Networked Civil Society: Three Essays on the Government–Nonprofit Relationship in China

Abstract

This dissertation has two goals: 1) Introducing data science methodologies to nonprofit studies; 2) Examining the impact of social relations on nonprofits’ social and economic behaviors. Ultimately, this dissertation provides empirical evidence for a new paradigm which is just in formation by a few scholars: a holistic network theory of government–nonprofit relationship. Chapter 2 establishes a robust and generalpurpose database which has the potential to support the development of a research topic. It also introduces the methodology for data management in contemporary quantitative social science. Based on the database established, Chapter 3 approaches the research question on nonprofit’s autonomy using network theory and finds that, although nonprofit organizations in China may lose their autonomy because of government officials on board, these organizations still enjoys a substantial level of freedom in the organizational network. The Chinese nonprofit sector suggests the existence of autonomous order theorized by political philosophers and observed in liberal societies. Chapter 4 reconsiders a classic research question in public economics – the crowd-out/in effect of government funding on private donations to nonprofits. This chapter proposes an innovative theoretical perspective for understanding the role of social relations in crowding mechanism: compensating mode and amplifying mode. Analysis suggests that, although government funding to a nonprofit may crowd out the private donations to the same organization, private donations are not reduced but redistributed to other nonprofits in the organizational network. This chapter also uses standardized data workflow to boost the research life-cycle, information extraction techniques to construct structured dataset from semi-structured raw data files, demonstrates how data science methodologies can help causal inference in classic econometrics.