An extended input-output table for environmental and resources accounting

Environmentally Extended Input-Output(EEIO)tables have become a powerful element in supporting information-based environmental and economic policies.National-and provincial-level 10 tables are currently published by the National Bureau of Statistics of the People's Republic of China according to well-defined conventions.However,county-level 10tables are not provided as a rule by official statistics organizations.This paper conducts an overview of compiling EEIO tables for environmental and resources accounting at the county level and then answers several questions:First,what kind of data should be prepared for the compilation of county-level EEIO tables?Second,how can we set up comprehensive EEIO tables at the county level?Third,regarding the survey methods and the indirect modeling,which one should be chosen to build EEIO tables at the county level?Finally,what policy questions could such a table answer?EEIO tables at the county level can be used to predict the economic impacts of environmental policies and to perform trend and scenario analysis.

Measuring I/O-Production in Digital Economy

According to OECD standards(United Nations,2008),“productivity is commonly defined as a ratio of a volume measure of output to a volume measure of input use”.This ratio indicates how efficiently production inputs,such as labour and capital,are being used in an economy to produce a given level of outputs.Productivity stays aside the main aggregates of national accounts,as the national income(a proxy of GDP),the total output and the circulating capital.Assume the existence of a Leontief-type national Input-Output Table with the vector of total output and the vector of intermediate inputs,situated on its right and lower border.In this paper a measure of capital productivity is proposed.It is called the productiveness,and results from the solution of a boundary value problem,elaborated for Input-Output Tables,involving the vector of total output and the vector of intermediate inputs.

A process-level hierarchical structural decomposition analysis (SDA) of energy consumption in an integrated steel plant

A hierarchical structural decomposition analysis(SDA) model has been developed based on process-level input-output(I-O) tables to analyze the drivers of energy consumption changes in an integrated steel plant during 2011-2013. By combining the principle of hierarchical decomposition into D&L method, a hierarchical decomposition model for multilevel SDA is obtained. The developed hierarchical IO-SDA model would provide consistent results and need less computation effort compared with the traditional SDA model. The decomposition results of the steel plant suggest that the technology improvement and reduced steel final demand are two major reasons for declined total energy consumption. The technical improvements of blast furnaces, basic oxygen furnaces, the power plant and the by-products utilization level have contributed mostly in reducing energy consumption. A major retrofit of ancillary process units and solving fuel substitution problem in the sinter plant and blast furnace are important for further energy saving. Besides the empirical results, this work also discussed that why and how hierarchical SDA can be applied in a process-level decomposition analysis of aggregated indicators.

Parameterless Pruning Algorithms for Similarity-Weight Network and Its Application in Extracting the Backbone of Global Value Chain

Purpose:With the availability and utilization of Inter-Country Input-Output(ICIO)tables,it is possible to construct quantitative indices to assess its impact on the Global Value Chain(GVC).For the sake of visualization,ICIO networks with tremendous low-weight edges are too dense to show the substantial structure.These redundant edges,inevitably make the network data full of noise and eventually exert negative effects on Social Network Analysis(SNA).In this case,we need a method to filter such edges and obtain a sparser network with only the meaningful connections.Design/methodology/approach:In this paper,we propose two parameterless pruning algorithms from the global and local perspectives respectively,then the performance of them is examined using the ICIO table from different databases.Findings:The Searching Paths(SP)method extracts the strongest association paths from the global perspective,while Filtering Edges(FE)method captures the key links according to the local weight ratio.The results show that the FE method can basically include the SP method and become the best solution for the ICIO networks.Research limitations:There are still two limitations in this research.One is that the computational complexity may increase rapidly while processing the large-scale networks,so the proposed method should be further improved.The other is that much more empirical networks should be introduced to testify the scientificity and practicability of our methodology.Practical implications:The network pruning methods we proposed will promote the analysis of the ICIO network,in terms of community detection,link prediction,and spatial econometrics,etc.Also,they can be applied to many other complex networks with similar characteristics.Originality/value:This paper improves the existing research from two aspects,namely,considering the heterogeneity of weights and avoiding the interference of parameters.Therefore,it provides a new idea for the research of network backbone extraction.

Evolution trends and structural decomposition of China's green value-added over 40 years of reform and opening-up

China's 40-year history of reform and opening-up includes rapid economic development as well as pollution and environmental governance.Using a four-stage division,this study explores the evolution trend and structural decomposition of China's green value-added by constructing a non-competitive input-output table for environmental pollution from 1978 to 2017.The results indicate that pollution production coefficients increased continuously,and the green value-added index decreased.Additionally,the structural decomposition showed that investment and export were critical for economic growth during the period,though they were accompanied by serious pollution problems.The pollution generated by the raw material(represented by coal mining)and processing industries(represented by the textiles)were not controlled effectively.Pollution treatment for these industries should be strengthened in the future.The study has implications for government officials,policy makers,and academics.First,China should make green development a core concept for economic development,increase environmental pollution governance,develop a“green GDP,”incorporate the external costs of environmental pollution into the national economic accounting system.Second,it must change the investment and export structure as well as the traditional economic development pattern that exacerbates pollution.Specifically,the country should develop industries with low pollution and promote the export of industries producing high value-added products and increase green GDP per capita.Third,it should closely monitor the development of highly polluting industries.Upgrading technology to reduce pollution and strengthening pollution treatment will reduce the number of polluting industries and improve environmental governance efficiency.

China's comparative advantage still in low-tech manufacturing sector

This paper represents an attempt to estimate the level of vertical specialization in China's manufacturing industry using China's input-output tables (1995-2005) compiled by the OECD; describe the trends of evolution in the trade competitiveness of China's manufacturing industry using the 1995-2006 trade data of 24 Chinese industries; and examine the key factors affecting the trade competitiveness of China's manufacturing industry in accordance with the analytical framework of Hummels et al (2001). The estimation results indicate that i) the rapid increase in the vertical specialization levels of China's merchandise sectors (especially the high-tech manufacturing sector) has to some extent explained the explosive growth of China's exports (especially high-tech exports) in recent years; ii) there have been no substantive changes in China's comparative advantages. Such advantages are still attributed to the low-tech manufacturing sector. However, the comparative advantage and trade competitiveness of the high-tech manufacturing sector have been on the rise; iii) vertical specialization has signif icantly enhanced the trade competitiveness of China's manufacturing industry. Foreign market dependence, domestic intermediate input intensity and R&D intensity have an obvious promoting effect on the trade competitiveness of China's manufacturing industry.

Analysis of urban metabolic processes based on input-output method： model development and a case study for Beijing

Discovering ways in which to increase the sustainability of the metabolic processes involved in urbanization has become an urgent task for urban design and management in China. As cities are analogous to living organisms, the disorders of their metabolic processes can be regarded as the cause of ＂urban disease＂. Therefore, identification of these causes through metabolic process analysis and ecological element distribution through the urban ecosystem＇s compartments will be helpful. By using Beijing as an example, we have compiled monetary input- output tables from 1997, 2000, 2002, 2005, and 2007 and calculated the intensities of the embodied ecological elements to compile the corresponding implied physical input-output tables. We then divided Beijing＇s economy into 32 compartments and analyzed the direct and indirect ecological intensities embodied in the flows of ecological elements through urban metabolic processes. Based on the combination of input-output tables and ecological network analysis, the description of multiple ecological elements transferred among Beijing＇s industrial compartments and their distribution has been refined. This hybrid approach can provide a more scientific basis for management of urban resource flows. In addition, the data obtained from distribution characteristics of ecological elements may provide a basic data platform for exploring the metabolic mechanism of Beijing.

基于投入产出技术的全球生产网络时空格局演变及驱动因素分析

Global production networks have become the most important organizational platforms for coordinating international production activities,and their evolution patterns profoundly affect value distribution across the world.In this study,we shall firstly carry out an in-depth quantitative research to analyze the patterns and evolution of global production networks,using a long time-sequenced multi-region input-output table and the network analysis approach.Then based on the method of value-added decomposition,we will develop an index system to measure the degree of participation of regions in global production networks.Finally,we will try to identify the factors affecting the degree of participation of countries in global production networks by constructing a regression model.The results show that from 1995 to 2015,the evolution of global production networks measured by input-output linkages experienced four stages:expansion,contraction,re-expansion,and re-contraction.In addition,the core communities of global production networks evolved from two major production communities(Europe and the Americas)to three pillars(Europe,Americas,and Asia)while more segmented communities are mainly affected by geographical proximity.The latter consists of European,North American,South American,African and Asian communities.The evolution of the global production network pattern primarily manifests as a process of cooperation strengthening or weakening among communities,based on changes in the external environment and the need for individual development strategies.Meanwhile,the United States,Germany,and the United Kingdom have consistently ranked among the top entities in global production networks,whereas China,Russia,and Southeast Asia have the fastest rises in ranking.In addition,government efficiency,resources endowment,infrastructure conditions and technology levels play important roles in the participation in global production networks.

Value, Structure and Spatial Distribution of Interprovincial Trade in China

This study uses two different datasets to explore the stylized facts of interprovincial trade in China during the recent two decades. One dataset provides the magnitude of bilateral interprovincial goods trade calculated using firms ＇ value-added tax invoices. The other supplies estimates of interprovincial trade using provincial input-output tables. We find that China has both a large value and a high growth rate of interprovincial trade, but there still exists a home bias in internal trade for most provinces. In addition, disaggregation by product shows that the manufacturing sector has the largest share of interprovincial trade and this share continues to grow. Finally, the spatial distribution of trade suggests that all provinces can be clustered into a smaller number of trade areas with large intra-cluster trade. Therefore, China＇s central government should make more effort to reduce local protection, stimulate domestic demand and coordinate interregional trade among local jurisdictions.

价格测算模型解的存在性定理

价格测算模型解的存在性定理曹国钧，王健（重庆医药设计院６３００００）（渝州大学数学系）ＡＴｈｅｏｒｅｍｆｏｒＥｘｉｓｔｅｎｃｅｏｆｔｈｅＳｏｌｕｔｉｏｎｏｎＰｒｉｃｅＥｓｔｉｍａｔｅＭｏｄｅｌＣａｏＧｕｏｊｕｎＷａｎｇＪｉａｎ（ＣｈｏｎｇＱｉｎｇＰｈ...

Productivity Growth in the Chinese Economy by Industry and the Role of Foreign Capital

The purpose of this paper is to estimate total factor productivity （TFP） growth in China by industry. As well as reviewing some previous studies on TFP growth in China, the authors present their estimation of TFP growth in China for two periods, 1987-1992 and 1992-1997. During both periods, output growth was as high as double digits. However, the differences in TFP growth between these two periods were remarkable. In the first period, wide-ranging TFP growth was observed, whereas in the latter period, high TFP growth was concentrated in industries such as ＂transportation equipment＂ and ＂electric machinery＂, which are known for actively introducing foreign capital and technologies. In fact, positive relations were confirmed among TFP growth, export performance, and the introduction of foreign capital. Foreign capital made a large contribution to China＇s exportled growth.