Variations in village migration profiles in rural China
An analysis based on the Second National Agricultural Census data
Bibliographic Data
| ID | 11147938 |
|---|---|
| Authors | Bin Wu (0000-0002-7568-1993, University of Nottingham, corresponding author), Wu Bin (0000-0001-6164-8722, University of Nottingham), Bernadette Robinson (University of Nottingham), Wenjin Long (0000-0003-1419-2544, Renmin University) |
| Year | 2015 |
| Volume | 24 |
| Issue | 2 |
| Pages | 160-186 |
| Publication date | 2015-06-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Asian and Pacific migration journal (JOURNAL) |
| Journal identifiers | ISSN: 0117-1968 • E-ISSN: 2057-049X |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/0117196815579954 |
| OpenAlex | W1778701722 |
| Language | EN |
| Citations received | 4 |
| References cited | 24 |
Relatively little attention is paid to variations in rural migration at the village level, even though labor-supplying villages present considerable diversity in economic and development profiles. This paper examines the relationships between labor and household migration at the village level and the factors associated with different migration patterns through an analysis of data from China’s Second National Agricultural Census. The study identified four types of village migration profiles based on labor and household migration data from 4,482 villages in 10 counties across five provinces. The key characteristics of four types of village migration profiles are highlighted and implications for researchers and policy-makers are discussed
Agriculture · Census · China · Demographic economics · Developing country · Diversity (politics · Economic growth · Economics · Geography · Internal migration · Political science · Population · Regional science · Socioeconomics · Sociology · China's Socioeconomic Reforms and Governance · Demography · Migration and Labor Dynamics · Migration, Ethnicity, and Economy
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| Unique citing works | 4 |
|---|---|
| Citations per year | 0.4 |
| Citation span | 2016 - 2022 (7) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 4 |