Does Longer Tenure Mean Greater Ability? Deep-Rooted Politics and Migration in Rural China
Bibliographic Data
| ID | 7170916 |
|---|---|
| Authors | Ge Zhu (0000-0002-2109-4857, Gansu University of Traditional Chinese Medicine, corresponding author) |
| Year | 2025 |
| Volume | 61 |
| Issue | 2 |
| Pages | 233-255 |
| Publication date | 2025-02-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | The Journal of Development Studies (JOURNAL) |
| Journal identifiers | ISSN: 0022-0388 • E-ISSN: 1743-9140 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00220388.2024.2401408 |
| OpenAlex | W4402448327 |
| Language | EN |
| Citations received | 1 |
| References cited | 52 |
This study examines the political motivations behind changes in labor migration rates in Chinese villages. Using data from the China village survey, we estimate the impact of the tenure gap between the village committee director and party branch secretary on village labor migration rates. We find that within the dual power structure of villages, a longer political tenure for the secretary relative to the director significantly suppresses village labor migration rates, while a shorter tenure significantly promotes them. IV estimation supports the causal interpretation found by OLS estimation. This mechanism of causality is associated with vested interests stemming from ambiguous ownership, having a director or secretary with a longer political tenure tends to bias these interests towards villagers or township authorities. Other accompanying effects of the tenure gap should not be ignored, including the amplification effect of the non-laboring population, the feedback effect of labor, and the shrinkage effect of outsiders. This causal relationship is heterogeneous, the dual role analysis shows that the structure and stance of village leaders will affect the strength of the causal relationship, and the regional heterogeneity analysis shows that economic factors that drive village labor migration may be more important than political factors
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| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |