中国主要工业省区能源效率分析：1990～2006年

本文基于DEA方法,计算了中国13个主要工业省区1990～2006年的能源效率。结果显示,13个省区的能源效率差异较大。比较几个模型,我们发现能源的相对定价并没有为节约能源提供合适的激励。两阶段估计结果表明,技术进步和工业内部结构是影响能源效率的重要因素。此结论的政策含义是,为了节能减排,这些工业省区需要:(1)吸引外资和技术,推进自主创新,加快技术进步;(2)改变重型化的工业结构,促使工业结构优化升级;(3)适当提高能源的使用成本。     

ECONOMIC IMPLICATIONS OF POLICY RESTRICTIONS ON WATER WITHDRAWALS FROM SURFACE AND UNDERGROUND SOURCES

The appropriation of water for economic activities is limited by regional surface and underground endowments, and symptoms of environmentally unsustainable withdrawals are already visible in many regions of the world. In this paper we investigate the economic implications of water policy imposing source- and region-specific restrictions on water withdrawals taking the Mexican economy as a case study. We use an inter-regional input–output model of Mexico's hydro-economic regions to allocate production subject to the availability of water and other factors of production. Water sustainability requires a reduction of 7.5?km³/yr of groundwater withdrawals, which is compensated by an increase of 3.4?km³/yr of surface water, an expansion onto an additional 1.4 million hectares of rainfed land, and modifications in subnational patterns of food trade. This framework for evaluating scenarios describing sustainability-oriented water policies is readily applicable to other regions.     

Updating Input–Output Tables with Benchmark Table Series

Numerous methods have been proposed to update input–output (I–O) tables. They rely on the assumption that the economic structure will not change significantly during the interpolation period. However, this assumption may not always hold, particularly for countries experiencing rapid development. This study attempts to combine forecasting with a matrix transformation technique (MTT) to provide a new perspective on updating I–O tables. Under the assumption that changes in the trend of an economic structure are statistically significant, the method extrapolates I–O tables by combining time series models with an MTT and proceeds with only the total value added during the target years. A simulation study and empirical analysis are conducted to compare the forecasting performance of the MTT to the Generalized RAS (GRAS) and Kuroda methods. The results show that the comprehensive performance of the MTT is better than the performance of the GRAS and Kuroda methods, as measured by the Standardized Total Percentage Error, Theil's U and Mean Absolute Percentage Error indices.     

土壤温度对大豆产量的影响试验研究

通过对大豆进行盆栽试验,来研究不同土壤温度对大豆各发育阶段及其产量的影响,从中找出提高土壤温度与大豆产量的关系,从而对充分利用气候资源提高大豆产量有着重要的指导作用。     

An input–output virtual laboratory in practice – survey of uptake,usage and applications of the first operational IELab

ABSTRACT

The Industrial Ecology Virtual Laboratory (IELab) is a collaborative cloud-computing platform for compiling large-scale, high-resolution, enviro-socio-economic accounts based on multi-region input–output tables and for conducting integrated sustainability assessment projects. These include, for example, assessments of biofuels and low-carbon construction materials or high-resolution waste modelling. This contribution provides a structured review of IELab applications that were published in either peer-reviewed journal papers or in the form of conference proceedings. The main research question posed is ‘What are the specific features of IELab that were used in the research and could the research have happened without them?’ It is investigated whether the IELab has actually and truly enabled new research. A detailed analysis of IELab characteristics and their usage is presented. The results can help with the design of new research projects and inform existing and prospective users of the IELab about the options for academic research and practical applications.     

Improving footprint calculations of small open economies: combining local with multi-regional input–output tables

In a small, open and resource-poor economy, import and export dependency have an ever-growing impact on local policy decisions, which makes local (environmental) policy-makers increasingly depend on global data. This increases the interest in models that link local production and consumption data to global production, trade and environmental data. The recent increase in availability of global environmentally extended multi-regional input-output tables (EE-MRIO tables) provides an opportunity to link them with existing local environmentally extended input-output tables (EE-RIO tables). These combined tables make it possible (1) to analyse the links between local and global production and consumption and (2) to study global value chains, material use and environmental impacts simultaneously. However, estimations using input-output (I–O) analyses contain errors due to imperfect databases. In this article the magnitude of specification, aggregation and time errors are estimated and compared. The results show the need to combine local datasets with multi-regional ones and show that highest detailed (country and sector levels) as well as time series of I–O tables are the way forward for using I–O analyses in local policy-making. The paper provides guidance on trading off investments in model adoption and/or extension and the reliability of estimation results.     

Measuring China’s domestic production networks through Trade in Value-added perspectives

Evaluating the role and performance of China's participation in Global value chains (GVCs) has been a hot policy and research issue in recent years. However, most GVCs-related literature about China focuses on country-to-country relations; less attention has been paid to China's domestic value chains (DVCs). GVCs should have their domestic foundations since strong linkages across domestic firms and regions can improve productivity through gains from specialization, which make domestic industries more competitive in GVCs in turn. This paper applies the so-called Trade in Value-added (TiVA) concept and the decomposition of domestic-regional trade in TiVA terms to re-measure the inter-industrial and interregional linkages in China's DVCs. We show that TiVA-based measures can significantly enrich our understanding on both the structure change of China's regional economy and the position and participation degree of Chinese regions in DVCs.     

省际间政府教育投入努力度的差异性研究

通过设定指标、建立模型,对1997年-2006年我国省际间政府教育投入的努力程度的差异性进行实证分析。结论与启示是：除经济发展水平外,其他影响因素会对政府教育投入产生影响,政策支持仍不失为一种有效的措施;我国政府教育投入努力度呈现区域差异,是与我国教育财政政策的区域倾向密切相关的,但这种差异难以弥补教育发展的区域差异,因此对于西部和中部地区,我国教育财政政策的支持力度还有待于进一步加大。     

Key Sectors,Industrial Clustering and Multivariate Outliers

In this paper a reflection is made on the problems that can arise in key sector analysis and industrial clustering, due to the usual presence of outliers when using multidimensional data related to the sectors in an input–output table. Multidimensional outliers are considered as being not only linked to the low number of clusters usually observed in this kind of study, but probably causing invalid results in most of the works involving multivariate statistical techniques, such as cluster and factor analysis. Actually, by comparing the key sectors of the Spanish economy obtained in Díaz et al. (2006) Díaz, B., Moniche, L. and Morillas, A. 2006. A fuzzy clustering approach to the key sectors of the Spanish economy. Economic Systems Research, 18: 299–318. [Taylor & Francis Online] [Google Scholar] to the ones we get taking into account the problem the outliers pose, one can realize they greatly distort the results. On the other hand, it is shown that identification of outliers can be considered as a good and new procedure to help select the most important sectors in an economy.     

方法、数据与全要素生产率测算差异

研究目标：检验不同方法之间TFP测算结果的“一致性”和“稳健性”,探讨测算方法和数据选取问题。研究方法：以中国2004~2012年总量分行业面板数据为例,从多个角度比较TFP测算结果,以及通过统计检验选取适用测算方法。研究发现：第一,研究的问题不同,测算方法之间“一致性”的检验结论不同;第二,在选择测算方法时,进行相关统计量检验是必要的,这有助于鉴别模型设定是否合理,缩小可选模型范围;第三,测算方法的选择,要符合数据本身的特征,基于宏观分行业面板数据,DEA是更为适用的TFP测算方法,而劳动力投入应选取全社会从业人员指标。研究创新：多种测算方法和统计检验的应用。研究价值：本文尝试构建如何选择TFP测算方法的一般框架。