This study develops an integrated 3E (energy–environment–economy) Dynamic Stochastic General Equilibrium (DSGE) model to evaluate how renewable-energy policies influence macroeconomic stability, environmental sustainability, and fiscal performance in a resource-rich developing economy. The model is calibrated to Iran’s structural features—capital scarcity, fossil-fuel dependence, investment inefficiency, and fiscal vulnerability— and validated through Bayesian estimation and variance decomposition. Five policy scenarios are examined: (i) renewable productivity shocks, (ii) carbon taxation, (iii) energy-mix adjustment, (iv) low-carbon technology adoption, and (v) energy-efficiency improvement with rebound effects. Results indicate that renewable productivity enhancement delivers the most balanced outcomes, promoting growth while reducing fossil dependence. Carbon taxation effectively cuts emissions but causes short-run output losses, whereas energymix adjustment without fiscal support generates adverse macroeconomic effects. Low-carbon technology adoption ensures sustained long-term gains, while non-renewable energy efficiency improvements reveal rebound mechanisms that offset part of emission reductions. By integrating fiscal feedbacks, Bayesian-based validation, and behavioral rebound dynamics, the study provides novel insights into the trade-offs shaping energy-transition policy in oil-dependent developing economies.

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