Panel Paper: Assessing the Outcomes of Collaborative Governance in Federal Hydropower Licensing

Friday, November 8, 2013 : 1:35 PM
Plaza II (Ritz Carlton)

*Names in bold indicate Presenter

Nicola Ulibarri, Stanford University
Despite the growing popularity of collaborative approaches to environmental management, empirical work on collaboration’s impacts on the natural environment remains inconclusive. This study explores the outcomes of collaborative governance using the case of federal hydropower licensing. The Federal Energy Regulatory Commission (FERC) oversees all non-federally owned or operated hydropower facilities in the US. FERC’s Integrated Licensing Process encourages the licensee (a utility), federal and state resource agencies, tribes, non-governmental organizations, and communities to work jointly through a 5-year process of studying project impacts on selected resources and developing license conditions that mitigate those impacts. Following the logic of a comparative case study, this study assesses the process and outcomes of 16 recent licensing negotiations, and then compares and contrasts the outcomes between high- vs. low-collaboration cases. For each case, level of collaboration was measured via an online survey of participants, combined with analysis of archival records including meeting minutes, ground rules, and public comments. Outputs and outcomes considered include efficiency of the process (including time to license and presence of conflict post-license); implementability of license conditions regarding aquatic habitat and water quality; and participant opinions of the licenses’ impacts on the environment and economy. This research has potential theoretical, methodological, and practical contributions. As an empirical exploration of the link between collaborative governance and environmental outcomes, it explores whether the theorized benefits of collaboration actually exist. Methodologically, by comparing between multiple data sources (which previous studies often used in isolation), it considers the validity and potential bias of using any single data type to measure collaboration. And practically, it provides a preliminary answer to government agencies and stakeholders whether collaboration is worth the added time, resources, and effort.