乌鲁木齐土地利用碳排放强度时空演变研究

[目的]土地利用二氧化碳排放强度是土地低碳利用的重要指标,对其时空调控是协同促进城市二氧化碳排放总量达峰的重要路径。[方法]文章研究基于乌鲁木齐市2005年和2012年1km高空间分辨率排放网格数据(CHRED)和土地利用矢量数据,采用GIS空间分析法,探讨乌鲁木齐市7个城区土地利用二氧化碳排放强度的时空演变特征。[结果](1)从时间上看,乌鲁木齐市7个城区的土地利用变化整体表现为"5增2减"的现象;二氧化碳排放总量从3 431.49万t上升到5 147.96万t,其中以城镇村及工矿用地二氧化碳排放增长最大,由2005年的2 885.15万t增加到2012年的4 139.15万t。(2)从空间上来看,城市向北部和东南部扩展明显,未利用地和耕地迅速减少,城市扩展区的二氧化碳排放量有明显增加;中心城区和城市扩展区二氧化碳排放强度上升最快。(3)从土地利用转移上看,土地利用结构的变化明显,整体呈现草地、耕地和未利用地向城镇村及工矿用地、交通用地、园林地和水域等类型转移。草地、耕地和未利用地向城镇村及工矿用地转移导致的碳排放强度增长最显著,均超过700万t/万hm~2。[结论]绿洲城市不同的土地利用类型二氧化碳排放强度时空差异较为显著,其中城镇村及工矿用地扩张是导致二氧化碳排放增长的主要原因之一。因此,合理控制绿洲城市扩张规模,优化城市用地布局,建立土地利用二氧化碳排放强度核算体系与综合调控政策,将是促进低碳城市建设的重要路径。     

Estimating input-mix efficiency in a parametric framework: application to state-level agricultural data for the United States

ABSTRACT

This paper contributes to the productivity literature by demonstrating novel econometric methods to estimate input-mix efficiency (IME) in a parametric framework. Input-mix efficiency is defined as the potential improvement in productivity with change in input mix. Any change in input-mix (e.g., land to labou r ratio) will result in change in productivity. The advantage of this approach is that it does not require data on input prices to estimate the mix efficiency levels. A nonlinear input-aggregator function (e.g., Constant Elasticity of Substitution) is used to derive an expression for input-mix efficiency. Bayesian stochastic frontier is estimated for obtaining mix efficiency using US state-level agricultural data for the period 1960–2004. Significant variation in input-mix efficiency is noted across the states and regions, attributable to diverse topographic and geographic conditions. Furthermore, comparisons of allocative and mix efficiencies provide insightful policy implications. The production incentives such as taxes and subsidies could help farmers in adjusting their input mix in response to changes in input prices, which can affect the US agricultural productivity significantly. The proposed methodology can be extended by i) using flexible functional forms; ii) introducing various time- and region-varying input aggregators; and iii) defining more sophisticated weights for input aggregators.     

Productivity Dispersion and Measurement Error

Several reasons have been put forward to explain the high dispersion of productivity across establishments: quality of management, different input usage and market distortions, to name but a few. Although it is acknowledged that a sizable portion of productivity dispersion may also be due to measurement error, little research has been devoted to identifying how much they contribute. We outline a novel procedure for identifying the role of measurement error in explaining the empirical dispersion of productivity across establishments. The starting point of our framework is the errors-in-variable model consisting of a measurement equation and a structural equation for latent productivity. We estimate the variance of the measurement error and subsequently estimate the variance of the latent productivity variable, which is not contaminated by measurement error. Using Norwegian data on the manufacture of food products, we find that about one percent of the measured dispersion stems from measurement error.     

How to reduce energy intensity to achieve sustainable development of China's transport sector? A cross-regional comparison analysis

China's transport sector has been attracting great attention for its excessive energy consumption and ever-increasing pollution emissions. Thus, reducing energy intensity is one of the top priorities of China's ongoing transport upgrade. In this paper, by establishing a panel data regression model derived from the Cobb–Douglas cost function, we focus on investigating the impacts of energy price and transport productivity on transport energy intensity at the national and regional levels. The study uses the provincial panel data for 2005–2016 to perform regression analysis. The results show that: (1) energy price has a significantly negative effect on transport energy intensity in the whole China and the eastern region, whereas it has no significant impacts in the central and western China. (2) Improvements in transport productivity can effectively decrease transport energy intensity in the whole China and the three major regions. (3) Applying an extended data envelopment analysis (DEA) approach, we decompose transport productivity into four components (i.e., technical change, technology gap change, scale efficiency change, and pure efficiency change) and further differentiate their impacts in different regions. The results indicate that these four components have substantially different impacts in each region. These results provide some valuable insights for policymakers and enterprise entities aiming to adopt measures to reduce energy intensity and achieve sustainable development in China's transport sector.     

农地权益保障与农业转移人口市民化

研究目的：明晰农地权益对农业转移人口市民化的影响，进而揭示当前全国各地对农业转移人口农地权益保护状况。研究方法：基于Probit模型的实证分析。研究结果：（1）从全国范围来看，农业转移人口的农地权益只得到部分保障；（2）农地权益保障状况存在较大的地区差异，区域经济越发达，农地权益保障越完善；（3）农地权益只得到部分保障对推动农业转移人口向城市迁移起着促进作用，但却对农业转移人口市民化有着显著负面影响。研究结论：农地权益保障是农业转移人口市民化的重要影响因素，农地权益的不充分保障对农业转移人口市民化具有负面影响，而经济越不发达的地区这种影响越显著。     

我国碳排放交易会计问题研究

从碳排放交易所涉及重点排放企业的角度出发,通过分析我国碳排放交易市场的现状,借鉴相关的研究与规范,就碳排放配额的会计确认问题、碳排放权交易的会计处理问题、企业碳排放相关的会计信息披露问题进行研究分析,提出了碳排放交易的会计处理的意见和建议。     

低碳视角下多式联运经济性能实例分析--以郑明物流为例

为了进一步研究铁路运输与其他运输方式开展多式联运的经济性能,在阐述多种运输方式性能差异的基础上,以郑明物流为例,通过分析其特定运输路线现有运输方式的能源消耗、碳排放量和运输过路费等指标,提出在不同月份和不同时期的多式联运优化方案,为物流企业开展多式联运提供借鉴。