Winners and Losers of Climate Change: Damage Inequalities via the DICE Model
A team-led project that downscales the integrated assessment DICE model to country-level resolution using GDP projections, revealing stark inequalities in who bears the economic burden of climate change.
Overview
This project assesses disparities in climate-induced economic damages across countries by downscaling William Nordhaus's Dynamic Integrated Climate-Economy (DICE) model. While the original DICE model operates at a global or regional aggregate level, our team adapted it to country-level resolution using GDP projections from Burke et al.'s datasets, enabling a granular analysis of which nations face the greatest economic vulnerability to climate change.
Motivation
Climate change is often discussed as a global challenge, but its economic impacts are profoundly unequal. Developing nations — which have contributed least to historical emissions — frequently face the most severe damages relative to their economic capacity.
Methodology
- DICE Model Downscaling: The original DICE model was adapted from its aggregate regional structure to operate at the country level. This required mapping regional parameters (damage functions, temperature responses, economic growth rates) onto individual countries using available data.
- GDP Projections Integration: Burke et al.'s datasets provided country-level GDP projections that were integrated into the DICE framework to estimate climate damages as a percentage of future economic output for each nation.
- Inequality Analysis: Damage estimates across countries were analyzed using inequality metrics (Gini coefficients, Lorenz curves) to quantify the distributional consequences of climate change and identify the most vulnerable nations.
Data & Tools
The project relied extensively on Excel for country-level data management, scenario analysis, and optimization calculations. RStudio was used for statistical analysis, visualization of damage distributions across countries, and generating the final presentation materials.
Team Leadership
As team lead, I coordinated the work of multiple students across data collection, model adaptation, analysis, and presentation preparation. This involved dividing tasks based on individual strengths, establishing timelines for intermediate deliverables, and synthesizing contributions into a cohesive final product presented at the Colorado State University International Symposium.
Key Findings
The downscaled analysis reveals significant inequalities in climate damage exposure: lower-income countries face disproportionately larger economic losses relative to their GDP, even though they have contributed minimally to cumulative emissions. These findings underscore the need for differentiated climate policy responses and support arguments for climate finance mechanisms.
Visualizations & Results
