The low-carbon city pilot is an important policy for promoting sustainable development and addressing climate change. The level of green technological innovation is a significant driving force for China's transition to high-quality development and the realization of carbon peaking and carbon neutrality goals. This essay takes the panel data of 30 provinces in China from 2008 to 2020 as the research sample, regards the number of urban green invention patent applications as a quantifiable indicator of the level of urban green technological innovation, and takes the policy of low-carbon city pilot as a quasi-natural experiment, and uses the difference-in-differences model to test the impact of low-carbon city pilot on the level of urban green technological innovation, and to investigate the mechanism of action within. The main conclusions are as follows: (1) The policy of low-carbon city pilot has an outstanding promotion effect on the level of urban technological innovation. (2) Using the mediating effect to analyze, it is found that the low-carbon city pilot policy can improve the level of urban green technological innovation through the development of green finance.

With the continuous advancement of technological revolution and industrial transformation, digital finance supported by big data and artificial intelligence has become an important engine for promoting carbon neutrality. We measured the industrial structure transformation index (ISU) of 30 provinces in China, and discussed the spatial spillover effect and transmission mechanism between digital finance and ISU using the spatial Durbin model. The research results demonstrate that the digital finance development can significantly improve the local ISU. Interestingly, the impact of digital finance on the ISU of adjacent areas has a significantly negative spatial spillover effect, which still exists under the different spatial weight matrix. Digital finance can improve ISU by improving green technology innovation, upgrading industrial structure, and alleviating capital allocation. We also found that the higher degree of marketization and environmental regulation can increase the positive influences of digital finance on ISU. This research proves the effectiveness of the digital finance in improving energy efficiency, and it encourages policymakers around the world to rely on digital finance to promote ecological governance and achieve high-quality economic development.

The primary goal of this research is to examine how different types of energy are used in South Asian countries and how they affect the environment and economic growth. From 1990 through 2021, this research employed Panel Data from multiple sources covering the South Asian countries of Pakistan, India, Bangladesh, Sri Lanka, Nepal, Bhutan, Maldives, and Afghanistan. The results are determined by using the Fixed Effect Regression (FEM) technique in both models. Several significant findings are supported by the data. First, while using renewable energy flattens carbon dioxide effusion, using non-renewable energy sources increases it. CO2 emissions are affected negatively by gross domestic product but positively by gross domestic product square. These results provide credence to the idea that South Asian countries do experience an Environment Kuznets Curve. Furthermore, foreign direct investment has a beneficial effect on CO2 emissions, lending credence to the Pollution Haven Hypothesis. Model 2 instead finds that both renewable and non-renewable energy consumption contributes to economic expansion. Gross Fixed Capital Formation and foreign direct investment also contribute to economic growth in this area. Finally, Inflation retards economic expansion.

Human factor inputs are key to promoting agricultural modernisation. Traditional economic theory suggests that improving human capital is the key to boosting agricultural productivity, but can this conclusion hold in China's dualistic economic structure? We use Chinese provincial panel data from 2000-2017 to examine the impact of rural human capital inputs on agricultural total factor productivity. We find that, on the whole, rural human capital inputs have a negative effect on agricultural total factor productivity, and that there is a "rural human capital trap". Mechanism analysis reveals that rural human capital inputs, on the one hand, cause labour loss and reduce the quality of agricultural workers, while on the other hand, they may promote the application of mechanization, which has both positive and negative effects on agricultural total factor productivity. Heterogeneity analysis finds that this negative effect is more pronounced in the central region of China because of the serious loss of rural labour. This study provides new policy insights for further improving the structure of rural education inputs and promoting human capital accumulation in agriculture.

The long-term extensive economic development has caused China's resource and environmental problems, especially the resource misallocation. The way China prioritises its limited resources is being significantly impacted by the rise of the digital economy and the interconnectedness of new technologies and the real economy. This paper quantitatively examines the linear and nonlinear impacts and mechanisms of digital development represented by internet development. With a series of empirical tests, we found that the internet development has significantly inhibited the resources misallocation, and the conclusion is still valid in the robustness test with internet popularization and internet infrastructure as the core explanatory variables. In addition to the marketization, internet development can further inhibit resource misallocation by promoting financial development, openness, urbanization and industrial structure. The findings of threshold regression suggest that the inhibitory effect of internet growth on resource misallocation becomes more visible as the degree of financial development and industrial structure increases; with the higher degree of urbanisation and marketization, although the internet development has always played an inhibitory role on resource mismatch, the inhibitory effect first increases and then decreases; with the improvement of openness, the hindering impact of internet growth on resource mismatch becomes more visible as the degree of financial development and industrial structure increases.

This paper examines impacts of China’s financial liberalization policy on income inequality, through three channels: financial scale, financial structure and financial efficiency, an empirical analysis based on panel data of 30 provinces in China from 1996 to 2013 is conducted. The results confirm the Kuznets effect between financial scale, financial structure and income inequality. As the size of the financial sector expands, the financial structure is tilted toward direct financing, and the income gap among residents will experience a "reverse U-shaped" trend that rises first and then falls. Most of China has not yet passed the turning point, and is still in the upper bound of the "inverted U-shaped" curve. Financial liberalization policies will continue to exacerbate income inequality. The impact of financial efficiency on income distribution is quite different in different regions of China. After dividing the whole China into three regions according to the degree of economic development, it is found that the financial efficiency of the eastern and western regions has a Kuznets effect on the income gap, but compared with the eastern region, more provinces and cities in the western region have entered the stage of reducing the income inequality, and the financial development has a great impact on the western region. The effects of financial development on central China are weak, and income inequality increases with financial efficiency.

Economic globalization has intensified economic volatility around the world, and the importance of economic resilience has become increasingly prominent in the face of rising uncertainty due to frequent domestic and foreign shocks. Based on provincial panel data in China from 2008-2019, a comprehensive indicator system is constructed to measure regional economic resilience (RER), and the impact of financial driver (FD) on RER is explored from staged, pathway and non-linear perspectives. The main findings are as follows. (1) Both national and regional levels of FD and RER show an upward trend, and the impact of FD on RER has an “inverted-U” shape: as the capacity of FD increases, its impact on regional economic resilience shifts from promoting to inhibiting. The RER has significant spatial agglomeration characteristic. (2) Interestingly, staged analysis shows FD can significantly promote RER only when it is in the “recovery stage”. (3) The pathway analysis of its effect on regional economic resilience shows the following characteristics: financial scale > financial efficiency > financial deepening. (4) From different regions, there are significant differences in the effect of FD on the promotion of regional economic resilience: central region > western region > eastern region. Finally, the corresponding suggestions were provided.

Using an international dataset, this letter finds that high stock returns are associated with increased death rates from drug use disorders. Although the out-of-pocket expenditure on healthcare also rises following a stock market surge, the net effect on life expectancy is significantly negative.

Credit markets around the world are undergoing digital transformation which has led to the rise in FinTech and BigTech lending. FinTech and BigTech lending is the provision of credit by FinTech and BigTech providers who have more capital, cutting-edge IT systems, worldwide recognition, greater online presence and are able to handle more big data on computers and mobile phones than traditional banks. FinTech and BigTech lending is growing in importance, but the determinants of FinTech and BigTech lending have received little attention in the literature. This study investigates the determinants of FinTech and BigTech lending. The study focused on the effect of financial inclusion and financial development on FinTech and BigTech lending. Using data for 18 countries from 2013 to 2019 and employing the difference-GMM and 2SLS regression methods, the findings reveal that financial inclusion and financial development are significant determinants of FinTech and BigTech lending. Financial development is a positive determinant of FinTech and BigTech lending while financial inclusion has a significant effect on FinTech and BigTech lending. Also, FinTech and BigTech lending lead to greater banking sector stability and also poses the risk of rising nonperforming loans. There is also a significant positive correlation between financial development and FinTech and BigTech lending. These findings add to the emerging literature on the role of FinTech and BigTech in financial intermediation. This research is significant because it provides insights into the role of financial inclusion and financial development in the digital transformation of credit markets.

Bank deposit is closely related to systemic risks. In addition, considering that resident deposits in China have significant seasonal characteristics, this paper focuses on which component of deposits drives the systemic risk volatility, that is, it can supplement the existing forecast information. We use X-13ARIMA-SEATS to decompose deposit into three subsequences. The research findings show that the forecast effect of subsequence models is better than that of benchmark series. Most importantly, the model with trend component has the best forecast performance.

This paper investigates the effect of economic policy uncertainty (EPU) on the systemic risk of the fintech industry. To achieve this goal, we first estimate the evolution of system-wide systemic risk using the CatFin method. We further examine whether EPU significantly affects systemic risk. Our findings demonstrate that the systemic risk of the fintech industry is time-variant and sensitive to major crisis events. Systemic risk tends to increase after major crises, especially the outbreak of the COVID-19 pandemic. EPU has a considerable impact on systemic risk, notably during periods of turmoil.

The vigorous development of the digital economy has brought new opportunities and challenges to the construction of local fiscal revenue efficiency. Based on the panel data from 2011 to 2020, this paper uses the fixed effect model, instrumental variable method and other empirical studies to investigate the impact of the development of the digital economy on the efficiency of local fiscal revenue. The research results show that the development of the digital economy has directly improved the efficiency of local fiscal revenue, and the regression results of instrumental variables are still significant. The mechanism analysis shows that the development of digital economy mainly promotes local fiscal revenue such as efficiency improvement by cultivating tax sources.

We assess the impact of the Strategic Economic Plan on Singapore’s long-term GDP per capita. To our knowledge, we are the first to evaluate the effect of the 1991 plan on Singapore’s successful growth trajectory using methodologies aimed at causal identification. In other words, this article applies the Synthetic Control method and World Bank data from 1970 to 2018. We estimate an average increase of 6,641.71 US$ in Singapore’s GDP per capita. Results remain robust to placebo and leave-one-out tests and the Synthetic Difference-in-Differences method.

This paper empirically investigates the relation between firm performance in corporate social responsibility (CSR) and the need and likelihood of external financing to test the predictions of agency and stakeholder theories. Empirical results from Logit, Linear Probability Model, OLS and Firm fixed effects regressions indicate that CSR is negatively related to the likelihood and level of external financing. Further analysis indicates that CSR has a negative and significant effect on both net equity issued (NEI) and net debt issued (NDI), the two components of external financing. Overall, the empirical results support the predictions of agency theory.

This study aims to examine the effects of student loan debt on the decisions of U.S. married households to invest in stocks located in non-retirement accounts. Using longitudinal datasets from the 2011 to 2017 U.S. Panel Study of Income Dynamics and a fixed effects logit model, the results show mixed findings. The presence of student debt decreases the probability that married households will own stocks, but the amount of student debt does not show a statistically significant effect. The findings suggest that the incidence of student debt raises the perception of liquidity constraints and debt burden among married households.

Consideration of optimal commodity storage with different discount rates. Finding that, even with a lower discount rate than private storage, optimal government-financed storage may not narrow price fluctuations compared with optimal privately financed storage because a government has to choose a probability of buffer stock failure greater than zero to economize on storage costs that could conceivably become very large. There is no presumption that government financed storage would be larger, with narrower intervention bands and more stable prices, than with privately-financed storage. The welfare enhancing effect of government financed storage compared to private storage is therefore indeterminate.

Considering that housing is the single biggest asset for most households, owning a home may create barriers to entrepreneurship for young people who generally accumulate relatively little wealth due to a short-term career and low income. Using longitudinal data from the China Family Panel Studies (CFPS) survey, our empirical work suggests that homeowners are associated with significantly less propensity for entrepreneurial engagement and the negative homeownership effect on entrepreneurship is much larger for younger homeowners. These findings are robust to omitted variable bias, reverse causality and model misspecification. We explore the mechanism through which capital constraints related to housing purchase may more affect younger homeowners from starting entrepreneurial activities. We find strong supportive evidence for this mechanism.

Cardiovascular disease is still a disease with high incidence rate and mortality. Although advanced technology continues to increase our understanding of cardiovascular disease, its diagnosis and treatment still have limitations. As an emerging interdisciplinary method, nanotechnology has shown enormous clinical application potential. Nanomaterials have unique physical and chemical properties, which help to improve the sensitivity and specificity of biosensor technology and molecular imaging technology in the diagnosis of cardiovascular diseases. This paper first summarizes the versatility of nanomaterials, the physicochemical adjustability of biomolecular engineering, the design strategy of nanoparticles in cardio cerebral Vascular disease, the application of nanomaterials in the diagnosis and treatment of common cardiovascular diseases, and the use of nanomaterials can significantly improve the diagnostic sensitivity, specificity and therapeutic effect. Subsequently, the article summarized various nanomaterials. Finally, the article demonstrated the potential of the antioxidant/anti-inflammatory and photoelectric/photothermal properties of nanomaterials to be directly applied to the treatment of cardiovascular diseases.

The purpose of the study is to determine the relationships between the factors, attitude towards food consumption and green purchase intention in organic food markets of Pakistan. A Total of 301 sample data was analyzed by SPSS and PLS-SEM. These statistical techniques were used to test the hypotheses. The study was supported the theories include theory of Reasoned Action, Planned Behavior, and expectancy-value model of attitude theory. It also enhances the intention of purchase to buy organic food. The study found that environment, consciousness of health, and safeties of food have significantly direct and indirect influence on Intention of purchase while, taste of food, and exposure of media only have significantly indirect effect on Intention of purchase. The study recommended that retailers should advertise organic food via social media or channels as media persuasively increase the chances to grab the consumer attention to buy the product.

Cryptocurrencies have gained popularity over the past five to six years. Most recently, events like the FTX bankruptcy fueled the interest in regulation. Moreover, it is possible that the FTX event disrupting the cryptocurrency market was a factor in Silicon Valley Bank's failure. While several countries consider regulation, from soft regulation, like Japan, to more rigid standards, like the total ban in China, we study the effect of other news or events on cryptocurrency prices. This paper looks at historical closing prices for Bitcoin, the largest of the cryptocurrencies, and how prices react to various events. Then we focus on modeling the time series considering an 'event,' China's ban on cryptocurrency exchanges, using intervention analysis. We find that intervention analysis provides a reliable approach to quantifying the impact regulation may have on cryptocurrency pricing.