中国出口隐含碳排放影响因素研究——基于反事实法的分析

中间消耗的"消耗规模与部门构成"是影响中国出口碳排放的重要因素。基于世界投入产出数据库(WIOD)1995—2015年数据,在部门归类与形式变换基础上,本文选取"单位产出碳排放量"、"完全消耗系数"与"出口值"为中国出口隐含碳排放的影响因子,构建"因子变动—反事实构造—效果评价"分析框架,借助规模指数与结构指数对影响因子的变化动态进行描述,并通过反事实构造对"因子变动"的影响效果进行评价。研究发现:"单位产出碳排放量"规模指数单调递减,Spearman偏度系数为右偏态,说明相比于意愿产出而言,非意愿产出"碳排放量"具有内在的规模不经济;"中间消耗"规模指数与碳偏向性指数在截面上始终处于高位水平,时序上出现了显著的递增趋势,说明中国单位出口值的中间消耗量偏大,消耗投入在结构上偏向于高碳部门,与"技术前沿国"美国存在显著"技术差距";"出口值"规模指数呈现"平缓扩张——快速攀升——V型震荡"的阶段性特征,结构指数经历了以基期2002年为顶点、"先下降、后上升、再平稳"的变化轨迹,说明"出口值"作为最具弹性的影响因子,受"亚洲金融危机"、"加入世界贸易组织"与"美国次债危机"等外部冲击的影响明显,对出口碳排放的推动作用存在伸缩性与阶段性差异。从"因子变动"影响效果来看,中国产出、中间消耗与出口的部门构成具有内生关联,均显著偏向于高碳部门,对出口隐含碳排放增长产生了叠加性的"正向"扩张效应。基于此,本文认为,总量控制与结构优化的视角需从产品环节向中间消耗环节扩展,现阶段应深化要素市场改革,加速要素禀赋升级,借力要素价格机制与差别化产业规制政策,从上游环节抑制出口碳排放的输入来源。     

道路交通安全反事实仿真评估技术综述与展望

为理清道路交通安全反事实仿真发展脉络,进一步推动反事实仿真技术的应用,从反事实仿真技术基本原理出发,梳理反事实仿真5个阶段,比较事故场景与自然驾驶场景的差异,讨论仿真模型在驾驶人避险行为、路面条件、事故损伤与事故风险结合等方面的不足,归纳、对比仿真过程、评估指标技术要点;并在分析反事实仿真技术适用性的基础上,归纳该技术的发展趋势。结果表明:驾驶员因素的不确定性限制了反事实仿真的应用领域,目前该技术更适于碰撞、避险阶段的交通安全评价与分析。     

The difference conservation makes to extinction risk of the world's ungulates

Previous studies show that conservation actions have prevented extinctions, recovered populations, and reduced declining trends in global biodiversity. However, all studies to date have substantially underestimated the difference conservation action makes because they failed to account fully for what would have happened in the absence thereof. We undertook a scenario‐based thought experiment to better quantify the effect conservation actions have had on the extinction risk of the world's 235 recognized ungulate species. We did so by comparing species’ observed conservation status in 2008 with their estimated status under counterfactual scenarios in which conservation efforts ceased in 1996. We estimated that without conservation at least 148 species would have deteriorated by one International Union for Conservation of Nature (IUCN) Red List category, including 6 species that now would be listed as extinct or extinct in the wild. The overall decline in the conservation status of ungulates would have been nearly 8 times worse than observed. This trend would have been greater still if not for conservation on private lands. While some species have benefited from highly targeted interventions, such as reintroduction, most benefited collaterally from conservation such as habitat protection. We found that the difference conservation action makes to the conservation status of the world's ungulate species is likely to be higher than previously estimated. Increased, and sustained, investment could help achieve further improvements.     

基于消费者购车决策的购置税、燃油税节能减排效应分析

本文基于中国乘用车市场车型层面微观数据,采用前沿的需求模型估计方法,通过反事实分析,实证模拟了燃油税与购置税税率变动作用于消费者购车决策的价格收入效应与替代效应,进而从需求侧探究购置税与燃油税实现节能减排的微观经济学机制,兼论环境税对企业和社会总福利的影响。结论表明：燃油税具有显著的价格变动收入效应,即促使更多消费者放弃驾车出行模式,购置税具有显著的价格变动替代效应,即促使消费者选择购买小排量车型。在这样的机制下,组合税对需求的影响更多地取决于购置税,即购置税的价格替代效应超过燃油税的价格收入效应。这使得组合税在样本期并未实现总量上的节能减排,但税收组合政策使得中国乘用车市场车型平均油耗降低。从时间趋势来看,燃油税节能减排效应具有时间稳定性,购置税减排效果具有很大的波动性。从税制福利效应来看,组合税制的税收效应更多地向消费者市场转移。总的来看,燃油税与购置税的组合税政策并未实现“1+1＞ 2”的效应,未来减排工作的核心应在于通过调整和匹配税率,以实现组合税最优的政策效果。     

电商参与促进农户绿色生产吗？

农业绿色生产是保障中国农产品质量安全、缓解生态环境恶化问题的根本路径。虽然学术界对影响农户绿色生产行为的因素进行了较为丰富的研究,但人们对农产品电商与果农绿色生产之间的关系知之甚少。因此,文章深入探讨了电商参与和果农绿色生产行为的关系及其影响机制,并基于三省四县812份实地调研的农户数据,运用RBP模型进行实证检验,然后对结果的稳健性与异质性展开探讨。研究发现：①电商参与能够提高果农绿色生产的实施概率,处理组平均处理效应为24.7%,通过更换模型和替换解释变量等一系列方法进行稳健性讨论后,上述基准结论稳健可靠。②电商参与对不同绿色生产行为的处理效应存在差异,按照ATT数值由大到小依次为：严格按照标准施药、物理防控措施、生物防控措施。③电商参与能够通过提升绿色生产认知、提高农产品价格预期和追求消费者正向口碑影响果农实施绿色生产行为。因此,应加大农产品电商宣传与推广力度,提高果农电商参与程度;与此同时,应确保农产品电商在通过实施绿色生产提升农产品质量并获得质量溢价方面的有效性,进而促进电商参与率与绿色生产实施率协同提高。此外,应强化政府在果农绿色生产上的引导作用。     

Cause-effect relationships in analytical surveys: an illustration of statistical issues

Establishing cause-effect is critical in the field of natural resources where one may want to know the impact of management practices, wildfires, drought, etc. on water quality and quantity, wildlife, growth and survival of desirable trees for timber production, etc. Yet, key obstacles exist when trying to establish cause-effect in such contexts. Issues involved with identifying a causal hypothesis, and conditions needed to estimate a causal effect or to establish cause-effect are considered. Ideally one conducts an experiment and follows with a survey, or vice versa. In an experiment, the population of inference may be quite limited and in surveys, the probability distribution of treatment assignments is generally unknown and, if not accounted for, can cause serious errors when estimating causal effects. The latter is illustrated in simulation experiments of artificially generated forest populations using annual plot mortality as the response, drought as the cause, and age as a covariate that is correlated with mortality. We also consider the role of a vague unobservable covariate such as `drought susceptibility'. Recommendations are made designed to maximize the possibility of identifying cause-effect relationships in large-scale natural resources surveys.