A Global and Hemispheric Analysis of the Relationship between Environmental Sustainability and Economic Inequality

Authors

DOI:

https://doi.org/10.37773/ees.v9i1.1691

Keywords:

CO2 Emissions, Economic Inequality, Energy Consumption, Temperature Anomaly, Regional Analysis

Abstract

In this article, we examine how income distribution and energy use shaped per-capita CO2 emissions between 1965 and 2022 at three spatial scales—world, northern hemisphere, and southern hemisphere. After re-scaling all the variables to the unit interval, we first estimate separate ordinary least squares regressions and then re-estimate the three equations jointly with Zellner’s seemingly unrelated regression, a step warranted by the substantial contemporaneous error correlation. Across both emission channels—aggregate CO2 and the land-use component—energy consumption emerges as the most consistent and statistically powerful predictor. Inequality effects are heterogeneous. The Gini coefficient amplifies emissions in the southern hemisphere and in the global system but is negligible in the northern fossil-fuel equation, while the Palma ratio reduces land-use emissions once overall inequality is held constant. Temperature anomalies display a further asymmetry, reducing land-use emissions everywhere, yet coinciding with higher fossil-fuel emissions in the south. Joint estimation raises the system-wide goodness of fit to 0.97 for land-use emissions and 0.99 for total emissions and yields more precise coefficients than the separate regressions. The results indicate that decarbonizing energy systems is a universal mitigation priority, whereas distributional reforms and land-governance measures are likely to deliver the greatest additional benefits in the southern hemisphere.

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Additional Files

Published

2026-01-31

How to Cite

Tobón Ospino, M., Marbello Peña, H., & Sierra Porta, D. (2026). A Global and Hemispheric Analysis of the Relationship between Environmental Sustainability and Economic Inequality. Ecology, Economy and Society–the INSEE Journal, 9(1), 87–119. https://doi.org/10.37773/ees.v9i1.1691

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