Green innovation, driven by China's new development concept, plays a crucial role in high-quality economic development. In line with the green development trend, businesses increasingly prioritize whether their corporate environmental responsibilities (CER) can effectively enhance corporate green innovation (CGI) levels. This paper examines the influence and mechanism of CER on CGI using a dynamic perspective, drawing from 1,640 manually-collected panel data of Shanghai and Shenzhen A-share listed companies between 2010 and 2017. The primary findings indicate that the impact of CER on CGI possesses phase-specific characteristics and a dual effect of "crowding in" and "crowding out." The current phase of CER negatively affects green innovation, while the lag phase has a positive effect. CER's impact on various CGI types is heterogeneous: specifically, it follows an "inverted-N" trajectory (inhibition-promotion-inhibition) for "strategic green innovation" and has a promotional effect on "substantive green innovation," which is stronger and has a longer time lag. The mechanism analysis reveals that financing constraints play a critical mediating role. A heterogeneity analysis based on multiple dimensions (ownership, industry, and location) suggests that CER has a more significant driving force for CGI among state-owned firms, high-polluting industries, and enterprises in inland areas. Finally, the paper presents corresponding suggestions for government and corporate entities.

Based on the empirical data of 6110 listed export companies in China from 2010 to 2019, this paper studies the impact of China's economic policy uncertainty (EPU) index on the profitability of listed companies from the specific perspective of export companies, and analyzes the moderating effects of different factors on this impact. The results show that China's EPU index has a significant negative impact on the profitability of listed export companies, and the increase in R&D investment and wage returns will aggravate this negative impact. In addition, listed export enterprises with different enterprise characteristics have different responses to EPU. State-owned enterprises and enterprises located in coastal areas are relatively less negatively affected by EPU.

Vector Error Correction Models (VECM) have become a standard tool in empirical economics for analyzing nonstationary time series data because they integrate two key concepts in economics: equilibrium and dynamic adjustment in a single model. The current standard VECM procedure is limited to time series data with the same degree of integration, i.e., all I(1) variables. However, empirical studies often involve time series data with different de‐grees of integration, necessitating the simultaneous handling of I(1) and I(0) time series. This paper extends the standard VECM to accommodate mixed I(1) and I(0) variables. The conditions for the mixed VECM are derived, and consequently, we present a test and estimation for the mixed VECM.

This paper evaluates the use of macro-level insurance to finance post-disaster recovery and reinstatement by investigating the case of the National Disaster Insurance policy implemented by Sri Lanka. The national scheme provided cover for all properties in the country against hazards such as flooding and provided compensation for those affected. Analysis of secondary data obtained from the organisations that managed the scheme showed that the scheme has delivered a much higher return compared to the total insurance premium paid, suggesting that the scheme has delivered a net positive benefit compared to the cost of the premium and can be considered a viable option. However, the existing secondary data did not reveal the values of other costs and indirect benefits associated with the scheme to compute a meaningful benefit-to-cost ratio. Further rigorous, evidence-based cost-benefit analysis is required to assess the cost-effectiveness of a scheme of this nature. A cost-benefit analysis approach based on an analytical hierarchy process is proposed as a possible solution to assess the cost-effectiveness of the scheme, which could be used by government organisations as an alternative, where analytical and research resources may be limited, to evaluate a range of disaster recovery financing options using stakeholder opinion.

With the advancement of science and technology and the advent of the digital economy, the digital economy has become a new driving force for economic development, and the digital economy industry at home and abroad is facing new opportunities for survival and development. However, due to the special development model and profit mode of the digital economy industry, the traditional performance evaluation method is no longer applicable, so it is particularly important to improve the previous performance evaluation method. This paper first adjusts the customer value assessment (CLV) model according to the characteristics of the digital economy industry, and then analyzes the traditional EVA based on the adjusted user value assessment (ULV) model of the digital economy industry. The performance evaluation system is improved, and the representative enterprises of Alibaba, JD and Pinduoduo in the digital economy industry are selected for performance evaluation and analysis, and the user value performance evaluation model of the digital economy industry is integrated, innovated and standardized, in order to provide reference and reference for the follow-up research and practice of performance evaluation in the digital economy industry.

Given the rapid development of live streaming commerce in China, this study focuses on the interactivity and sociability of live streaming shopping activities and explores online consumers’ real-time interaction intentions and trust-building behaviours with online merchants. To discover the real-time interaction between online consumers and online merchants, this study builds a research model based on the Theory of Planned Behaviour (TPB). Through the data analysis based on the partial least squares path modelling and variance-based structural equation modelling (PLS-SEM), the key findings state that, three factors, including attitude, subject norm, and perceived control, positively affect online consumers’ real-time interaction intentions and lead them to build trust with online merchants. Meanwhile, control variables, including gender, age, and educational background, demonstrate insignificant effects across the model. Unlike existing literature, the current study pays much attention to the interactive characteristics of live streaming shopping activities and can provide some valuable suggestions both for online consumers and online merchants, which can promote the co-development of the commercial and social aspects of live streaming platforms.

In the past, investing in housing has served as an engine of growth for many economies as it is widely recognized that poor housing conditions can have significant negative impacts on human health, education, and economic opportunities. To assess the housing-related quality of life, indicators such as housing quality, housing environment, and cost burdens can be applied. However, recent studies indicate that materials used for construction are critical. Permanent materials, as opposed to temporary materials, typically offer a range of benefits in terms of durability, low maintenance, improved energy efficiency, increased property value, and better safety. The ultimate aim is to identify the key drivers of housing conditions in Cambodia, with a particular focus on materials and water quality, and the legal status of housing. To find the empirical relationship between economic, socio-economic, and demographic variables on the one hand, and variables measuring housing and living conditions in Cambodia on the other, the analysis employs Ordinary Least Squares and Methods-of-Moments regression modeling. Results indicate that high employment rates and entrepreneurship increase home ownership, and improve the quality of drinking water available. Furthermore, in addition to employment and entrepreneurship, the higher-performing construction materials can also be empirically explained by a bigger labor force and variables capturing the wider macroeconomic environment.

Because of the complexity of indirect financial intermediary services (FISIM) accounting, the traditional price index deflation method can no longer meet its accounting needs. The manual of price and volume measurement suggests that the stock deflation method and output index method should be used to calculate the volume of FISIM. Comparing the two accounting frameworks, it can be found that the key to the implementation of the stock deflation method is to set a scientific and reasonable deflation index from two aspects of service price and the service quantity, while the key of the output index method is the selection of the output index and the determination of weight. This paper compares the application cases of stock deflation method and output index method in practice, summarizes the similarities, differences, advantages and disadvantages of each case in index construction, index selection and weight determination, and further provides a reference for China FISIM volume accounting.

The objectives and tasks of the European Central Bank (ECB) are defined in Articles 2 and 3 of Protocol (No 4) on the Statute of the European System of Central Banks (ESCB) and of the European Central Bank (ECB). While in Article 3,1° of this Protocol other tasks are mentioned, the prime objective of the ESCB and therefore of the ECB, is price stability. This concept was originally specified by the Executive Board of the ECB as an annual increase of less than 2% in the inflation rate over the medium term, measured by the Harmonized Index of Consumer Prices (HICP) for the euro area. This paper examines to what extent the ECB has been effective in realizing price stability over the period from January 1, 2000 to December 31, 2022. Price stability is important for economic agents. It allows them to plan their savings, spending and investment eventually resulting in sustained economic growth.   Notwithstanding the commitment of large human and other resources and the use of unconventional monetary policies, the ECB did not realize its prime objective during a large part of this period. We conclude that putting too much confidence in DSGE-modeling as one of the methodologies to determine monetary policy, may have played an important role in the ECB not achieving its main statutory objective.

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.

In light of the events of 2020 and 2022, this study aims to examine the co-movements between the capital markets of the Netherlands (AEX), France (CAC 40), Germany (DAX 30), the United Kingdom (FTSE 100), Italy (FTSE MIB), Spain (IBEX 35), Russia (IMOEX), and spot prices of crude oil (WTI), silver (XAG), gold (XAU), and platinum (XPT) from January 1, 2018 to December 31, 2022. The purpose of this analysis is to answer the following research question: (i) Did the events of 2020 and 2022 increase the shocks between stock markets and WTI, XAG, XAU, and XPT prices? The findings indicate that time series do not follow a normal distribution and are stationary. In response to the question of investigation, we found that during the Tranquil period, it was possible to verify the existence of 28 causal relationships (out of 110 possibilities). During the stress period, there was a very significant increase in the number of causal relationships between the market pairs under analysis (62 causal relationships out of 110 possibilities), including a relative increase in the influence of commodities on capital markets and capital markets on commodities. These findings show that during the events of 2020 and 2022, capital markets and commodities significantly accentuated their co-movements among themselves, indicating that alternative markets such as WTI, XAG, XAU, and XPT do not provide safe-haven properties. These results have implications for portfolio diversification during times of global economic uncertainty.

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.

In the statistical standard of population aging adopted by the United Nations in 1956, the UN only focused on age, which is no longer a good statistical indicator in the context of deepening global population aging. To some extent, population aging is also the embodiment of social progress. This paper suggests improving the existing statistical standards of population aging to better adapt to the reality of social development.

Green innovation, as a sustainable development approach, can synergistically promote high-quality economic and social development. We select China's A-share-listed manufacturing corporations from 2011 to 2021 as the research sample to empirically study the impact of executive academic experience on green innovation in manufacturing corporations. Further, we test the relationship between executive academic experience and green innovation in manufacturing corporations under the mediating role of corporate social responsibility and the moderating role of heterogeneous environmental regulations. The study shows that (1) executive academic experience helps to promote green innovation in manufacturing corporations; (2) executive academic experience is conducive to promoting the fulfillment of social responsibility by manufacturing corporations; (3) corporate social responsibility plays a mediating role between executive academic experience and green innovation in manufacturing corporations; (4) environmental regulation positively moderates the relationship between executive academic experience and green innovation in manufacturing corporations, and both formal environmental regulation and informal environmental regulation positively moderated the promotion of green innovation in manufacturing corporations by executive academic experience.

We employ the joint production decomposition model to conduct a full decomposition of CO2 emission among 36 industrial sectors in China from 1998 to 2011, under the framework of growth accounting. The results show that: (1) the average CO2 emission increases at an annual rate of 3.01%, and production technology progression is the main driving force, while the transformation toward clean production effectively curb the rapid growth of CO2 emissions; (2) the effect of technology changes on CO2 emission is larger during the "10th Five-Year Plan" compared with the "11th Five-Year Plan", which makes the annual growth rate of CO2 emission during the "11th Five-Year Plan" 1% lower than its counterpart; This study has important theoretical and practical significance for understanding the driving factors of CO2 emission and the corresponding emission reduction measures.

Under the background of digital economy, global tax governance has become one of the important topics in today's world development and change. In recent years, new challenges, such as tax base erosion and profit transfer, and the imbalance of cross-border tax source division, have become prominent, forcing the reform of international tax rules and the reshaping of international tax order. Based on this, the article first deeply digs into the scale and cross-border characteristics of the spatial-temporal aggregation of the digital economy, and comprehensively evaluates its impact on the global tax governance pattern. After that, the article combs out the realistic picture and challenges of the current digital tax reform from the aspects of theoretical basis, basic principles and governance mechanism. Finally, based on China's basic national conditions, the article puts forward some institutional ideas and policy suggestions, with a view to improving China's participation, voice and influence in global tax governance, and also enabling governments, enterprises and residents of various countries to enjoy the fruits of world economic development fairly and promote the construction of Community of Shared Future for Mankind.

Trust beneficiary protection constitutes an important legal system in the trust industry. This paper, based upon the study approach of the “Theory of Law and Finance”, establishes the trust beneficiary protection index of China. We also test the influence of trust beneficiary protection on the performance of trust companies. As indicated by our study’s results, an “inverted U-shaped” relationship exists between the degree of trust beneficiary protection and the performance of trust companies. In a period when the trust law system has not yet been well established, strengthening trust beneficiary protection could help facilitate the growth of trust company performance. However, this facilitation effect gradually diminishes as the trust law system becomes more perfect. This in turn means that, after reaching a certain peak, conferring the beneficiary with more rights of supervision and participation would cause the performance of trust companies to decline. Improving regional legal environments could also help facilitate the growth of trust company performance. In addition, this facilitation effect is subject to the influence of the nature of trust company controllers. In trust companies controlled by local state-owned capitals, we find that the facilitation effect of the improvement of regional legal environments on trust company performance is inhibited. In trust companies controlled by non-state-owned capitals, however, the facilitation effect of the improvement of regional legal environments on trust company performance is enhanced.

Noninvasive acquisition of deep tissue temperature has important applications in home health monitoring, hyperthermia safety control, and other domains. In this work, we present here a novel magnetically mediated thermoacoustic temperature measurement method. Utilizing coil to stimulate amplitude modulated magnetic field and ultrasound transducer to receive the generated thermoacoustic wave from the inserted magnetic nanoparticles. Benefiting from the high sensitivity of thermoacoustic emission from nanoparticles and the deep penetration capability of both magnetic field and ultrasound propagation, the proposed thermoacoustic temperature measurement system enables a high measurement accuracy of 0.5 degrees Celsius in real time. This work potentially facilitates further development of closed loop magnetic hyperthermia for practical clinical applications.

Protein S-nitrosylation (SNO), emerging as an important posttranslational modification, involves covalent addition of nitric oxide (NO) to the sulfur atom of cysteine in proteins. Accumulated evidence suggests that protein SNO plays crucial roles in pathophysiological mechanisms in cancer, which is attracting great attention. However, there are still controversies about whether S-nitrosylated proteins act as oncogenic proteins or tumor suppressors in cancer. In this review, we provide an overview of the early and latest evidence regarding the underlying mechanism and dual roles of SNO in cancer, in an effort to clarify its contribution in tumor progression. It has been well established that S-nitrosylated proteins restrain tumor progression in several types of cancer, while they have exhibited activities in promoting cell proliferation and inhibiting apoptosis in some other kinds of cancer. Interestingly, emerging evidence also has highlighted both its anti-cancer and pro-tumorigenic roles in several other cancer diseases. Finally, current limitations and future research prospects are presented. The overview of targeting SNO in cancer will provide new opportunities for drug development through in-depth exploration of SNO-mediated signaling pathways.

The rapid growth of renewable solar and wind energy necessitates extensive, long-term energy storage solutions to stabilize the electric grid and address the intermittent nature of these sources. In the absence of cost-effective long-duration, large-scale (LDLS) energy storage, there is a risk of increased disruptive blackouts and brownouts as intermittent energy sources approach 50% of electricity generation. Our analysis underscores volumetric energy density as a pivotal determinant in LDLS energy storage solutions, which is particularly crucial during periods of diminished renewable resource availability, such as the rainy season. Despite emphasis on conventional electric batteries and mechanical storage technologies such as compressed air and pumped hydro for LDLS, their costs pose a significant obstacle to widespread adoption, especially in emerging economies. In this study, we present a groundbreaking approach to LDLS: on-demand electricity generation from carbon-neutral renewable oil, known as "green oil," leveraging Reliance’s innovative catalytic hydrothermal liquefaction (R-CAT-HTL) technology. Our investigation evaluated two distinct sources of green oil production: organic waste streams (e.g., municipal solid waste, agricultural-waste, etc.) and on purpose production of algal biomass. We demonstrate that burning renewable green oil to produce electricity offers a cost-effective solution for large-scale (GWh) long-duration (many days) energy storage, ensuring the stability, reliability, and resiliency of the electric grid. We also demonstrate that minimum 14 days, ideally 30 days energy storage is needed for continuous uninterrupted service, especially critical for manufacturing facilities. Through a meticulous levelized cost of storage (LCOS) analysis comparing green oil with other LDLS technologies reported in literature, we demonstrate the cost effectiveness of green oil. In this model, green oil serves as stored energy, functions akin to a battery and is efficiently converted into electricity through conventional reciprocating engines or next-generation more efficient turbines. Our findings suggest that green oil derived from diverse organic sources is the most economically viable option for GWh-scale storage, particularly when storage requirements extend beyond a single day. This research thus presents a transformative cost-effective solution to the pressing challenge of LDLS energy storage, accelerating a sustainable and resilient energy future.