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25 June 2020, Volume 0 Issue 3 Previous Issue    Next Issue

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On the Calculation of Xinjiang's Green Economic Efficiency and Its Spatial-temporal Evolution—Based on Undesired Output Super-efficiency SBM-DEA Model Gao Zhigang, Tian Feng 2020, (3):  5-16.  doi: 10.16716/j.cnki.65-1030/f.2020.03.001 Abstract ( )   PDF (2094KB) ( )   Save This paper uses the undesired output super-efficiency SBM-DEA model to measure the green economic efficiency of 14 regions and cities in Xinjiang (excluding XPCC) from 2000 to 2017, and summarizes the development features of green economic efficiency in Xinjiang through space-time analysis. The following conclusions are drawn: The resource consumption index of most prefecture-level cities in Xinjiang is increasing year by year; the environmental pollution index has experienced two stages: first up, then down; the average value of green economy efficiency in Xinjiang decreased first and then fluctuated to rise with the efficiency value fluctuating around 0.4; by region, the average value of green economic efficiency in northern Xinjiang is higher than the average in Xinjiang, while the average in eastern and southern Xinjiang is lower than the average in Xinjiang; the spatial correlation shows that after 2007 in all parts of Xinjiang, the city has spatial agglomeration, and Xinjiang's green economic efficiency generally shows a pattern of hot in the middle, sub-cold in the east, and cold in the southwest. To this end, Xinjiang should reduce resource investment and environmental pollution, formulate a green development model that adapts to local conditions, optimize industrial structure, strengthen environmental governance capabilities, and improve environmental laws and regulations to achieve green and high-quality development. References | Related Articles | Metrics

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A Comparative Study of Industrial Multiplier, Spillover and Feedback Effect in the Yangtze River Delta Region —Based on Multi-region Input-output Model Huang Ruiling, Zhang Xu 2020, (3):  17-28.  doi: 10.16716/j.cnki.65-1030/f.2020.03.002 Abstract ( )   PDF (2004KB) ( )   Save Based on the latest inter-regional input-output table, this paper constructs a multi-regional input-output model to calculate the multiplier effect, inter-regional spillover effect and feedback effect in the Yangtze River Delta region. The empirical results show that Shanghai's industrial driving force is the strongest, and its spillover effect and feedback effect are stronger than those of Jiangsu and Zhejiang, and the spillover effect of the three industries is also the strongest, and its spillover effect on Jiangsu is stronger than that on Zhejiang. Jiangsu has the closest industrial association, with the strongest multiplier effect in the primary and secondary industries, however, no cross-regional industrial association has been formed, and the manufacturing industry is at the low end of the value chain. The secondary industry in Zhejiang is closely related and plays a strong driving role in Shanghai industry. Therefore, it is of great necessity to optimize the internal industrial structure to build the modern industrial system in the Yangtze River Delta region, improve the industrial correlation between regions to promote the overall coordinated development of the Yangtze River Delta region and improve the layout of the infrastructure network to enhance connectivity in the Yangtze River Delta region. References | Related Articles | Metrics

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Can Financial Knowledge Help Rural Households Participate in Internet Finance?—Based on the Data Analysis of China's Household Finance Survey in 2015 Wang Gang, hang Tian, Shi Qi 2020, (3):  29-39.  doi: 10.16716/j.cnki.65-1030/f.2020.03.003 Abstract ( )   PDF (891KB) ( )   Save Based on the data of 2015 China Household Finance Survey （CHFS）, this paper employs Probit model and instrumental variable analysis to investigate the impact of financial knowledge on rural households' Internet financial participation behavior. Through theoretical analysis and empirical test, it is found that financial knowledge can significantly promote the participation of rural households in Internet finance, however, heterogeneity exists between different age groups. Among them, the Internet financing behavior of the youth group and the Internet investment behavior of the middle-aged group were most significantly affected by financial knowledge, while the Internet investment and financing behavior of the elderly group was not significantly affected by financial knowledge. Therefore, it is of great necessity to strengthen financial literacy in rural areas, step up the innovation in Internet financial products, and strengthen the defense line of Internet financial risks to ensure that rural households can participate in Internet finance more rationally and which, in turn, can better serve the rural economy. References | Related Articles | Metrics

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Influence of Heterogeneous Social Capital of Rural Areas on Gender Income Gap—An Empirical Evidence from the 2015 Chinese General Social Survey （CGSS） Li Juanwei, Zhang Xiaoqian 2020, (3):  40-52.  doi: 10.16716/j.cnki.65-1030/f.2020.03.004 Abstract ( )   PDF (921KB) ( )   Save Narrow the income gap among rural residents is positively significant for the implementation of the current rural revitalization strategy. Selecting the 2015 China General Social Survey （CGSS） data, this paper uses the intermediary model to examine the adjustment effect of heterogeneous social capital on the gender income gap of rural residents from three dimensions: social media, trust and social contact. The research finds that the current gender income gap of rural residents is significant. The social capital measured by social network can significantly adjust the gender income gap of rural residents, on the contrary, the trust dimension of social capital could restrain the adjusting effect to the gender income gap of rural residents. However, the adjustment effect of social capital with the dimension of social interaction on rural gender income gap is not significant. Therefore, it is necessary to distinguish different forms of social capital. Government should improve the social capital accumulation of rural residents by improving the social network construction in rural areas, by enhancing the awareness of rural residents' trust and risk prevention, and by encouraging rural residents to cross-regional mobility, so as to create favorable benefits for adjusting rural gender income gap. References | Related Articles | Metrics

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Will TMT Heterogeneity Enhance Corporate Performance?—Based on the Threshold Effect of Executive Ownership Feng Linjie, Zou Wenjie 2020, (3):  53-61.  doi: 10.16716/j.cnki.65-1030/f.2020.03.005 Abstract ( )   PDF (878KB) ( )   Save This paper selects the panel data of Shenzhen-Shanghai A-share listed companies from 2012 to 2017, and uses the Hanse threshold model to demonstrate the correlation between TMT heterogeneity and corporate performance. The results show that the TMT heterogeneity has a nonlinear relationship with performance, and it has an interval effect due to the influence of the shareholding ratio of executives. Among them, TMT tenure heterogeneity is positively correlated with corporate performance, and changes to opposite as executives' shareholding ratio rises; TMT age heterogeneity has a negative impact on corporate performance. This interval effect also exists in the sub-sample of private enterprises. As the shareholding ratio of executives rises, this negative effect is enhanced. This paper uses the shareholding ratio of executives as a threshold variable, enriching the research model, broadening the perspective of performance improvement of listed companies, and providing a theoretical basis for enterprises to form a high-level management team. References | Related Articles | Metrics

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On Status Quo and Prospects of Russian Economic Growth from Historical Mirror Image Li Yang 2020, (3):  62-72.  doi: 10.16716/j.cnki.65-1030/f.2020.03.006 Abstract ( )   PDF (891KB) ( )   Save After the interruption of sustained economic growth since the beginning of the new millennium since 2008, the Russian economy has been in a long-term downturn. Under the influence of various internal and external factors, the Russian economy urgently needs to find a breakthrough. Historically, the inertia of the "Soviet-style" model 30 years after the transition has not gone far, and structural reforms have not been completed, it still relies heavily on it Energy industry. In this regard, Russia hopes to use the Basic Development Plan of the Russian Government 2024 as a breakthrough point to lead the next structural reforms, while promoting economic growth from the political level through "constitutional reforms". It is an important historical task for Russia to strike a balance among the various influencing factors and find the road to stabilize economic development in the future. References | Related Articles | Metrics

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A Study of the Influence of Road Connectivity Level on Bilateral Trade—Take China and the Countries along the "Silk Road Economic Belt"As an Example Wang Xia, Liu Tian 2020, (3):  73-80.  doi: 10.16716/j.cnki.65-1030/f.2020.03.007 Abstract ( )   PDF (1121KB) ( )   Save As the core content of the "Belt and Road" initiative, the construction of facility and trade connectivity is particularly important. Road connectivity is the foundation of facility connectivity. By using factor analysis, this paper establishes an evaluation index system to measure the level of road connectivity of countries along the "Silk Road Economic Belt". On this basis, taking India, the Russian Federation, Kazakhstan, and Pakistan as examples, this paper analyzes the level of road connectivity based on the VAR model. The influence of bilateral trade shows that the level of road connectivity in India, Kazakhstan and Pakistan has a greater positive effect on bilateral trade, while the level of road connectivity in the Russian Federation does not show a positive external effect. With the accelerated advancement of the "Belt and Road" initiative, the level of road connectivity in countries along the "Silk Road Economic Belt" can be improved by strengthening transportation infrastructure technology cooperation and talents cooperation, and promoting the intelligent development of transportation infrastructure. And then expanding the scale of bilateral trade. References | Related Articles | Metrics