The Impact of Farmland Transfer on Urban–Rural Integration: Causal Inference Based on Double Machine Learning

Urban–rural fragmentation represents a significant challenge encountered by nations globally, particularly in both developing and developed contexts, during the modernisation process. This study examines the effects of rural land system reform on facilitating integrated development between urban and rural areas. The analysis of the impact of the 2010 liberalisation of the land transfer policy employs a dual machine learning model, utilising provincial-level data from China spanning 2005 to 2022, to address the limitations of traditional causal inference models while ensuring estimation accuracy. The findings indicate that the reform of the rural land system significantly enhances integrated urban–rural development, particularly in demographic, economic, and ecological dimensions. The mechanisms encompass the facilitation of extensive land and agricultural service operations, the development of new business entities, the migration of rural labour, and the enhancement of agricultural capital. Furthermore, notable disparities exist in the effects of reforms across various regions, particularly concerning urban–rural integration development and land transfer levels. The policy effects of land transfer exhibit a marginally diminishing trend. The influence of land transfer on urban–rural integration varies with economic development levels, demonstrating a nonlinear relationship, with the most pronounced effects observed in regions with moderate economic development. Additionally, the policy effects of land transfer differ based on geographic location. The impact of land transfer policies varies across geographic regions, with the central region exhibiting the most significant effect, followed by the north-eastern region, the western region, and the eastern region, which shows the least effect. This study provides a reference for advancing the reform of the marketisation of land factors, improving the efficiency of land resource allocation, and regionally and in multiple layers advancing the reform of the rural land system.