covariates on total fertility rates have statistically significant geographical variations, and in some regions, sign shifts in the opposite direction from what it is in the global model. We conclude that fertility response to external forces may vary across regions because of their historical and geographical settings, and results of the global model may not be appropriate to uniformly apply for each region.
Presented in Session 32: Statistical, Spatial, and Network Methods