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Under the leadership of China's ''dual-carbon'' goal, clarifying the interaction between the digital economy, artificial intelligence, and the sports industry is an important guarantee to promote the structural upgrading of China's sports industry and achieve low-carbon development. Therefore, a panel vector autoregression (PVAR) model is constructed based on the panel data of 15 provinces in China from 2014 to 2020 to investigate the interaction between the three. It is found that (1) every 1-unit increase in the level of digital economy in the lagged period can cause a 0.008-unit increase in the level of AI application in the current period at the 10% significance level, i.e., the digital economy has a short-term and weakly facilitating effect on AI. (2) Every 1 unit of digital economy level in the lagging period can cause 9.539 units of value added to the sports industry at a 1% significance level. That is, the digital economy has a short-term but strong enhancing effect on the development of the sports industry. (3) Their internal driving force mainly drives the development of digital economy and artificial intelligence, and the self-contribution rate is 72.7% and 91.5% respectively. In contrast, the self-driving force of the sports industry is weaker, and the self-contribution rate is only 68.2%. (4) The contribution rate of the digital economy and artificial intelligence to the development of the sports industry is 12.3% and 19.6% respectively, i.e., the sports industry is more affected by the degree of application of artificial intelligence than the level of development of digital economy.

The article investigates the Covid-19 pandemic related changes in the demand for insurance services in the Unites States due to business interruptions by employing panel vector autoregression models to a dynamic panel data set of 50 states and District of Columbia for three periods of time: 01 January, 2004 to 28 June, 2020; 01 January, 2004 to January 21, 2020 (pre-Covid period); January 22, 2020 to June 28, 2020 (Covid-period). This paper is the first attempt to obtain estimates by applying Google Trends with a search key word “Business Interruption Insurance”. The data was collected and reduced to a single scale by US states within the widest possible time span. Google Trends Hits and Initial Claims for Unemployment Insurance Benefits are used as endogenous variables in the built models. In the constructed models, the impact of the exogenous variable New Covid Cases is compared with that of over US billion-dollar natural disasters. The impulse responses show a positive relationship between the Google Trends Hits and Initial Claims with the Covid-factor having a significant impact on the responses. The conducted analyses reveal that the demand for insurance services due to the Covid-19 outbreak in the United States can be expected to increase 2–6 times, with the total amount of the incurred costs for the economy due to the virus ranging from 0.3 to 7 percent of the US-2019 GDP. The results lay the foundation for recommending the insurance market participants to lobby for adoption of public-private protection schemes being able to secure a more efficient response to the pandemic-related losses that may occur in the future.

Under the leadership of China's "dual-carbon" goal, clarifying the interaction between the digital economy, artificial intelligence, and the sports industry is an important guarantee to promote the structural upgrading of China's sports industry and achieve low-carbon development. Therefore, a panel vector autoregression (PVAR) model is constructed based on the panel data of 15 provinces in China from 2014 to 2020 to investigate the interaction between the three. It is found that (1) every 1-unit increase in the level of digital economy in the lagged period can cause a 0.008-unit increase in the level of AI application in the current period at the 10% significance level, i.e., the digital economy has a short-term and weakly facilitating effect on AI. (2) Every 1 unit of digital economy level in the lagging period can cause 9.539 units of value added to the sports industry at a 1% significance level. That is, the digital economy has a short-term but strong enhancing effect on the development of the sports industry. (3) Their internal driving force mainly drives the development of digital economy and artificial intelligence, and the self-contribution rate is 72.7% and 91.5% respectively. In contrast, the self-driving force of the sports industry is weaker, and the self-contribution rate is only 68.2%. (4) The contribution rate of the digital economy and artificial intelligence to the development of the sports industry is 12.3% and 19.6% respectively, i.e., the sports industry is more affected by the degree of application of artificial intelligence than the level of development of digital economy., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Laibing Lu reports financial support was provided by The National Social Science Fund of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

This article studies the linkage between financial inclusion, monetary policy and financial stability in 58 countries including 31 high financial development countries (HFDCs) and 27 low financial development countries (LFDCs) from 2004 to 2020 using the PVAR method. Results of impulse - response function suggest that in LFDCs, while financial inclusion and financial stability are positively correlated, they are negatively correlated with the inflation rate and the money supply growth rate. In HFDCs, financial inclusion is positively corelated with inflation rate and money supply growth rate, while financial stability is negatively correlated with financial inclusion, inflation rate and money supply growth rate. These findings imply that in LFDCs, financial inclusion increases financial stability and reduces inflation. In HFDCs, on the contrary, financial inclusion increases financial instability, leading to long-term inflation. The results of the variance decomposition confirm the above outcomes, specifically, this relationship is clearer in HFDCs. From the above findings, we propose some policy recommendations on financial inclusion and monetary policy for financial stability for each group of countries., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

The article investigates the Covid-19 pandemic related changes in the demand for insurance services in the Unites States due to business interruptions by employing panel vector autoregression models to a dynamic panel data set of 50 states and District of Columbia for three periods of time: 01 January, 2004 to 28 June, 2020; 01 January, 2004 to January 21, 2020 (pre-Covid period); January 22, 2020 to June 28, 2020 (Covid-period). This paper is the first attempt to obtain estimates by applying Google Trends with a search key word "Business Interruption Insurance". The data was collected and reduced to a single scale by US states within the widest possible time span. Google Trends Hits and Initial Claims for Unemployment Insurance Benefits are used as endogenous variables in the built models. In the constructed models, the impact of the exogenous variable New Covid Cases is compared with that of over US billion-dollar natural disasters. The impulse responses show a positive relationship between the Google Trends Hits and Initial Claims with the Covid-factor having a significant impact on the responses. The conducted analyses reveal that the demand for insurance services due to the Covid-19 outbreak in the United States can be expected to increase 2-6 times, with the total amount of the incurred costs for the economy due to the virus ranging from 0.3 to 7 percent of the US-2019 GDP. The results lay the foundation for recommending the insurance market participants to lobby for adoption of public-private protection schemes being able to secure a more efficient response to the pandemic-related losses that may occur in the future., Competing Interests: The authors declare no conflict of interest., (© 2021 The Author(s).)