Panel: Evidence and Local Environmental Governance: Methods and Data Sources for Measuring the Design and Impacts of Local Policy
(Natural Resource Security, Energy and Environmental Policy)

Friday, November 3, 2017: 8:30 AM-10:00 AM
Soldier Field (Hyatt Regency Chicago)

*Names in bold indicate Presenter

Panel Organizers:  Tyler A Scott, University of Georgia
Discussants:  David P. Carter, University of Utah

Fracking Regulatory Stringency: The Role of Time and Overall Policy Goal
Gwen Arnold, Le Anh Nguyen Long, Madeline Gottlieb, Michael Bybee and Nikita Sinha, University of California, Davis

Linking Stated Policy Priorities and Policy Framing to Environmental Risk Resilience.
Tima T. Moldogaziev, Tyler A Scott and Jason Anastasopoulos, University of Georgia

Local governments play a significant role in many facets of environmental policy and management. However, local government data are typically much more limited, and irregular, than national or state data, which makes it difficult to assess the impacts of local policy and planning initiatives. This panel presents four papers that demonstrate unique research designs and data sources suitable for studying local environmental governance practices. Each paper draws upon a novel data source, and concerns a different environmental issue--municipal greenhouse gas (GHG) mitigation, permitting and regulation of unconventional oil and gas development, public health impacts of natural resource extraction, and wildfire and drought risk management--in which local decision-making plays a major role in determining policy outcomes.

The first paper uses a longitudinal national survey of local officials in the United States who direct municipal environmental sustainability efforts. Given the diffuse, transboundary nature of GHG emissions, direct measurement of city level policy impacts are not readily feasible. Thus, this paper demonstrates how expert solicitation from those tasked with implementing and overseeing local policy efforts over a period of time can be used as a proxy measure for local-level pollution outcomes. The paper uses a selection model to account for selection bias associated with voluntary adoption in estimating expected impacts. The second paper draws upon a novel database of 426 hydraulic fracturing policies adopted by different municipalities in the state of New York; the authors analyze the text of each policy to develop a comprehensive measure of policy stringency. These data are then coupled with measures of policy support and socio-economic conditions to understand how local community attributes influence the focal outcomes and time horizon of municipal policies. The third paper examines local grants provided by the state of Colorado meant to mitigate the public health impacts of mining and energy extraction in local communities. Using machine learning text analysis, the authors generate a novel dataset that quantifies the focus and content of grant applications from 2013 to 2016. In particular, the authors assess the extent to which local grant applications emphasize measurable impacts and the subsequent role of different impacts in determining granting funds. The results demonstrate the relative importance of different impact measures in driving local policy responses. Finally, the fourth paper examines how counties in the state of California prioritize and implement efforts to prevent and mitigate acute and chronic environmental disasters, specifically wildfire and severe drought. Using topic modeling, the authors measure local policy priorities based upon yearly budget proposals and budget hearing minutes from each of 56 counties from 2012 to 2017. These data are then matched to county budget records in order to measure how well stated priorities are reflected in actual expenditures. Further, the authors develop metrics of relative problem local problem severity using historic drought and wildfire records in order to gauge how these pressures affect prioritization and subsequent policy responses. This paper demonstrates how procedural documents generated by local governments can be used to measure how prepare for uncertain, potentially high consequence environmental disasters.