Integrating policy design with agricultural emissions reduction in China: A multi-sector DSGE Approach

China’s agricultural sector is pivotal to national emission reduction strategies, with policy design shaping the balance between environmental and food security objectives. This paper employs a multi-sector Dynamic Stochastic General Equilibrium model—integrating Input-Output tables and Social Accounting Matrices—to simulate the effects of distinct emission reduction policies and their implementation pathways on agricultural output and emissions. Utilizing solution techniques such as perfect foresight, stochastic simulations, and rational expectation extended path, the analysis captures inter-sectoral spillovers and agents' forward-looking behaviors shaped by varying degrees of expectations and uncertainties. The results demonstrate that regulatory tools, such as emission taxes with agricultural exemptions, achieve substantial emissions reductions but at the cost of lower agricultural output. Incentive-based subsidies, by promoting low-carbon technology adoption, yield the most balanced long-term gains in both emissions mitigation and growth, while market-based emissions trading schemes, though flexible, often delay abatement initiatives and underperform in both respects. Policy transparency and stability are found to significantly enhance effectiveness, reducing volatility and supporting sustained improvements. Combinations of regulatory, incentive, and market-based instruments are shown to best reconcile growth with emissions reductions, highlighting the value of coordinated and predictable policy frameworks for agricultural decarbonization.