A Dynamic Regional Integrated Assessment Model to Assess the Impacts of Changing Globalization and Environmental Stewardship on the Regional Economy and Environmental Quality
Creators: name: Jeong, Junyoung
name: Cultice, Brian
name: Chun, Soomin
name: Shaffer-Morrison, C. Dale
name: Gong, Ziqian
name: Bielicki, Jeffrey
name: Cai, Yongyang
name: Irwin, Elena
name: Jackson-Smith, Douglas
name: Martin, Jay
name: Wilson, Robyn
Publisher: name: Unknown
Year: 2024
Subjects: subject: Climate Change
subject: Environmental Economics and Policy
subject: Food Consumption/Nutrition/Food Safety
subject: food-water-energy systems
subject: integrated assessment model
subject: global-to-local linkages
subject: scenarios framework
subject: global economy
subject: environmental stewardship
subject: climate change

description: Changes in the global economy and climate system have large and wide-ranging repercus- sions for local and regional economies and ecosystems. Here we focus on global-to-local linkages that are hypothesized to impact water quality outcomes within a five-state Great Lakes-Corn Belt region, which includes some of the most intensive agricultural region of the Midwest. We develop a dynamic integrated assessment model (IAM) that links the regional economy to global conditions, local land use change, and water quality outcomes and use a sce- narios framework to assess the likelihood that phosphorus reduction targets for Lake Erie are met by 2050 under a range of plausible global and regional conditions. We examine the relative role that global economic and climate conditions play in regional land use and water quality outcomes and the extent to which local land stewardship incentives and best management prac- tices (BMPs) can offset the potential negative effects of global economic and environmental changes. By integrating a regional-level forward-looking dynamic model, a state-level static computable general equilibrium model, and a local-level land use change model, this IAM en- ables a comprehensive and theoretically consistent integration from global conditions through regional and local decision-making. The model simulates five scenarios defined by distinctly different combinations of global commodity prices, CO2 prices, climate conditions, produc- tivity, population, and economic growth. Our results reveal that success in attaining the policy target is relatively uncertain and highly dependent on future economic, environmental, and policy conditions. We find that only two of the scenarios are projected to attain the 40 per- cent spring DRP and TP reduction targets nine out of ten years by the 2030’s. Other results confirm that lower commodity prices generally lead to reduced cropland acres and are mostly associated with better water quality outcomes. However greater intensification of cropland use is not associated with greater water pollution, a result that may be driven by the relatively high adoption rates for subsurface placement that are reached in later years across scenarios. Taken together, these results demonstrate the potential for local policies to incentivize BMP adoption at levels that can act as a buffer to uncertain, changing global conditions.