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• W4289731620 abstract "The phenomenon of population aging is gradually spreading around the world. Consequently, it is leading to unsustainable economic development due to the decline of the labor force. Therefore, many people identify the aging population from national and intercontinental levels, as it would not be possible to recognize specific population spatial distribution characteristics and impacting factors in a province or state because of the spatial and temporal differences. In this paper, Jiangsu Province was selected as the study area to represent its aging population’s spatial characteristics and to identify the spatial heterogeneity with impacting factor by Geographically Weighted Regression (GWR), as well as to determine the impacting situation by marginal effect. The results show the following: (1) The impact factor’s spatial heterogeneity from the cities in Jiangsu Province is small but occurs in the city groups, while the impacting situation is the same in the north, central and south city groups, showing a disparity among them. (2) There is a significant change in the impact factor’s influence from 2010 to 2020. (3) The social–economic factor negatively relates to the aging population in 2020, with an interval value of [−1.0585, −1.0632]. This finding indicates that the spatial heterogeneity of the aging population at the province level is not the same as that at the national level. Therefore, we need to consider the local situation more. These findings further provide an empirical basis for the province-level study of the aging population, which differs from the national level." @default.
• W4289731620 created "2022-08-04" @default.
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• W4289731620 date "2022-08-03" @default.
• W4289731620 modified "2023-10-18" @default.
• W4289731620 title "Aging Population Spatial Distribution Discrepancy and Impacting Factor" @default.
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• W4289731620 doi "https://doi.org/10.3390/su14159528" @default.
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