Accounting illusion or genuine decarbonisation? ARIMA-based evidence on Tunisia's NDC3.0 trajectories
DOI:
https://doi.org/10.18686/cest847Keywords:
ARIMA forecasting; NDC3.0; carbon intensity; per-capita emissions; Tunisia; decarbonisation; sectoral analysisAbstract
The credibility of climate targets based on emission intensity raises a central yet underexplored question: in low-growth economies, a decline in the emissions-to-GDP ratio may reflect macroeconomic stagnation rather than genuine decarbonisation, turning compliance with Nationally Determined Contributions (NDCs) into a statistical artefact. This study assesses Tunisia's ability to achieve its NDC3.0 objectives by explicitly distinguishing reductions in carbon intensity from actual declines in emissions within the context of sluggish growth. ARIMA time-series models project aggregate and sectoral greenhouse gas (GHG) emissions to 2030 under both GDP-normalised and per-capita indicators, and the results are interpreted through Tapio's decoupling framework. First, the GHG-to-GDP ratio achieves only 49% of the reduction required to meet the 45% target, while per-capita emissions remain 71% above the level consistent with the NDC pathway. Second, the sectoral analysis reveals heterogeneous dynamics: energy and agriculture exhibit moderate declines, whereas industry displays a marked divergence, in which a substantial reduction in emission intensity relative to GDP (−70.4%) coexists with a slight increase in per-capita emissions (+2%)—a pattern of recessive coupling indicating economic contraction rather than structural transformation. These findings challenge exclusive reliance on intensity-based indicators in climate policy evaluation. They call for multidimensional assessment frameworks that integrate emission levels, growth dynamics, and sectoral trajectories to evaluate the real feasibility of climate commitments and for climate finance scaled to sectoral shortfalls rather than to aggregate intensity targets.
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Copyright (c) 2026 Ibtissem Gannoun, Shaykhah Aldossari, Majdi Argoubi, Khaled Mili
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