EN中文

PROGRESS IN GEOGRAPHY >

2025 , Vol. 44 >Issue 3: 534 - 550

DOI: https://doi.org/10.18306/dlkxjz.2025.03.008

Original article

Spatial patterns and driving factors of interprovincial elderly migration in China

  • GU Hengyu , 1 ,
  • LI Yuxiang 2 ,
  • WAN Siqi 3 ,
  • WANG Yuqu , 4, *
Expand
  • 1. School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
  • 2. School of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China
  • 3. School of Philosophy and Social Development, South China Normal University, Guangzhou 510631, China
  • 4. School of Geography, South China Normal University, Guangzhou 510631, China

Received date: 2024-06-07

  Revised date: 2024-09-15

  Online published: 2025-03-24

Supported by

National Natural Science Foundation of China(42301221)

National Natural Science Foundation of China(42301278)

National Natural Science Foundation of China(72404093)

Young Elite Scientists Sponsorship Program by CAST(2023QNRC001)

Fold

Abstract

China has fully entered a stage of moderate aging, and the elderly migration population has become a focal group in contemporary urban and rural governance. Supported by the data of interprovincial migration flows of China's elderly population from 2000 to 2020, we used social network analysis and the eigenvector spatial filtering Poisson pseudo-maximum likelihood estimation (ESF PPML) gravity model to explore the spatial-temporal variability of influencing factors of interprovincial elderly migration in China. The following conclusions were drawn: 1) From 2000 to 2020, the scale of China's interprovincial elderly migration population continued to grow, and the main destinations remained basically stable. 2) The migration pattern of the elderly population remained stable but also with some changes: Generally, a large number of elderly people migrated from the northeastern, central, southwestern, and northwestern regions to the northern, eastern, and southern regions; however, from 2015 to 2020, there was a reversal trend in the outflow of elderly people from the southwestern and northwestern regions. In addition, the density of the elderly migration network first decreased and then increased, and the source areas became increasingly dispersed while the destination areas remained concentrated. The main migration flows occurred more frequently between adjacent provinces over time. 3) The ESF PPML model indicated that traditional gravity factors (population size, geographical distance), living costs, natural environment factors, health service facilities, resource depletion level, and social network factors jointly drove the interprovincial elderly migration pattern between 2000 and 2020. 4) Over the 20-year period, the hindering effect of living costs on interprovincial elderly migration showed a weakening trend, while the promoting effect of social network factors on elderly migrants had gradually increased. The impact of health service facilities on the elderly migrants was relatively weak and fluctuated, while natural environment amenity only significantly affected the scale of out-migration of the elderly population. The findings of this study provide a scientific and empirical foundation for actively addressing population aging and promoting high-quality population development in the new era.

Key words： elderly population; aging; interprovincial migration; social network analysis; gravity model; ESF PPML

Cite this article

GU Hengyu , LI Yuxiang , WAN Siqi , WANG Yuqu . Spatial patterns and driving factors of interprovincial elderly migration in China[J]. PROGRESS IN GEOGRAPHY, 2025 , 44(3) : 534 -550 . DOI: 10.18306/dlkxjz.2025.03.008

References

Publishing order | Descend order by publishing year | Descend order by cited within
[1]
Zhang J S. The evolution of China's one-child policy and its effects on family outcomes[J]. Journal of Economic Perspectives, 2017, 31(1): 141-160.

[2]
Feng Q S, Yeung W J J, Wang Z L, et al. Age of retirement and human capital in an aging China, 2015-2050[J]. European Journal of Population, 2018, 35(1): 29-62.

[3]
杨菊华, 卢瑞鹏. “漂老”与 “老漂”: 国内老年流动人口的研究进展与展望[J]. 西安交通大学学报(社会科学版), 2023, 43(1): 84-94.

[Yang Juhua, Lu Ruipeng. Elderly migrants in China: Research progress and future prospects. Journal of Xi'an Jiaotong University (Social Sciences), 2023, 43(1): 84-94.]

[4]
万思齐, 秦波. 老年人口迁移的研究进展及其启示[J]. 地理科学进展, 2022, 41(5): 922-934.

DOI

[Wan Siqi, Qin Bo. A review of elderly migration research and implications. Progress in Geography, 2022, 41(5): 922-934.]

DOI

[5]
柴彦威, 田原裕子, 李昌霞. 老年人居住迁移的地理学研究进展[J]. 地域研究与开发, 2006, 25(3): 109-115.

[Chai Yanwei, Tahara Yuko, Li Changxia. A review of the geographical research on the elderly migration. Areal Research and Development, 2006, 25(3): 109-115.]

[6]
Wiseman R F. Why older people move: Theoretical issues[J]. Research on Aging, 1980, 2(2): 141-154.

[7]
Hays J C. Living arrangements and health status in later life: A review of recent literature[J]. Public Health Nursing, 2002, 19(2): 136-151.

PMID

[8]
Fielding A J. Migration and social mobility: South East England as an escalator region[J]. Regional Studies, 1992, 26(1): 1-15.

PMID

[9]
Graves P E. A reexamination of migration, economic opportunity, and the quality of life[J]. Journal of Regional Science, 1976, 16(1): 107-112.

[10]
Shanas E, Streib G F. Social structure and the family: Generational relations[M]. Englewood Cliffs, USA: Prentice Hall, 1965.

[11]
Litwak E, Jr Longino C F. Migration patterns among the elderly: A developmental perspective[J]. The Gerontologist, 1987, 27(3): 266-272.

[12]
Yahirun J J. Take me "home": Return migration among Germany's older immigrants[J]. International Migration, 2014, 52(4): 231-254.

PMID

[13]
蔡裕莹, 王洁晶. 人口的空间流动与代际社会流动: 出生地和流入地的影响[J]. 人文地理, 2024, 39(1): 68-79.

[Cai Yuying, Wang Jiejing. Spatial mobility and intergenerational social mobility of migrants: The influence of birthplace and destinations. Human Geography, 2024, 39(1): 68-79.]

[14]
Liu Y, Huang C Y, Wu R W, et al. The spatial patterns and determinants of internal migration of older adults in China from 1995 to 2015[J]. Journal of Geographical Sciences, 2022, 32(12): 2541-2559.

DOI

[15]
Rappaport J. Moving to nice weather[J]. Regional Science & Urban Economics, 2007, 37(3): 375-398.

[16]
Wang M M, Yang Y C, Jin S T, et al. Social and cultural factors that influence residential location choice of urban senior citizens in China: The case of Chengdu City[J]. Habitat International, 2016, 53: 55-65.

[17]
van Diepen A M L, Mulder C H. Distance to family members and relocations of older adults[J]. Journal of Housing and the Built Environment, 2009, 24(1): 31-46.

[18]
Liaw K L, Frey W H, Lin J P. Location of adult children as an attraction for black and white elderly primary migrants in the United States[J]. Environment and Planning A: Economy and Space, 2002, 34(2): 191-216.

[19]
Kim J H, Han J H. Myths of migration on retirement in Korea: Do the elderly move to less dense areas?[J]. Habitat International, 2014, 41: 195-204.

[20]
Jauhiainen J S. Will the retiring baby boomers return to rural periphery?[J]. Journal of Rural Studies, 2009, 25(1): 25-34.

[21]
Qin B, Peng Y Y, Wan S Q. The geography of older adults' migration in China: Spatial patterns and driving forces[J]. Population, Space and Place, 2024, 30(4): e2754. doi: 10.1002/psp.2754.

[22]
古恒宇, 李薇, 刘晔, 等. 异地养老、家属随迁与中国流动老人居留意愿[J]. 热带地理, 2023, 43(6): 1123-1133.

DOI

[Gu Hengyu, Li Wei, Liu Ye, et al. Off-site pension, migrant families, and the settlement intention of older migrants in China. Tropical Geography, 2023, 43(6): 1123-1133.]

DOI

[23]
刘晔, 王晓歌, 管靖, 等. 1990—2015年亚洲内部人口迁移格局及影响因素[J]. 地理学报, 2022, 77(10): 2409-2425.

DOI

[Liu Ye, Wang Xiaoge, Guan Jing, et al. Spatial pattern and determinants of international migration flows in Asia, 1990-2015. Acta Geographica Sinica, 2022, 77(10): 2409-2425.]

DOI

[24]
Shen J F. Error analysis of regional migration modeling[J]. Annals of the American Association of Geographers, 2016, 106(6): 1253-1267.

[25]
古恒宇, 劳昕, 温锋华, 等. 2000—2020年中国省际人口迁移格局的演化特征及影响因素[J]. 地理学报, 2022, 77(12): 3041-3054.

DOI

[Gu Hengyu, Lao Xin, Wen Fenghua, et al. Spatiotemporal patterns and determinants of interprovincial migration in China between 2000 and 2020. Acta Geographica Sinica, 2022, 77(12): 3041-3054.]

DOI

[26]
Flowerdew R, Aitkin M. A method of fitting the gravity model based on the Poisson distribution[J]. Journal of Regional Science, 1982, 22(2): 191-202.

PMID

[27]
Biagi B, Faggian A, McCann P. Long and short distance migration in Italy: The role of economic, social and environmental characteristics[J]. Spatial Economic Analysis, 2011, 6(1): 111-131.

[28]
Skeldon R. Of skilled migration, brain drains and policy responses[J]. International Migration, 2009, 47(4): 3-29.

[29]
Dou X L, Liu Y J. Elderly migration in China: Types, patterns, and determinants[J]. Journal of Applied Gerontology, 2017, 36(6): 751-771.

DOI PMID

[30]
高斯瑶, 程杨. 北京市老年人口迁移意愿及影响因素研究[J]. 地理研究, 2018, 37(1): 119-132.

DOI

[Gao Siyao, Cheng Yang. Willingness to relocation of the older people within Beijing. Geographical Research, 2018, 37(1): 119-132.]

[31]
Huang C Y, Liu Y, Pan Z H, et al. Modelling locational choices of older adults in China, 2010-2015[J]. Applied Geography, 2023, 155: 102954. doi: 10.1016/j.apgeog. 2023.102954.

[32]
Gu H Y, Jie Y Y, Lao X. Health service disparity, push-pull effect, and elderly migration in ageing China[J]. Habitat International, 2022, 125: 102581. doi: 10.1016/j.habitatint.2022.102581.

[33]
任远, 金雁, 陈虹霖. 多类型和具体文化制度环境下的老年人口迁移流动: 一个解释性的框架[J]. 华东师范大学学报 (哲学社会科学版), 2020, 52(4): 143-155, 187-188.

[Ren Yuan, Jin Yan, Chen Honglin. Different types of elderly migration influenced by concrete cultural systems: A framework. Journal of East China Normal University (Humanities and Social Sciences), 2020, 52(4): 143-155, 187-188.]

[34]
万思齐, 彭彦彦, 秦波, 等. 中国老年人口省际迁移的时空格局与影响因素: 基于人口普查微观数据的分析[J]. 地理研究, 2024, 43(6): 1482-1501.

DOI

[Wan Siqi, Peng Yanyan, Qin Bo, et al. Spatio-temporal patterns and influencing factors of interprovincial elderly migration in China: Based on the census data. Geographical Research, 2024, 43(6): 1482-1501.]

[35]
Yu W H, Peng Y W, Yao X. The effects of China's supporting policy for resource-exhausted cities on local energy efficiency: An empirical study based on 284 cities in China[J]. Energy Economics, 2022, 112: 106165. doi: 10.1016/j.eneco.2022.106165.

[36]
Li S X Alex, Hu W Y, Guo F Y. Recent relocation patterns among older adults in the United States: Who, why, and where[J]. Journal of the American Planning Association, 2021, 88(1): 15-29.

[37]
Yan D, Kong Y, Ren X H, et al. The determinants of urban sustainability in Chinese resource-based cities: A panel quantile regression approach[J]. Science of the Total Environment, 2019, 686: 1210-1219.

[38]
Mincer J. Family migration decisions[J]. Journal of Political Economy, 1978, 86(5): 749-773.

Options
Outlines

/

〈 〉