Communities Built on Political Trust: Theory and Evidence from China

52 Pages Posted: 13 Feb 2024 Last revised: 11 Apr 2024

See all articles by Yu Zeng

Yu Zeng

Peking University

Shitong Qiao

The University of Hong Kong - Faculty of Law; Duke University School of Law

Date Written: January 15, 2024


This study offers a unique mixed-methods investigation on the formation of neighborhood communities in China’s megacities. We find that the local government helps homeowners overcome prevalent collective action problems and govern themselves more effectively. Neighborhoods that have established homeowners’ associations (HOAs) enjoy better governing outcomes than do those without HOAs, as evidenced by homeowners wielding greater control over neighborhood affairs, showing heightened respect for democratic principles, and maintaining a stronger sense of community identity. Owing to these positive outcomes, and as compared to their counterparts in neighborhoods without HOAs, homeowner activists in neighborhoods with HOAs develop a deeper trust in their local government. As such, our argument that urban communities are based on political trust in authoritarian regimes complicates the conventional view that such regimes either repress civic engagement or manipulate civic organizations for social control.

Keywords: community; political trust; China; homeowners’ association

Suggested Citation

Zeng, Yu and Qiao, Shitong and Qiao, Shitong, Communities Built on Political Trust: Theory and Evidence from China (January 15, 2024). Urban Studies, forthcoming, Duke Law School Public Law & Legal Theory Series No. 2024-13, Available at SSRN: or

Yu Zeng

Peking University ( email )

5 Yiheyuan Road
Haidian District
Beijing, Beijing 100871

Shitong Qiao (Contact Author)

The University of Hong Kong - Faculty of Law ( email )

Pokfulam Road
Hong Kong, Hong Kong

HOME PAGE: http://

Duke University School of Law ( email )


Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
PlumX Metrics