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The China's Input-Output tables for 2007 and 2012 which were published by the China National Bureau of Statistics are competitive current price input-output tables. Based on these tables, this paper constructs the China's non-competitive constant price input-output data for 2007 and 2012. This dataset is supplementary to Ref. [1]. And we share the...
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Citations
... Bagoulla and Guillotreau (2020) analyzed the impact of maritime transport in France on the domestic economy, providing a different perspective by assessing the environmental impact of shipping on direct and indirect gas emissions. Yu et al. (2019) constructed the China non-competitive constant price IO model comprising the transport and storage sector. Kwak et al. (2005) examined the status and economic impact of four maritime industries in Korea to present policymakers' relations of these sectoral industries with the rest of the national economy. ...
The aim of this paper was to determine the economic impact of the transportation sector on the Croatian economy by using input–output analysis. According to the input–output tables for the Croatian economy for 2004, 2010, 2013, and 2015, output and gross value-added multipliers were calculated. The results of the conducted analysis indicated that the multiplicative effects of the transportation sector in Croatia were significant in the observed period, especially for the air transport sector. Furthermore, comparative multiplier analysis with selected European Union countries was performed to assess the Croatian transportation industry position from an international perspective. Lower output and gross value-added multipliers for the Croatian transportation sector imply that old European Union member states capitalized the transportation sector more for growth and development. The Croatian transportation sector recorded lower imported intermediate inputs, average domestic inputs, and higher value-added multipliers similar to new European Union members. Simulations based on multiplicative effects show that restrictions on movements and human contacts, imposed due to the COVID-19 pandemic, could induce a strong reduction in the economic activity of transport and other sectors that are included in the value-added chain of the transport industry.
BACKGROUND AND OBJECTIVES: The stock market of a country can be considered as a network that consists of different sectors which are interconnected. Presently, many researchers try to build different types of networks by focusing on different aspects of the stock market and assessment the connections between various parts of the stock markets. One of the most important industries of the stock market is the insurance industry, which in addition to creating security and reducing effective risks, can be effective in increasing the production rate of industries and their profitability. The objective of this research is to assess the circumstances of the insurance industry in the Iranian stock market and its relationship with other industries. METHODS: In this research, a new approach was used to examine the position of the insurance industry in the stock market. In this way, firstly, one of the 36 selected industry networks of the Iranian economy, according to the active industries in the stock market, and based on their weight, in accordance with the 36 input-output table of the Iranian economy (related to the year 2015 which was published in 2019) was determined. In the next step, the correlation network was determined between how the stock market index of these 36 industries corresponded to 243 trading days per year, using the centrality criteria of the insurance industry. FINDINGS: According to the results obtained from the analysis of the first network, the first to third ranks of the insurance industry did not achieve any of the centrality indicators. Based on these results, the telecommunications industry has had the greatest impact on the insurance industry, and the transportation industry has also had the greatest impact on the insurance industry. Based on the results obtained from the second network survey, the insurance industry stock market index, in terms of degree, closeness and special vector, won the first rank and had the highest correlation with the pharmaceutical industry stock market index. CONCLUSION: The insurance industry is not considered a key node in the first network. The reason for that is the very small share of the added value of this industry in the country's gross domestic product. The results of the evaluations carried out of in this research show that telecommunications industry has the greatest impact on the insurance industry due to the creation of an information transmission infrastructure for insurance. The transportation industry's use of various insurance coverages makes the industry take the most influence from the insurance industry. In the second network, the stock market index of the insurance industry is considered as a key node and has the highest correlation with the stock market index of the pharmaceutical industry. This shows that in the period of research, the behavior of the stock market index of these two groups have shown a great similarity to each other. T The results of this research will be usable and useful for both policy makers and shareholders of the insurance industry, The most important application of the results of this research is that policymakers pay more attention to the consequences of mandated policies in a specific and key industry, and to be aware that wrong decisions in one sector can have many consequences for all economic sectors. Therefore, the officials in the regulatory departments, as soon as they see a crisis in a key economic sector, should immediately take appropriate decisions to prevent the spread of the crisis among other industries of the stock market.
In today's world, the interconnected structures of modern economies have caused the crisis to spread from one sector or country to other countries or sectors of the economy. Empirical evidence has shown that markets are interconnected and do not move apart. In the present study, a new approach is presented to investigate the contagion effect in Iran stock market. First, with the economic analysis, a network of 36 selected industries of Iran's economy is formed in accordance with the industries active in the stock market and the weight of the edges that connect them is determined according to the input- output table of Iran. In the next step, a correlation network is formed between the stock market indices of these 36 industries by using centrality criteria, Key industries are identified and then attacked. Comparison of the results of the two networks show that only in a limited number of cases in both networks, the basic metals industry, the banking industry, investment and other financial intermediaries, and the agricultural industry have won first place in accordance with a number of centrality criteria. But in other cases, the two networks have not the same results, which shows that economic relations among industries do not dominate their stock market index relations alone. The results of this study help both policymakers and shareholders to make appropriate decisions as soon as they see a crisis in important industries of the stock market.
One of the small and young industries in the stock market is the tourism industry, which includes several companies, including the Cultural Heritage Investment Group. This group is known as one of the smallest groups in the stock market in terms of market value. In the present study, in order to investigate the position of the tourism industry in the Iran stock market, two networks are considered by using the theory of complex networks. First, with the approach of economic and fundamental analysis, a network of 36 selected industries of Iran economy is formed in accordance with the industries active in the stock market. In the next step, with the approach of technical analysis, a correlation network is formed among the stock market indices of these 36 industries. According to the results of the Fundamental Analysis Network, the food industry has the greatest impact on the tourism industry because of the supply of food for hotels and restaurants. The industrial contracting industry is the most affected by the tourism industry because of the impact of tourism development on building contracting activities such as the restoration of historic buildings. According to the results obtained from the technical analysis network, the stock market index of the tourism industry has the highest correlation with the stock market index of the printing and publishing industry. The results of this study can be used for policy makers and stock market shareholders in the tourism group to make appropriate decisions by observing any changes in key points of the stock market.
Population aging is an important concern not only in China but also to many developed countries, and it will be a more serious issue throughout the world in the future. From this point, understanding the impact of population aging on CO2 emissions is important for achieving carbon neutral in the future. To analyze this impact, this study quantifies lifestyle and urban household's consumption impacts upon carbon emissions from the indirect CO2 emissions aspect and uses the structural decomposition method to analyze the factors influencing the growth of indirect CO2 emissions from 2007 to 2012. The analysis results indicate that the indirect CO2 emissions peak at 20s age group and gradually decline as age increases. Since elderly households have relatively lower indirect CO2 emissions, population aging in the future will reduce indirect CO2 emissions. The decomposition analysis for indirect CO2 emissions shows that the effects of changes in consumption pattern and production technology progress reduced indirect CO2 emissions to a large extent. The main factors leading to the increase in indirect CO2 emissions are the increase in the number of households and consumption volume. The corresponding policy implications are proposed based on our findings: improving energy efficiency in older households, promoting energy conservation promotion among younger households, and cultivating consumers’ green-consumption awareness.
