Contribution of the Optimization of Financial Structure to the Real Economy: Evidence from China’s Financial System Using TVP-VAR Model

Liu, Xiaoye; Yin, Kedong; Cao, Yun

doi:10.3390/math9182232

Cited by 5 publications

(3 citation statements)

References 57 publications

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“…This overcomes the burden of the often arbitrarily chosen rolling window size that can lead to erratic or flattened parameters and the loss of valuable observations; instead, it is possible to examine the dynamic connectedness at lower frequencies and with limited time series data. Time-varying connectedness can be used to examine correlation effects of one-to-many, many-to-one, and one-to-one among variables (Antonakakis and Gabauer 2017 ; Zhang and Hamori 2021 ; Jebabli et al 2014 ; Liu et al 2021 ) and is introduced here for the purpose of studying the dynamic spillover effect of the carbon price among pilot markets so as to broaden the research of the return dynamic spillover of the pilot markets in China.…”

Section: Introductionmentioning

confidence: 99%

Time-varying spillovers among pilot carbon emission trading markets in China

Xiao

Sun

et al. 2022

Environ Sci Pollut Res

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Clarifying the time-varying spillovers among pilot carbon emission permit trading markets in China is an important foundation for building the national carbon emission trading market. We calculate the dynamic spillover of carbon price return among the pilot carbon emission permit trading markets in China with the time-varying connectedness approach. The dataset is constructed from transaction data from seven pilot carbon markets in China during the period of June 23, 2014, to December 31, 2020. The quantitative analysis suggests that (i) Beijing and Chongqing carbon emission trading markets are the main spillover markets of carbon price returns, with strong pricing power, while the Guangdong and Tianjin markets are the main receivers of the price return spillover in other pilot carbon emission trading markets. (ii) The spillover effect among China’s carbon markets has a strong policy orientation. The improvement and development of the carbon market driven by macroeconomic regulation and control policies can effectively improve the spillover ability of the carbon market, and the market trading activity, namely the volatility of the carbon price return rate, can amplify the spillover ability of the carbon market in the short term. (iii) There exist three types of price return spillover among China’s pilot carbon emission trading markets, including central divergence, one-way chain transmission, and circular spillover. Along with the improvement of market operation efficiency, the central divergent type of spillover shifts to the pattern of circular spillover. It is necessary for the government to improve market efficiency and ensure the coordinated development of China’s pilot carbon emission trading market and national carbon emission trading market. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-022-19914-4.

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Section: Introductionmentioning

confidence: 99%

Time-varying spillovers among pilot carbon emission trading markets in China

Xiao

Sun

et al. 2022

Environ Sci Pollut Res

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“…Han and Fu (2020) found that finance has a positive regulatory effect on manufacturing innovation performance. However, Liu et al (2021) study found that the financial structure can promote the scale of the real economy, but the impact on the structure is not obvious. Therefore, it is necessary to further study the impact of finance on the industry.…”

Section: Influencing Factors Of Industrymentioning

confidence: 94%

Exploring the influencing factor of urban industry development: An order parameter method

Dou¹,

Sun²,

Wu³

et al. 2023

Front. Sustain. Cities

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This study aims to analyze the factor affecting the urban industry development in Guangzhou. Based on push-pull-mooring theory, we explain the reasons for choosing the above indicators and use order parameters to analyze their impact on the urban industrial development. The results show that: (1) Environment has an obvious promoting effect on the urban industrial development. This shows that the current environment and the urban industrial development have reached a balance. (2) Technology has a positive impact on the urban industrial development, but it needs to go through the technology running in period smoothly. (3) Different from other factors, finance has a crowding out effect on industrial development. However, the development of finance will promote the rapid development of industry in Guangzhou. (4) The impact of finance, technology and green on UID is applicable to different development stages of UID, that is, these variables are related. Lastly, we provided development suggestions for Guangzhou. This will lay a foundation for promoting its industry.

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“…This approach builds on the work of Antonakakis et al (31,32) and Gabauer (33,34) who advances the connectedness approach proposed by Diebold and Yilmaz (35)(36)(37) and overcomes the burden of the often arbitrarily chosen rolling-window-size that can lead to erratic or flattened parameters and loss of valuable observations, being able to examining the dynamic connectedness at lower frequencies and limited time-series data. This method that is mostly applied to research the correlation effects of one-tomany, many-to-one and one-to-one among variables (38)(39)(40)44) is introduced by us to model the dynamic transmission of the COVID-19 epidemic among countries to broaden the research of the dynamic transmission of the global COVID-19 epidemic.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Global Dynamic Contagion of COVID-19

Xiang

Lü

et al. 2022

Front. Public Health

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The COVID-19 infections have profoundly and negatively impacted the whole world. Hence, we have modeled the dynamic spread of global COVID-19 infections with the connectedness approach based on the TVP-VAR model, using the data of confirmed COVID-19 cases during the period of March 23rd, 2020 to September 10th, 2021 in 18 countries. The results imply that, (i) the United States, the United Kingdom and Indonesia are global epidemic centers, among which the United States has the highest degree of the contagion of the COVID-19 infections, which is stable. South Korea, France and Italy are the main receiver of the contagion of the COVID-19 infections, and South Korea has been the most severely affected by the overseas epidemic; (ii) there is a negative correlation between the timeliness, effectiveness and mandatory nature of government policies and the risk of the associated countries COVID-19 epidemic affecting, as well as the magnitude of the net contagion of domestic COVID-19; (iii) the severity of domestic COVID-19 epidemics in the United States and Canada, Canada and Mexico, Indonesia and Canada is almost equivalent, especially for the United States, Canada and Mexico, whose domestic epidemics are with the same tendency; (iv) the COVID-19 epidemic has spread though not only the central divergence manner and chain mode of transmission, but also the way of feedback loop. Thus, more efforts should be made by the governments to enhance the pertinence and compulsion of their epidemic prevention policies and establish a systematic and efficient risk assessment mechanism for public health emergencies.

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Contribution of the Optimization of Financial Structure to the Real Economy: Evidence from China’s Financial System Using TVP-VAR Model

Cited by 5 publications

References 57 publications

Time-varying spillovers among pilot carbon emission trading markets in China

Time-varying spillovers among pilot carbon emission trading markets in China

Exploring the influencing factor of urban industry development: An order parameter method

Modeling the Global Dynamic Contagion of COVID-19

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