Maritime carbon tax's impact on China's shipping industry: economy and carbon reduction.

Existing studies on maritime carbon taxation rely on static or homogeneous-firm models, failing to capture industry heterogeneity and dynamic policy responses. We constructed a four-sector Dynamic Stochastic General Equilibrium (DSGE) model, explicitly distinguishing between pollution-intensive and clean shipping companies, and calibrated it to the actual characteristics of China's shipping industry. We explored the dynamic transmission mechanism of shocks from carbon tax and green technology through scenario simulations, while using a Time-Varying Parameter-Stochastic Volatility-Vector Autoregression (TVP-SV-VAR) model to complement the results for robustness. The findings show that the maritime carbon tax exhibits significant asymmetric effects: in the short term, it raises corporate costs and suppresses industry output, with a more pronounced impact on high-pollution enterprises; while in the long term, it can effectively drive the adoption of green technologies and optimize the energy structure, significantly reducing industry carbon emissions while promoting investment and employment growth. The study also identifies a reasonable trade-off between economic development and carbon reduction. A moderately intensive and differentiated carbon tax policy can balance short-term economic costs with long-term low-carbon benefits, providing a scientific basis for the low-carbon transformation of China's shipping industry.