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ESG ratings are closely linked to corporate resource allocation and overarching macroeconomic constituents. Nevertheless, there is a noticeable lack in the literature investigating the interconnected relationship between the growth of local government debt, corporate underinvestment, and ESG ratings. This study aims to investigate the impact of local government debt on corporate underinvestment and its subsequent effects on corporate ESG performance. To achieve this goal, this study utilizes special bond data from Chinese provinces spanning the period between 2015 and 2021. The findings suggest that as local government debt swells, it imposes financing constraints on local companies, leading to underinvestment, particularly for listed companies with a high proportion of fixed assets and non-state-owned enterprises. A key effect is a "crowding-out effect" in which local government debt absorbs resources that could otherwise be allocated to private corporations and non-investment sectors. This trend illuminates the concealed costs of a debt-reliant growth model extending beyond the financial sector to impact broader corporate behavior and ESG performance. Our research suggests that government debt, corporate financing constraints, and ESG investment are intimately linked. The study concludes with policy implications and recommendations aimed at mitigating the investment gap in Chinese enterprises and promoting sustainable economic growth. [ABSTRACT FROM AUTHOR]

This paper investigates the interrelationships among local government debt, fiscal decentralization, and public health. The investigation begins by constructing a theoretical model to analyze the inherent connections between these variables. Subsequently, an empirical analysis is conducted using data from China between 2015 and 2021. The findings demonstrate a bidirectional relationship between fiscal decentralization, local government debt, and public health. Specifically, it is observed that an increase in local government debt has adverse effects on both fiscal decentralization and public health, while fiscal decentralization has a positive impact on public health. These insights are consistently validated through rigorous regression methodologies, affirming the robustness and significance of these relationships. [ABSTRACT FROM AUTHOR]

The attentional processes are conceptualized as a system of anatomical brain areas involving three specialized networks of alerting, orienting and executive control, each of which has been proven to have a relation with specified time-frequency oscillations through electrophysiological techniques. Nevertheless, at present, it is still unclear how the idea of these three independent attention networks is reflected in the specific short-time topology propagation of the brain, assembled with complexity and precision. In this study, we investigated the temporal patterns of dynamic information flow in each attention network via electroencephalograph (EEG)-based analysis. A modified version of the attention network test (ANT) with an EEG recording was adopted to probe the dynamic topology propagation in the three attention networks. First, the event-related potentials (ERP) analysis was used to extract sub-stage networks corresponding to the role of each attention network. Then, the dynamic network model of each attention network was constructed by post hoc test between conditions followed by the short-time-windows fitting model and brain network construction. We found that the alerting involved long-range interaction among the prefrontal cortex and posterior cortex of brain. The orienting elicited more sparse information flow after the target onset in the frequency band 1–30 Hz, and the executive control contained complex top-down control originating from the frontal cortex of the brain. Moreover, the switch of the activated regions in the associated time courses was elicited in attention networks contributing to diverse processing stages, which further extends our knowledge of the mechanism of attention networks. [ABSTRACT FROM AUTHOR]

In recent years, the global economy has become more closely related among countries, and people's pursuit of economic growth has caused the destruction of the environment. This paper selected panel data from 30 provinces in China from 1997 to 2020 to investigate the dynamic relationship between trade liberalization, financial development and carbon dioxide emissions by constructing a PVAR model. We also consider technology as an important variable for studying the effect on carbon dioxide emissions. We draw the following conclusions. First, financial development promotes carbon dioxide emissions, while trade liberalization has no significant impact on carbon dioxide emissions. Second, China's trade liberalization promotes financial development, which has limited support for international trade. Third, there is a two-way causal relationship between financial development and carbon dioxide emissions, and there is also a two-way causal relationship between trade liberalization and financial development. Finally, there is a significant inverted "U" curve relationship between trade liberalization and innovation efficiency, environmental regulation and innovation. According to the results, we believe that openness to trade impacts emissions of carbon dioxide, opening a new function path: namely, trade openness and financial development result in high carbon dioxide emissions; consequently, China has relied on this process in the development of their financial system. [ABSTRACT FROM AUTHOR]

The contradiction between financial development and environmental pollution has become increasingly prominent with economic development. The discovery of the link between financial development and carbon dioxide emissions will aid in the development of solutions to this problem. This paper uses a panel smooth transition regression (PSTR) model to examine the impact of financial development on carbon dioxide emissions using panel data from 28 Chinese provinces from 2005 to 2021. The PSTR model can solve the problem of minimizing potential outliers ignored in the previous literature, while taking into account the endogeneity and heterogeneity of the model and obtaining more reliable results. According to the findings, financial development has a nonlinear effect on carbon dioxide emissions. Furthermore, the positive effect of financial development on carbon dioxide emissions occurs via the scale and structural effects, while the negative effect occurs via the technological effect, which takes up more space. Moreover, financial added value and the financial scale demonstrate a smooth transition, while financial efficiency and foreign direct investment demonstrate a positive influence.