ORIGINAL RESEARCH article
Front. Sustain. Food Syst.
Sec. Land, Livelihoods and Food Security
Volume 9 - 2025 | doi: 10.3389/fsufs.2025.1647052
This article is part of the Research TopicBuilding Resilience Through Sustainability: Innovative Strategies In Agricultural SystemsView all 19 articles
Bridging the Urban–Rural Income Divide through Entrepreneurship: Evidence from a Double Machine Learning Approach in China
Provisionally accepted
- 1Chinese Academy of Agricultural Sciences Institute of Agricultural Economics and Development, Beijing, China
- 2Agricultural Information Institute of CAAS, Beijing, China
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Narrowing the urban–rural income gap in a sustainable and inclusive manner remains a longstanding concern in development economics. This study investigates how entrepreneurial activity can contribute to narrowing the urban–rural income gap in China, with a focus on technological spillovers and structural transformation. Drawing on a county-level panel dataset from 2000 to 2022, we apply a Double Machine Learning (DML) framework for causal inference. The empirical results show that entrepreneurship significantly reduces the urban–rural income gap, and the findings are robust to a series of validity checks. Mechanism analysis reveals two key pathways through which entrepreneurship helps narrow the income gap. First, it enhances resource allocation efficiency via knowledge and technology spillovers. Second, it promotes industrial upgrading in rural areas. Heterogeneity analysis shows that the effects are particularly pronounced in central and western regions. Across industries, labor-intensive entrepreneurship exerts the strongest equalizing effect, while technology-intensive sectors rely more on spillover channels. The impact of resource-intensive entrepreneurship is comparatively weaker and may be accompanied by negative externalities. This study provides novel empirical evidence on how entrepreneurship can support coordinated urban–rural development and informs the design of regionally and sectorally differentiated innovation policies.
Keywords: entrepreneurial activity, Urban–rural income gap, common prosperity, Double machine learning, China
Received: 14 Jun 2025; Accepted: 08 Sep 2025.
Copyright: © 2025 Hao, Liu, Wang and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Guogang Wang, Chinese Academy of Agricultural Sciences Institute of Agricultural Economics and Development, Beijing, China
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