Tropical Geography

   

Spatio-Temporal Evolution and Influencing Factors of PopulationAging in the Chengdu-Chongqing Economic Circle at the County Level in China Using the Latest Three National Census Data

Junjun Guo(), Yuping Liu()   

  1. Public Policy Research Institute, China West Normal University, Nanchong 637009, China
  • Received:2023-02-06 Revised:2023-05-03 Online:2023-11-03
  • Contact: Yuping Liu E-mail:kangweiye1982@163.com;emniang114@163.com

Abstract:

Based on the National Census data of 2000, 2010, and 2020, with districts and counties as spatial units, the current situation of population aging is described using a time-series comparison method, and its distribution position is identified using a standard deviation ellipse. Moran's I index was used to investigate the spatial correlation and evolution characteristics of population aging, and the Dagum Gini coefficient and decomposition were used to evaluate its regional differences and sources. Then, a spatial econometric regression model was used to test the factors influencing the spatial differentiation of population aging. This study revealed that the population aging of counties in the Chengdu-Chongqing economic circle has been accelerating as a unit from 2000 to 2020. However, different regions before and after 2010 have shown relatively different changes. The center of population aging in the counties gradually shifted to Chengdu over time. Population aging in counties of the Chengdu-Chongqing economic circle mainly shows the spatial distribution characteristics of similar types of agglomeration; counties with significant spatial correlation are mainly characterized by high-high or low-low type clustering, of which the latter has gradually concentrated in Chengdu and Chongqing during the survey period. After 2010, the high-high type clustering areas rapidly concentrated on the two wings of the central axis of Chengdu and Chongqing. The overall difference in population aging of the counties in the Chengdu-Chongqing economic circle accelerated during the investigation period. The increase and decrease in intra-regional differences varied among different periods, with increased inter-regional differences occurring after 2010. Hypervariable density contributed the most to the overall difference in population aging. Compared with 2010, factors such as aging inertia, fertility inertia, population inflow, and education level had a greater impact on the spatial differentiation of population aging in the Chengdu-Chongqing economic circle in 2020, and an increasing number of elderly people have been observed to gather in more densely populated districts and counties since 2010. Overall, this study provides a detailed presentation of the spatial imbalance and dynamic evolution characteristics of population aging at the county level in the Chengdu-Chongqing economic circle over the past two decades and reports that, compared to 2000-2010, the population aging in the counties of the Chengdu-Chongqing economic circle during 2010-2020 underwent rapid deepening with an overall increase in differences and showed new changes in deepening speed, regional relative aging degree, and distribution of similar types of agglomeration counties, that could be considered, there are also certain differences in the causes of population aging in the counties.

Key words: population aging, county level, census, spatial econometric regression, Chengdu-Chongqing economic circle

CLC Number: 

  • C922