Panel Paper: Interlocal Collaboration Network and Environmental Governance Performance in China

Friday, November 9, 2018
Taylor - Mezz Level (Marriott Wardman Park)

*Names in bold indicate Presenter

Chen Huang, Huazhong Agricultural University, Wenna Chen, City University of Hong Kong and Hongtao Yi, The Ohio State University

In recent years, scholars have paid increasing attention to collaborative environmental governance at the local level in the context of China (Yi et al. 2017; Chen Suo and Ma 2015; Huang et al. 2017). However, most of the extant literature has focused on the drivers for the formation of the collaboration network, with little attention to how collaboration network affects environmental governance performance. This study aims at filling the gap in extant research by answering the following research question that directly addresses the social influence of the governance network: how does interlocal collaboration network affect the governance performance of the policy actors embedded in the network?

We conduct our analysis with a unique data set: the Dongguan Water Policy Network collected by the research team. As the biggest manufacturing hub in the world, Dongguan municipal government is faced with tremendous challenges in managing and governing its water resources. Stimulated by the ineffectiveness of vertically managed and fragmented administration of water resources, Dongguan has started experimenting inter-governmental cooperation in water management and administration. A horizontal cooperation network has emerged among the 32 towns in Dongguan. Following a similar codebook and data collection procedure used in the Ecology of Games framework (Lubell 2013; Berardo and Scholz 2010), an interlocal policy network data set is collected in 2015 via survey from 32 towns in Dongguan with a response rate of more than 90%. Along with the network data, we also collected local water governance performance data, as measured in water consumption per unit of GDP and water pollution data, along with a set of control variables at the town level from 2013 to 2015.

With this local water governance network data set, we seek to answer the following questions in our study. How does the interlocal water governance network affect the performance of the 32 towns in water governance? We hypothesize that governance network affects the environmental performance of towns through a social influence mechanism, and thus we expect governance performance of ego towns will emulate that of alters as a result of network participation.

We test this hypothesis by estimating a network/spatial autoregressive model: y = α1W1y + α2W2y + Xβ + ε, where y is the water governance performance at the town level, W1 represents the interlocal governance network matrix, W2 represents a spatial matrix among the 32 towns. X includes a set of control variables, such as GDP, local fiscal health, population and median income. The network/spatial effects are captured by estimating the size and significance of α1 and α2. A positive and significant α1 indicates a strong social influence effect on local water governance performance imposed from the governance network. Preliminary results indicate strong support for the existence of network and spatial effects. The study represents a contribution to the burgeoning literature on collaborative network governance performance.