Land Titling: A Catalyst for Enhancing China Rural Laborers’ Mobility Intentions?

Land titling, a critical land institution reform aimed at enhancing tenure security, serves as a pivotal policy instrument to strengthen rural laborers’ mobility intentions. Leveraging a balanced panel dataset from the 2014 and 2016 China Labor-force Dynamic Survey (CLDS), this study employs a diffe...

Full description

Saved in:
Bibliographic Details
Main Authors: Shanshan Mou, Zhongkun Zhu
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Land
Subjects:
Online Access:https://www.mdpi.com/2073-445X/14/4/867
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Land titling, a critical land institution reform aimed at enhancing tenure security, serves as a pivotal policy instrument to strengthen rural laborers’ mobility intentions. Leveraging a balanced panel dataset from the 2014 and 2016 China Labor-force Dynamic Survey (CLDS), this study employs a difference-in-differences (DID) model to evaluate the policy effects of the latest round of land titling on rural laborers’ mobility intentions. The results demonstrate that land titling significantly enhances rural laborers’ willingness to migrate. To ensure robustness, we incorporate individual and year fixed effects, cluster robust standard errors at the household level, and conduct multiple robustness tests, including placebo test, propensity score-matching difference-in-differences (PSM-DID), replacement of dependent variable, clustered adjustment, adding control variables and interaction fixed effects. Mechanism analysis reveals that land titling elevates laborers’ mobility intentions primarily by reducing land reallocation and stimulating investments in agricultural machinery. Heterogeneity analysis further identifies stronger effects in villages dominated by agricultural employment, and among middle-aged laborers. These findings highlight the nuanced role of tenure security in reshaping rural laborer dynamics and provide empirical support for optimizing land-related policies to facilitate structural transformation.
ISSN:2073-445X