减少砍伐和退化造成的排放机制（REDD+）影响毁林行为的传导路径及权利平等性研究

Reducing Emissions from Deforestation and Forest Degradation - plus (REDD+) mechanism as the most feasible emission reduction measure that can help China reduce carbon emission at a lower cost. Since REDD+ mechanism was born shortly, there is fewer systematic research for REDD+ mechanism. Therefore, it will be difficult to find theoretical foundation and empirical basis for relivant macro policy formulation. Firstly, the project will establish emmision scenatios which are based on Improved WITCH Model, and the impact on REDD+ mechanism to mitigate climate change for China will be analyzed. Secongdly, the conduction path of REDD+ to deforestation palliation will be analyzed through the framework of Deforest EKC. The agent-based modeling (ABM) is suggested to model the conduction path by simulating the REDD+ trading. Thirdly, the evaluation index system for right equality of REDD+ will established from four levels of participation, economic benefits and non-economic benefits, and institutional, and the right equity of REDD+ can be evaluated by the right equity appraisal matrix (REAM).Finally, because the error between the observed values and structure values can be estimated by econometric model, the policy assessment model for REDD+ mechanism which is based on structural variables can be established. We can use the model to evaluate the policy effectiveness in China's pre-REDD+ era.The project is expected to supply new methods and theoretical basis for the research on impact analysis and policy assessment of REDD + mechanism, and scientific basis for developing the REDD+ mechanism suitable for China's national conditions.

减少砍伐和退化造成的排放（REDD+）机制作为目前最可行减排措施，可帮助中国以较低成本减少碳排放。因REDD+机制诞生不久，目前国内针对REDD+系统化研究较少，导致相关宏观政策制定缺乏理论基础和实证依据。本课题基于改进型WITCH模型建立排放情景，分析REDD+机制对中国减缓气候变化的影响；在毁林EKC曲线框架下分析REDD+影响毁林行为的传导路径，并建立基于Agent模型的REDD+交易仿真模型来仿真模拟这一传导路径；从参与性、经济收益、非经济收益和制度四个层面构建REDD+权利平等性评价指标体系，通过构建REDD+权利平等性矩阵来研究REDD+的权利平等性问题；通过计量模型估计观测值与结构值间的误差项，建立基于结构变量的REDD+政策效果评价模型并对中国进行评价。本课题有望为REDD+的影响分析和政策评价提供新的方法和理论基础，为我国制定适合于国情的REDD+机制提供科学的参考依据。

由砍伐和退化所致排放已成全球变暖第二大主因，因而减少森林砍伐和退化所致排放(REDD+)项目得以广泛实施。由于信息、补贴和不确定性等驱动因素影响，REDD+项目绩效差异显著；同时因各区域社会经济和生态环境存在多样性，REDD+项目绩效的驱动因素表现出空间异质性。本项目构建了反映信息、参考水平与项目绩效之间关系的多任务委托-代理模型，探索最优参考水平设定方法；通过构建含开发商和代理人的动态博弈模型，系统揭示补贴影响REDD+项目绩效的作用机理；通过加入不确定性变量改进动态博弈模型，优化不确定性估计方法的适用性；识别中国REDD+项目绩效的潜在驱动因素和环境变量，建立地理加权回归模型对关键驱动因素的空间异质性进行分析。项目研究成果不仅可从驱动因素角度，为不同区域REDD+项目的差异化绩效改进政策制定提供依据，推进生态文明建设；而且有助于加深对REDD+项目绩效驱动机制的理解，推动相关学科发展。