What Drives Country-Level Exposure to the Social Cost of Carbon? Discounting, Economic Scale, and Equity in Developing Economies
DOI:
https://doi.org/10.32479/ijefi.24465Keywords:
Social Cost of Carbon, Climate Policy, Developing Economies, Discounting, Machine Learning, EquityAbstract
The social cost of carbon (SCC) is the central price signal in climate policy, and a recent literature decomposes it into country-level shares of global damage. This paper asks what explains cross-country variation in this country-level SCC (CSCC), and whether developing economies bear a disproportionate share once economic size is taken into account. Using the Ricke et al. (2018) CSCC database merged with macroeconomic and emissions data for 169 countries, an OLS model explains 93 percent of cross-country variation in log CSCC, driven almost entirely by GDP per capita and population. A machine learning ensemble, interpreted with SHAP attribution, confirms this finding. A population-neutral equity measure -- CSCC as a share of GDP -- shows no significant excess burden on developing economies under the baseline specification. Across 24 alternative specifications, the equity conclusion is highly sensitive to the discounting assumption: constant-rate discounting produces a large, significant gap favoring the conventional equity narrative, while Ramsey discounting narrows or eliminates it. The results imply that discounting, not the damage function or emissions scenario, is the decisive choice when integrating country-level SCC estimates into carbon pricing and climate finance policy in developing economies. Both the scale finding and the equity result replicate closely on an independent, newly published national SCC dataset built on an entirely different damage-function methodology.Downloads
Published
2026-09-01
How to Cite
Aggarwal, S., & Aggarwal, M. (2026). What Drives Country-Level Exposure to the Social Cost of Carbon? Discounting, Economic Scale, and Equity in Developing Economies. International Journal of Economics and Financial Issues, 16(5), 26–33. https://doi.org/10.32479/ijefi.24465
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