Testing climate NGFS scenarios through the lens of a large-scale ABM for the Italian economy

We apply a data-driven, macroeconomic agent-based model calibrated on the Italian economy to study the green transition – specifically, the shift in electricity production from fossil fuels (“brown” sources) to renewable (“green”) technologies – and the process of electrification, defined as the replacement of fossil fuel use with electricity. To better capture the dynamics of the energy sector, we extend the original macroeconomic model by expanding the energy sector into three subsectors, based on the Exiobase database, distinguishing between brown electricity, green electricity, and non-electricity energy sectors. We incorporate detailed information, particularly regarding carbon pricing and electrification, from three NGFS scenarios: Current Policies, Delayed Transition, and Net Zero. Based on these scenarios, we conduct a series of economic policy analyses. We find that a higher carbon tax leads to significant reductions in emissions while imposing only modest short-term economic costs on certain sectors, particularly those reliant on fossil fuels, along with a moderate increase in inflation. However, the green transition is associated with stronger long-run economic growth, primarily driven by increased investment in the renewable energy sector. Notably, when the carbon tax is combined with higher government consumption, the negative short-term effects on GDP are fully offset. Moreover, if the carbon tax is accompanied by green investment incentives, the resulting cost-push inflationary pressures can be partially mitigated. These findings highlight the potential of well-designed policy mixes to reconcile environmental objectives with sustained economic growth.