Non-competitive Input-output Model Research Articles

Influencing mechanisms and decoupling effects of embodied carbon emissions: An analysis based on China's industrial sector

Carbon emission reduction in industrial sectors is an important link to achieve green sustainability development. In this paper, non-competitive input-output model and structural decomposition model are constructed for measuring embodied carbon emissions of 28 industrial sectors and their decomposition factor effects in China. Additionally, the decoupling state between embodied carbon and economic growth is explored using the decoupling model. On this basis, key industrial sectors' decoupling influencing factors are analyzed. The results show that the embodied carbon emissions from the industrial sector grow at an average annual rate of 7.743 % during 2005–2020. Investment demand and urban consumption are the primary sources of embodied carbon emissions, and demand size can also significantly drive carbon emissions. However, energy efficiency is crucial to reducing carbon emissions. According to embodied carbon flows and network centrality size, six key industry sectors were identified. The number of industrial sectors achieving strong decoupling increased significantly in 2005–2020, but the key industrial sectors were dominated by expansionary negative decoupling. Further analysis showed that energy efficiency contributed to the strong decoupling, whereas demand scale would inhibit decoupling more significantly. These findings are valuable for proposing targeted strategies to reduce emissions, improve industrial efficiency and resilience for sustainable development.

Structural path and decomposition analysis of sectoral carbon emission changes in China

With the “carbon neutrality” target proposal, China is facing severe pressure on carbon reduction. Industrial economic activities form an essential emission source of carbon dioxide. Therefore, it is necessary to promote industrial sectors’ coordinated emission reduction work. This paper uses non-competitive input-output model and structural path decomposition method to analyze the carbon emission changes from three levels of total, production layer and industrial chains, identifying the main paths and driving factors of carbon emission changes in China from 2017 to 2018. The results show that: (1) The first layer presents obvious low-carbon characteristics as a direct emission level, but the change in its carbon emissions accounted for 41.8%. (2) The increased emission of industrial chains is mainly caused by consumer spending and fixed capital formation, and emission reduction is mainly triggered by consumer spending. (3) Demand scale is an essential driving factor of carbon emission increase. The contribution rate of demand structure to emission increase and reduction industry chains is 55.1% and −16.5%, respectively, which is the biggest reason for the difference between them. Finally, targeted policy recommendations are put forward from the perspective of the emission transmission path and driving factors in the industrial chain.

Towards Cleaner Production Ecosystem: An Analysis of Embodied Industrial Pollution in International Trade of China’s Processing versus Normal Exports

While promoting economic growth, industrial development is causing serious environmental problems and threatening human health. Studies on pollution transfer through international trade often over-estimate the actual embodied emissions in exports and ignore the industrial pollutants. By designing a non-competitive input-output model which differentiates between processing exports and normal exports, we calculate the embodied domestic and imported industrial emissions in China’s processing and normal exports and imports. We also calculate the balance of embodied emission in trade (BEET) and the pollution terms of trade (PTT), as well as the decomposition of scale, structural, and technical effects on embodied emission in international trade. The results demonstrate that processing exports reduce domestic pollution by importing intermediate inputs; normal exports, on the other hand, have a considerable impact on domestic pollution. Bilateral trade between China and the US has the most detrimental impact on China’s local environment, followed by trade between China and Japan. China’s exports to Japan are more polluting per unit than those to the US and Germany. Technological upgradations and transformation of trade structure have helped to reduce the negative environmental consequences of China-US and China-Japan bilateral trade. Investment in technology and trade policy can lead to a cleaner production ecosystem.

Impact of Manufacturing Servitization on Factor Productivity of Industrial Sector Using Global Value Chain

The current study estimates the impact of manufacturing servitization on industrial productivity from the perspective of global value chain division. For this purpose, from 2000 to 2014, the study uses the World Input–Output Database (WIOD) to measure the servitization level of China’s manufacturing industry based on the non-competitive input–output model. Moreover, it develops a unified framework of source and structural differences in service factors and explores the mechanism and impact of manufacturing servitization on industrial productivity from the perspective of global value chain division. The results showed that if the division status of the manufacturing industry in the global value chain is higher, there will be a higher productivity effect of servitization. Regarding service factor country difference, foreign service factor input positively strengthened the industrial productivity effect, whereas domestic service factor input had no obvious effect on industry productivity. Furthermore, it was found that distribution and transportation services do not play a significant role in promoting industry productivity, whereas modern service factors such as information technology, finance, and business services have significant driving effects on industry productivity. The study suggests optimizing the layout of the industrial chain and improving the servitization of the manufacturing industry.

Analysis of energy efficiency in China’s export trade: A perspective based on the synergistic reduction of CO2 and SO[formula omitted

China has become the world’s largest energy consumer with its energy consumption growth accounts for three-quarters of the global growth. It is necessary to measure its energy efficiency reasonably. Previous studies mainly investigated energy use efficiency from the perspective of direct energy consumption without considering the energy consumption related to intermediate production, and did not eliminate the influence of random errors and environmental variables, resulting in deviations in energy efficiency measurement results. Combining a non-competitive input–output model and a three-stage data envelopment analysis, and based on the perspective of synergistic CO2 and SO2 emission reduction, this study constructs a new environmentally extended energy efficiency model to elucidate the true energy efficiency of China’s export trade. The results are as follows. (1) The implied energy efficiency of China’s export trade is generally on the rise under environmental constraints. Although its real efficiency in excluding external environmental factors has declined, its potential for improvement is still great. (2) Technological innovation and the expansion of export trade scale are conducive to the improvement of energy efficiency. Due to overcapacity, increasing industry capital investment will not greatly improve energy efficiency, but will increase the energy consumption and pollution emissions. (3) The average energy saving potential of China’s export trade is 8.91%, and the average emission reduction potential is 11.77%. (4) From 2002 to 2017, the average annual growth rate of implied energy efficiency in export trade was 8.9%, and technological progress was the main source of growth.

A Multi-Perspective Factorial-Analysis Based Non-Competitive Input-Output Model for Energy-Water Nexus in Kazakhstan

A Multi-Perspective Factorial-Analysis Based Non-Competitive Input-Output Model for Energy-Water Nexus in Kazakhstan

The contribution of ocean trade to national economic growth: A non-competitive input-output analysis in China

Measuring the contribution of ocean trade to national economy is crucial for marine economy policy. However, the contents of ocean trade are not well classified. This study first provides a clear classification of ocean trade which accounts for both ocean merchandise trade and service trade, and then quantifies the contribution of ocean trade to China’s GDP using the value-added content in trade instead of the gross value of trade. Employing China’s tripartite non-competitive input-output model which distinguishes China’s processing trade, this study enables us to take full consideration of China’s dual-trade regime. The results show that ocean trade has been an important driving force for China’s economic growth but its contribution is overestimated by the gross value of trade. Our study yields clear policy recommendations for promoting the sustainable development of China’s ocean economy.

Carbon emission efficiency of China’s industry sectors: From the perspective of embodied carbon emissions

Carbon emission efficiency directly determines the overall carbon emissions level. Previous studies mainly investigated carbon emission efficiency from the perspective of direct carbon emissions without considering carbon emissions associated with intermediate production and consumption, resulting in deviations in the measurement results of carbon emission efficiency. This study distinguishes the differences between direct carbon emissions and embodied carbon emissions, including intermediate production and consumption, and constructs a noncompetitive input-output model to measure the embodied carbon emissions from 28 industry sectors in China between 2005 and 2017. The super-efficiency slack-based measure model was used to analyze the carbon emission efficiency of 28 industry sectors in embodied carbon emissions and direct carbon emissions scenarios. The results are as follows. First, China’s embodied carbon emissions and direct carbon emissions are generally increasing, with large differences in the total amount, growth rate, and rate of change. Second, China’s overall efficiency of direct carbon emissions and embodied carbon emissions has improved. However, there was significant heterogeneity among various industry sectors. Third, in the 28 industry sectors, the change in embodied carbon emissions efficiency was generally gradual, while its average value was significantly lower than that of direct carbon emissions efficiency, indicating that indirect carbon emission efficiency is lower than direct carbon emissions efficiency. Fourth, the reduction potential of embodied carbon emissions for the 28 industry sectors was less than that of direct carbon emissions, although both have decreased, with a greater magnitude of decrease in the former. Finally, this paper proposes countermeasures to promote low-carbon development of China’s industries based on improving intermediate production technology and implementing dynamic supervision.

Analysis on Factors Driving Growth in China's Fishery Industry, Based on a Noncompetitive Input-Output Model

Qin, G.; Zhang, S.; Liu, X., and Cheng, B., 2019. Analysis on factors driving growth in China's fishery industry, based on a noncompetitive input-output model. In: Li, L.; Wan, X.; and Huang, X. (eds.), Recent Developments in Practices and Research on Coastal Regions: Transportation, Environment and Economy. Journal of Coastal Research, Special Issue No. 98, pp. 367–370. Coconut Creek (Florida), ISSN 0749-0208.Based on the input-output (IO) table data from 2002 to 2012, a noncompetitive IO model was used to calculate the factors driving growth and change in the final demand of China's fishery industry. The results show that the intermediate input, initial input, consumption, capital formation, export, and other final demands of the fishery industry all showed significant growth, and the added value increased first and then decreased. The role of consumption is the most outstanding, capital formation is second, and export is lowest, with a contribution rate of 66.22%, 20.51%, and 11.31%, respectively. Compared with final demand, the contribution rates of intermediate input and increased rate of gross domestic product growth by fisheries are relatively small, with the contribution of the value-added rate of only 8.63%, and intermediate input structure's contribution to growth of 6.67%. From 2002 to 2007, consumption contributed the most at 48.88%, followed by export, with its contribution rate being up to 21.91%. From 2007 to 2012, consumption contributed the most at 76.68%, capital formation contributed 22.20%, and export contributed 7.21%.

Inflationary and distributional effects of fossil energy price fluctuation on the Chinese economy

This study uses a non-competitive input-output model with monthly empirical data from January 2012 to November 2018 to evaluate the inflationary and distributional effects of fossil energy price fluctuation on the Chinese economy. Results show that the average monthly responses of consumer price index, producer price index, and gross domestic product deflator to fossil energy price change are 0.64%, 1.95%, and 1.46%, respectively. The inflationary pressures resulted from the price fluctuation of different energy types and sources are identified, which facilitates policymaking targeting different driving factors of inflation. Opposite progressivity is observed in terms of distributional effect measured by the expenditure changes of residents at different income levels, i.e., the coal price change leads to regressive impact while the crude oil price change leads to progressive one. Policy implications for China's energy market reform and energy tax design have been put forward based on the results of this study.

External Virtual Water Contributes Greatly to Continual Development in Urumqi

Previous studies indicated that the population size would arrive at its “upper limits” under the intense water scarcity in Urumqi; yet the “upper limits” had been repeatedly exceeded. Two latest research paper put forward a new term “generalized water”, and estimated it under the framework of a noncompetitive input-output model. It was proved that generalized water made a main contribution to alleviate acute water scarcity in the past 40 years in the arid city, and answered the question why an urban population continues to grow under intensifying water scarcity. Another question is whether and how generalized water contributes to the continual development in the future in this city. This paper applied coefficients deduced from the noncompetitive input-output model, and set up a multi-objective linear programming model to investigate the question. Simulation results indicated that the upper limit of gross domestic products of Urumqi would be at most 1.3 times that in 2012; however, this “upper limit” was far more exceeded in 2018, about 1.7 times that in 2012. This phenomenon indicates that generalized water also made a main contribution to continual development, and this contribution mainly comes from external virtual water embodied in commodities. This contribution from generalized water results from the characteristic of dissipative structure in an urban economy, and it is suggested that polices should be designed to make the most use of generalized water.

China’s fast growing CO2 emissions driven by increasing consumption in 1992-2012: A structural decomposition analysis

China is the largest carbon emitter worldwide and subsequently the greatest contributor to increments in global carbon emissions. Uncovering the driving forces behind China’s rapid CO2 emission growth can provide a theoretical basis for formulating scientific emission reduction policies, which are of great significance for mitigating global climate change. Based on an updated noncompetitive input-output model and structural decomposition analysis, the driving factors and their mechanisms of action for the rapid growth of China’s carbon emissions from 1992 to 2012 were explored in this study, with greater attention to the period 2007-2012. The main conclusions are as follows. (1) China’s carbon emissions increased by 7424.2 MtCO2 from 1992 to 2012. Particularly rapid growth of carbon emissions occurred during the periods 2002-2007 and 2007-2012, which respectively accounted for 43.33 % and 36.94% of the accumulated emission increments. (2) From 2007 to 2012, the growth of China’s carbon emissions was almost entirely driven by the expansion of the final demand scale, whereas the decline in carbon intensity dominantly mitigated carbon emissions. The effects of input-output structure and final demand structure also contributed to abating carbon emissions, with the relatively small contributions.

Double Measurement of Foreign Trade Comparative Advantage in Sino-US High-tech Industry Under Intra-product Specialization

Since China developed technology, its exports of high-tech products increased rapidly. Whether trade comparative advantage in China is reversal? Is export structure optimized? This paper measure the revealed comparative advantage (RCA) of technology of China and the U.S., and measure the export domestic added value comparative advantage (AVCA) based on non-competitive input-output model. The results show that China’s RCA has increased except special industries; the RCA exceed the U.S. in some technical industries; while the domestic value added coefficients are always less than American; compared with the U.S., RCA of different technologies after adjustments has decreased significantly in China

International Comparison Analysis of the Value Added Share of Imported Intermediate Goods: Based on Non-Competitive Input-Output Model

In this paper, we use the input-output model to calculate each sectors’ value added share of imported intermediate goods via eight representative countries’ input-output tables, to explore the relation between each sectors’ value added share of imported intermediate goods and the specialty industries of each countries. The analysis results show that there is a positive correlation among one country’s specialty industry and the value added share of imported intermediate goods of its upstream industry.

Optimizing China’s export structure combining goal programming and non-competitive input-output model

Based on a non-competitive input-output model capturing China’s processing exports, this paper establishes a goal programming model to optimize China’s export structure. In this model, China’s domestic production is divided into three parts: Production for domestic use, processing exports, and non-processing exports and production for other foreign invested enterprises. This division enables differentiation of the effects of various trade patterns, on the basis of which the authors conduct an empirical analysis using 2002 data, to obtain a Pareto optimality.

Inflationary effect of coal price change on the Chinese economy

This study investigates the pass-through effect induced by coal price fluctuations on the Chinese economy 2007–2011 based on a non-competitive input–output model. Three scenarios with different domestic tariff regulation alternatives, i.e., Actual Regulation (AR), No Regulation (NR), and Strong Regulation (SR), are simulated to reflect the effectiveness of different policies. At the sectoral scale, the Coking sector has the largest price variation under all scenarios while agriculture sectors and services sectors are the least sensitive. Nation-level impacts are examined by the weighted price changes of commodities used for different purposes. With the government regulation in reality, about 5% of the GDP deflator and CPI changes as well as 25% of the PPI change over the research period are attributed to coal price increase. Comparison shows the AR scenario brings more stable fluctuations but higher inflation than the NR scenario. The SR scenario confirms that authorities can remarkably relieve short-run inflation by controlling domestic electricity and heat tariffs. The induced inflationary expense sums up to between 0.03% and 0.97% of China’s GDP, around three quarters of which are burdened by investors and foreigners. The quantitative effect investigated in this study can serve as empirical evidence for policy makers regarding inflation control in China.

Does the Domestic Value Added Induced by China's Exports Really Belong to China?

AbstractSince 2001, the exports of foreign‐invested enterprises (FIEs) have accounted for more than 50 percent of China's total exports. As foreign capital occupies a high proportion of the total capital of FIEs, most FIEs' capital gains are foreign factor income. Although these gains are calculated as a part of China's GDP, they do not belong to China's national income. To determine the real contribution of exports to China's welfare, the present paper analyses the impact of exports on China's national income using a non‐competitive input–output model capturing processing trade. The results show that every US$1000 of China's exports generates US$506.8 of national income. The real contribution of exports to China's welfare is much smaller than what we expected. This suggests that China should endeavor to improve the gains from international markets or find another engine to maintain its economic growth.