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.

In this paper, we develop a model in which a monopolistic firm manufactures and sells a digital product, by incorporating digital rights management (DRM), quality degradation of pirated products, and government copyright enforcement into the consumer’s utility function. We determine the monopolist’s optimal pricing strategies and the appropriate DRM protection level through mathematical deduction. Our results show that when the government copyright enforcement is moderate and the quality of pirated products is relatively high, implementing a DRM system is optimal for the monopolist. However, in most other cases, DRM-free is better for the monopolist. This result may explain why DRM is not very popular in some industries. Our results suggest that choosing the right price, focusing on content innovation, and weakening DRM protection may be a better strategy for firms now. The results also indicate that DRM-free may be more prominent in the digital music industry than in the software and video games industries.

This paper examines the efficiency, in its weak form, of the clean energy stock indices, Clean Coal Technologies, Clean Energy Fuels, and Wilderhill, as well as the cryptocurrencies classified as "dirty", due to their excessive energy consumption, such as Bitcoin (BTC), Ethereum (ETH), Ethereum Classic (ETH Classic), and Litecoin (LTC), from January 2020 to May 30, 2023. In order to meet the research objectives, the aim is to answer the following research question, namely whether: i) the events of 2020 and 2022 accentuated the persistence in the clean energy and dirty energy indices? The results show that clean energy indices such as digital currencies classified as "dirty" show autocorrelation in their returns; the prices are not independent and identically distributed (i.i.d). In conclusion, arbitrage strategies can be used to obtain abnormal returns, but caution is needed as prices can rise above their real market value and reduce trading profitability. This study contributes to the knowledge base on sustainable finance by teaching investors how to use forecasting strategies on the future values of their investments.

The digital transformation of manufacturing industry can promote the development of green transformation and promote the differentiation of workers’ skill structure; On the other hand, it will also hinder the green development due to the huge energy consumption generated by the application of digital technology and facilities. In addition, the green transformation of manufacturing industry will also have differentiated impacts on the employment of labour with different skills due to the innovation of green technology. The existing research has not discussed too much about the interaction among the digital transformation and green transformation in manufacturing industry and labour structure. So, this paper uses the PVAR model to examine the dynamic relationship between digital and green transformation within the industrial sector from the perspective of labour structure, specifically analyzing the impact difference across regions. The results suggest that there is a reciprocal connection between the digitization of manufacturing sector and the labour structure, particularly in the eastern region of China, but the overall interaction between the two remains weak. The interactive between the green transformation of manufacturing industry and the labour structure in the central and western areas has been delayed over periods 1-6. Digital and green manufacturing transformation reinforce each other in central and western regions. However, the digital revolution in the manufacturing industry is hindered by the green transformation in eastern region.

A differences-in-differences (DID) model and financial data from Chinese listed firms from 2011 to 2019 are used to empirically investigate the effects of the digital economy on corporate financial asset holdings using the "Broadband China" policy as a quasi-natural experiment. After robustness testing and heterogeneity effects are disposed of, the digital economy dramatically boosts corporate financial asset holdings. According to the channel analysis, the digital economy can reduce corporate financing constraints and boost corporate financial asset holdings, notably based on speculative demand. Heterogeneity analysis shows that the digital economy has a greater impact on corporate financial asset holdings for firms with higher market competition, small-scale firms with a short-listed age, and firms in the western region. This paper provides policy guidance for enterprises returning to the real economy.

Based on China's 30 provincial panel data from 2006 to 2018, this paper uses the spatial Durbin model to empirically study the influence path and transmission mechanism of financial development on regional technological innovation, and introduce digital finance environment, marketization degree, and government environmental management as an adjustment variable to verify its regulating effect on financial development and regional technological innovation. The study found that the overall promotion of digital finance to local technological innovation is not significant. Besides, the characteristics of ownership discrimination and weak risk appetite in the bank's medium and long-term credit market have led to its failure to promote regional technological innovation. In contrast, the stock market and bond market in direct financing channels have enhanced local innovation capabilities. When the external environmental system is used as the adjustment variable, the results show that an excellent digital finance development, marketization degree, and government environmental management can effectively and positively regulate the effect of financial development and technological innovation.

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 study examined the determinants of the exchange rate in a mono-resource economy, during the period of currency and oil price fall in Nigeria. The aim of the study is to ascertain the potentiality of economic diversification (non-oil export) in saving the falling value of the domestic currency, as well as, its stability. The study employed the use of monthly data from the Central Bank of Nigeria and Nigeria National Petroleum Corporation from January 2008 to December 2020 using the ARDL and NARDL models to achieve the stated objectives. In the literature, several empirical studies analyzed the relationship between exchange rates, oil price, and oil export and came to the logical conclusion that a rise in the price of oil would bring about a rise in the exchange rate, all things being equal while the reverse is the case. To add to the existing body of knowledge this study did not only look at the relationship between the variables but also examined the determinants of the exchange rate in a mono-resource economy and ascertained the potentiality of economic diversification in bringing succor to the falling exchange rate in the midst of falling oil price. The NARDL result corroborates the findings of previous studies on the relationship between exchange rate, oil price, and the performance of non-oil export. It maintains that positive changes in oil prices would lead to the appreciation of domestic currency while negative changes in oil prices would lead to the depreciation of the domestic currency. With this analysis, the study recommends the diversification of the economy and revitalization of the non-oil sector. Since import proves to have a negative impact on the exchange rate, the revitalization of the non-oil sector stimulates domestic consumption and thus reduces import bills which raise the demand for the dollar and weakens the naira.

The study investigates the impact of COVID-19 on African exchange rates, employing a panel dataset over the period 2016-2022 from 13 African economies and employing pooled OLS estimator. The findings reveal a noteworthy positive correlation between COVID-19 levels and exchange rates within the region. However, this association necessitates deeper exploration due to its multifaceted implications, including economic disruptions, government interventions, global market interconnections, regional stability perceptions, and investor behavior. Economic indicators, such as GDP, inflation rate, real interest rate, and unemployment rate, significantly influence exchange rates. While GDP positively impacts exchange rates through economic growth, investor confidence, and trade strength, controlled inflation fosters investor confidence and export competitiveness, positively affecting exchange rates. Moreover, a pronounced positive impact of the real interest rate indicates economic stability, attracting investment and contributing to currency appreciation. Conversely, high unemployment negatively affects exchange rates, signaling economic weaknesses and eroding investor confidence. These findings emphasize nuanced policy responses for managing health crisis-induced economic disruptions and suggest future research directions focusing on specific country-level analyses and multifaceted factors influencing currency valuations within African economies.

The digital transformation provides an opportunity for the development of a green and low-carbon economy. This study used panel data collected from 30 Chinese provinces between 2011 and 2018, and assessed the impact of digitization (Dig) on environmental efficiency (EE). Quantile regression is employed to scrutinize the evolution of the marginal effect. From the perspectives of population and institutional factors, this study empirically investigates nonlinear relationships and potential mechanisms using Hansen threshold and mediation models. The findings reveal several key insights. Overall, levels of digitization and environmental efficiency (EE) are increasing with regional dispersion expansion, indicating a “polarization” characteristic. The impact of digitization on EE exhibits noticeable stage and regional heterogeneity. Analysis of population factors reveals that population structure, population size, and human capital trigger a sharp “marginal increase” of positive effects with single thresholds of 0.8155, 7.2284, and 11.0497, respectively. Analysis of institutional factors highlights the significance of fiscal policy quality (tax proportion), education expenditure, and tax system structure as important intermediaries. Finally, this paper presents corresponding policy implications.

Following the seminal paper on Optimum Currency Areas (OCA) by Mundell (1961) a wealth of literature has been published on the business cycles synchronisation and its main determinants. This work provides a systematic review of this research field both at country-level synchronization and regional level. The paper aims to evaluate the contribution of the related literature’s methodologies to the measurement of the business cycle and the estimation of the level of synchronization. The discussion of the collected papers is expected to substantially assist researchers, practitioners, and policy makers keen to employ themselves in the area of business cycles synchronisation.

Speeding up digital development and building "digital China" is an important strategic deployment of the "14th Five-Year Plan" and a concrete measure to promote the high-quality development of China's sports industry and national health. Based on provincial data in China from 2011 to 2019, an empirical model is used to analyze the relationship between digital construction, sports industry development and national health investment. The results show that digitalization is instrumental for sports industry development and the improvement of national health in China. Digitalization has promoted the healthy development of sports industry and national health by increasing the input of public science and technology.

Non-compliance with tax obligations, particularly by wealthy taxpayers and large corporations, continues to represent a source of social injustice that fuels social instability, especially in developing countries. Understanding the strategies of tax evasion and avoidance is of critical importance. This article highlights five main strategies used by large corporations and wealthy taxpayers to avoid taxes, including tax havens, the underground economy, aggressive tax optimization, alternative financial markets, and crypto currencies. We also propose several actions to tackle global tax non-compliance, including prevention, peer reporting, active monitoring of compliance indicators and inter- national cooperation. These actions can be combined to achieve optimal results in reducing tax evasion and avoidance.

Economy has various stages which have been described as economic cycle and due to that the circulatory movement observed, some have faster cycle some have longer cycle which depends on numbers of factors and from that inflation is an important segment. Various terms have been described for inflation, in simple meaning when price of different commodities have been raised compared to previous stage due to depreciation of currency having lesser purchasing power. Perception of people towards inflation and its impact is the main crux of the study, because how the people think about technical terms is vital matter. The present study is based on primary data collected from 277 respondents through questionnaire from the Gujarat state India. The perception has been analysed from four statement have been asked in Lickert’s five scale form. The one-way ANOVA has been used to test the hypotheses and it has been found from that in first statement regarding price of commodity once increase then it will not decrease due to inflation has significant difference with place, education and age of the respondents and in rest three statement no significant differences have been observed.

Innovation has received a great attention in the creative industries literature. We propose in this study a bibliometric method to examine the literature on innovation in creative industries (ICI). A file of 656 manuscripts published on ICI between 1998 and 2022 was retrieved from the Web of Science Core Collection for analysis. The results highlight the evolution of study volume, authors, affiliated institutions and countries, author networks, keyword co-occurrences, and keyword networks. The study also includes a thematic map that highlights four types of research: driving themes (e.g., digital technology, cultural innovation, performing arts, product innovation, innovation management); core and cross-cutting themes (e.g., creativity, digitization, technology, copyright); emerging themes (e.g., gender, artificial intelligence, sustainability); and specialized and peripheral themes (e.g., gender, blockchain, digital music). We finally conclude by proposing future perspectives and a research agenda in this area.

Current societal challenges related to retirement planning, healthcare systems’ evolution and environmental changes require households to pay a closer attention to their personal finances. This in turns calls for the associated industry to transform and scale. To do so, the personal finance industry could potentially leverage artificial intelligence tools for which there has been increasing levels of chatter. However, there is, to my knowledge, little consensus on whether or not those tools are appropriate given the challenges ahead. The literature review at the heart of this article first suggests that the stream of personal finance where transformation is more than needed is the one pertaining to investments, rather than the ones associated to loans, insurances or payments. Second, the productivity levers fueling the transformation of this branch are yet more driven, as of today, by simple digitalization notions rather by the usage of A.I. instruments. Over the next couple of years, more attention should thus be paid to use/business cases associated to investment products and the digitalization of their distribution chain.

This paper explores the transformative journey from traditional e-commerce to the emerging realm of virtual commerce (v-commerce) within the metaverse, a collective virtual shared space created by the convergence of virtually enhanced physical reality and physically persistent virtual reality. The metaverse, with its immersive and interactive capabilities, is reshaping the landscape of economic activities, creating a paradigm shift in the way consumers shop, sell, and buy goods and services. The study delves into the impact of virtual reality (VR) technologies on consumer behavior, business models, and the overall economy. It investigates how VR is revolutionizing the shopping experience by offering immersive, personalized, and interactive platforms, thereby influencing con-sumer decision-making processes. The paper further examines the implications of these changes for businesses, particularly in terms of strategy, operations, and customer engagement. Moreover, the paper discusses the challenges and opportunities presented by the metaverse economy, including issues related to privacy, security, digital divide, and regulatory frameworks. It also highlights the potential of v-commerce to drive economic growth, innovation, and sustainability in the digital age. The paper concludes with a discussion on the future directions of v-commerce and the potential strategies for businesses to thrive in this new economic landscape.

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.

As the COVID-19 epidemic swept the world in early 2020, it is worth watching how it affects the total factor productivity of enterprises. Based on the theory of information asymmetry and the data of A-share listed companies from 2014 to 2021, this paper conducts an empirical study on the relationship between COVID-19 and the total factor productivity of enterprises. The results show that the impact of the COVID-19 epidemic can significantly reduce the total factor productivity of enterprises, and the conclusion is still true after a series of robustness tests. Taking the financing constraint as an intervening variable, it clearly reveals a transmission mechanism, that is to say, the impact of the COVID-19 epidemic exacerbates the financing constraint of the enterprise, thus it makes the total factor productivity of the enterprise reduce. It is further found that the above effects are more obvious for small and medium-sized enterprises and non-intelligent enterprises. Based on this, the government should implement some active economic development policies to create a free, relaxed and orderly market environment for enterprise financing. At the same time, enterprises should not only pay attention to digital and intelligent development, and transform into technology-intensive enterprises, but also strengthen the awareness of worry. Enterprises should store "more grain" for preparing for the cold winter.

This paper provides a thorough review of the shifting landscape of economic analysis, spotlighting recent trends and predicting future paths. While traditional economic models remain key for interpreting economic activity, they are being supplemented by fresh methods and cross-disciplinary viewpoints. The increased attention to inequality studies, using advanced statistical techniques and unique data sources, underscores the growing emphasis on fairness and distribution within economic analysis. The incorporation of behavioral elements into economic models also expands our comprehension of economic decision-making and market results. Notably, the emergence of computational economics-integrating artificial intelligence (AI), big data, and machine learning into economic scrutiny-represents a major development. Often referred to as ’smart economics,’ this field employs technology to formulate, address complex economic dilemmas, and perceive economic activity in unconventional ways. Yet, the application of AI and machine learning in economics introduces new hurdles around data privacy, algorithmic bias, and the transparency of model outcomes. The impact of the digital revolution on economic analysis is significant, as the advent of computational economics and the surge of big data are transforming research techniques and policy implications. Concurrently, the advent of the circular economy indicates a radical shift in our perspective on economic sustainability, carrying considerable implications for environmental policy and business tactics.  In the future, it’s anticipated that these trends will further modify the realm of economic analysis, with AI and machine learning integration, emphasis on sustainability and fairness, and the influence of big data becoming more pronounced. As these changes take place, it’s imperative for researchers, policymakers, and practitioners to remain adaptable and flexible, prepared to capitalize on the opportunities and tackle the challenges these trends present.