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Analysing inter-provincial urban migration flows in China: A new multilevel gravity model approach.
- Source :
- Migration Studies; Mar2020, Vol. 8 Issue 1, p19-42, 24p
- Publication Year :
- 2020
-
Abstract
- This paper proposes a novel multilevel gravity model of migration to study the under-researched topic of urban to urban migration in China. Many previous studies have looked at rural to urban migration in the context of urbanisation and economic development, and at return migration. Very few have looked at what is becoming more important in increasingly urbanised countries, which is the movement from one urban location to another. In the study, we develop a new method that allows for the interconnections between migration flows: between those that share an origin, those that share a destination, and where there is a reciprocal flow between places. A conventional gravity model of migration ignores those connections, risking erroneous estimation of the regression parameters and of their statistical significance. It also ignores that those connections are of substantive interest—they reveal the interconnections between places regarding the numbers of migrants that they send and receive. We motivate and illustrate the advantages of our approach using 2010 interprovincial migration census data for China. The results obtained from the model confirm the effect of distance, of population size and of regional income levels. They show that there is greater variation in the numbers of migrants received by provinces than there is in the numbers sent, and that reciprocal migration between pairs of provinces is an important feature of what is happening in China, especially between the neighbouring provinces of Sichuan and Tibet. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20495838
- Volume :
- 8
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Migration Studies
- Publication Type :
- Academic Journal
- Accession number :
- 142489876
- Full Text :
- https://doi.org/10.1093/migration/mny026