Anhui University of Finance and Economics

Abstract This study seeks to estimate the carbon implications of recent changes in China’s economic development patterns and role in global trade in the post-financial-crisis era. We utilised the latest socioeconomic datasets to compile China’s 2012 multiregional input-output (MRIO) table. Environmentally extended input-output analysis and structural decomposition analysis (SDA) were applied to investigate the driving forces behind changes in CO 2 emissions embodied in China’s domestic and foreign trade from 2007 to 2012. Here we show that emission flow patterns have changed greatly in both domestic and foreign trade since the financial crisis. Some economically less developed regions, such as Southwest China, have shifted from being a net emission exporter to being a net emission importer. In terms of foreign trade, emissions embodied in China’s exports declined from 2007 to 2012 mainly due to changes in production structure and efficiency gains, while developing countries became the major destination of China’s export emissions.

Abstract With the implementation of China’s top-down CO2 emissions reduction strategy, the regional differences should be considered. As the most basic governmental unit in China, counties could better capture the regional heterogeneity than provinces and prefecture-level city, and county-level CO2 emissions could be used for the development of strategic policies tailored to local conditions. However, most of the previous accounts of CO2 emissions in China have only focused on the national, provincial, or city levels, owing to limited methods and smaller-scale data. In this study, a particle swarm optimization-back propagation (PSO-BP) algorithm was employed to unify the scale of DMSP/OLS and NPP/VIIRS satellite imagery and estimate the CO2 emissions in 2,735 Chinese counties during 1997–2017. Moreover, as vegetation has a significant ability to sequester and reduce CO2 emissions, we calculated the county-level carbon sequestration value of terrestrial vegetation. The results presented here can contribute to existing data gaps and enable the development of strategies to reduce CO2 emissions in China.

Along with the development of Fintech, many scholars have studied how information technology is applied to financial services with a focus on extended methods for application. Few scholars have studied the influence mechanism behind the adoption of Fintech services. This paper proposes an improved technology acceptance model (TAM) that incorporates user innovativeness, government support, brand image, and perceived risk as determinants of trust to investigate how users adopt Fintech services. We designed a questionnaire, sent it to active customers of the Hefei Science and Technology Rural Commercial Bank, and obtained 387 eligible responses. We analyzed the data with a structural equation model (SEM) to test the hypotheses, including the relationships of all latent variables. The results reveal that users’ trust in Fintech services has a very significant influence on users’ attitudes for adoption. In addition, perceived ease of use and perceived risk does not affect users’ attitudes toward the adoption regarding Fintech services. This study contributes to the literature of the adoption of Fintech services by providing a more comprehensive view of the determinants of users’ attitudes by combining trust of Fintech services with TAM.

Abstract Under the growing threats of climate change, innovation and pollution reduction have become driving forces for cleaner economic growth and the environment. This study endeavors to analyze the effect of economic complexity—understood as structural transformation toward more sophisticated and knowledge‐based production, economic progress, renewable energy consumption, and population growth over carbon emissions. Our study employs panel data for a sample of 28 OECD countries covering the period of 1990–2014. The main contribution to the energy economics literature is given by bringing together the concept of environmental degradation and economic complexity controlling via renewable energy consumption and economic and population growth. Based on the extensive empirical analysis (augmented mean group estimator, panel cointegration, and panel regression techniques), we conclude that economic complexity and renewable energy might help in mitigating the environmental degradation problems in OECD countries.

As fundamental data, gross domestic product (GDP) and electricity consumption can be used to effectively evaluate economic status and living standards of residents. Some scholars have estimated gridded GDP and electricity consumption. However, such gridded data have shortcomings, including overestimating real GDP growth, ignoring the heterogeneity of the spatiotemporal dynamics of the grid, and limited time-span. Simultaneously, the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) and National Polar-orbiting Partnership's Visible Infrared Imaging Radiometer (NPP/VIIRS) nighttime light data, adopted in these studies as a proxy tool, still facing shortcomings, such as imperfect matching results, discontinuity in temporal and spatial changes. In this study, we employed a series of methods, such as a particle swarm optimization-back propagation (PSO-BP) algorithm, to unify the scales of DMSP/OLS and NPP/VIIRS images and obtain continuous 1 km × 1 km gridded nighttime light data during 1992-2019. Subsequently, from a revised real growth perspective, we employed a top-down method to calculate global 1 km × 1 km gridded revised real GDP and electricity consumption during 1992-2019 based on our calibrated nighttime light data.

Abstract Information technologies exist to enable us to either do things we have not done before or do familiar things more efficiently. Metaverse (i.e. extended reality: XR) enables novel forms of engrossing telepresence, but it also may make mundate tasks more effortless. Such technologies increasingly facilitate our work, education, healthcare, consumption and entertainment; however, at the same time, metaverse bring a host of challenges. Therefore, we pose the question whether XR technologies, specifically Augmented Reality (AR) and Virtual Reality (VR), either increase or decrease the difficulties of carrying out everyday tasks. In the current study we conducted a 2 (AR: with vs. without) × 2 (VR: with vs. without) between-subject experiment where participants faced a shopping-related task (including navigating, movement, hand-interaction, information processing, information searching, storing, decision making, and simple calculation) to examine a proposed series of hypotheses. The NASA Task Load Index (NASA-TLX) was used to measure subjective workload when using an XR-mediated information system including six sub-dimensions of frustration, performance, effort, physical, mental, and temporal demand. The findings indicate that AR was significantly associated with overall workload, especially mental demand and effort, while VR had no significant effect on any workload sub-dimensions. There was a significant interaction effect between AR and VR on physical demand, effort, and overall workload. The results imply that the resources and cost of operating XR-mediated realities are different and higher than physical reality.

As a major carbon dioxide-emitting country, China set carbon trading market to reduce enterprise carbon emissions through the rational allocation of carbon quotas among different enterprises and regions. The market has also conducted a preliminary exploration for the country to achieve carbon dioxide emissions peak in 2030 and carbon neutrality in 2060 while actively addressing the challenges of global climate change. This study analysed the emission reduction effect of China's carbon trading pilot policy, especially the role of carbon quota and carbon trading price. The analysis used county-level panel data from 1997 to 2017, regarded the implementation of the carbon trading pilot policy as a quasi-natural experiment, and used the difference-in-differences method. The results showed that, first, the policy implementation not only reduced regional carbon emissions but also inhibited carbon dioxide emissions per capita, with long-term effects. Second, the carbon emission reduction effect brought by the carbon pilot policy showed significant heterogeneous results with the different degrees of regional carbon emissions and environmental supervision. The effect was greater in areas with higher carbon emission density and stronger legal supervision. Third, the difference in carbon quota allocations resulted in different emission reduction effects, among which the historical method had the strongest effect. The carbon quota price and number of enterprises participating carbon trading market were the key factors affecting carbon emission reduction.

Abstract China has entered the economic transition in the post-financial crisis era, with unprecedented new features that significantly lead to a decline in its carbon emissions. However, regional disparity implies different trajectories in regional decarbonisation. Here, we construct multi-regional input–output tables (MRIO) for 2012 and 2015 and quantitatively evaluate the regional disparity in decarbonisation and the driving forces during 2012–2015. We found China’s consumption-based emissions peaked in 2013, largely driven by a peak in consumption-based emissions from developing regions. Declined intensity and industrial structures are determinants due to the economic transition. The rise of the Southwest and Central regions of China have become a new feature, driving up emissions embodied in trade and have reinforced the pattern of carbon flows in the post-financial crisis period. Export-related emissions have bounced up after years of decline, attributed to soaring export volume and export structure in the Southeast and North of the country. The disparity in developing regions has become the new feature in shaping China’s economy and decarbonisation.

The adoption of Sustainable Development Goals (SDG) in 2015 shifted the attention towards sustainability-related concerns in both developing and developed counties. The aim of this paper is to examine how agricultural productivity – a key driver in achieving many of these SDGs – is affected by carbon emissions, deforestation, renewable energy consumption, natural resources, and regional integration for the ten Association of Southeast Asian Nations (ASEAN) countries. Using the Mean Group (MG) class estimators, able to tackle the cross-sectional dependence in the data, empirical findings reveal that environmental degradation (in the form of CO2 emissions) reduces agricultural productivity in the region. Both the forest area and natural resource variables negatively affect the productivity of the agricultural sector, while the use of renewable energy sources positively contributes to the agricultural sector. However, despite being one of the highest integrated regions in the world, regional integration among the ASEAN members does not boost their agricultural productivity. The causality tests confirm the existence of bidirectional causality between agricultural productivity and renewable energy consumption, and unidirectional causality across a few other variables. Accordingly, the study provides policy recommendations for the governments of ASEAN economies on improving the environmental performance of agriculture and achieving the SDGs by 2030.

The paper seeks to explore the role of green finance in achieving sustainable development goals through the case of China, and address some issues of sustainable finance and environmental, social and governance concerns of green finance by introducing the episodes of green finance in China. This paper aims to provide some viewpoints about the following questions: 1) What are the latest trends in green finance? 2) What are the main challenges to the development of green finance? 3) What are policy recommendations for the development of green finance? 4) What are the roles of both the public and private sectors in promoting green finance? This paper identifies the mainstream to sustainable bonds, diversification of green finance, transition of corporates' business models, transparency and disclosure, and harmonizing taxonomy and measurement of green finance for the emerging trends of green finance. As the results, this paper recommends some policy measures for the private sector such as greening the banking system, greening the bond market, and greening institutional investors. This paper also suggests some policy initiatives for the public sector such as developing policies and capacity, promoting market transparency and governance, and promoting private-public partnership for diversifying resources of green finance.

The current study aims to explore the role of environmental taxes and regulations for the renewable energy consumption, focusing on reporting policy suggestions to overcome climate change issues and achieve environmental sustainability. The main objective of this paper is to examine the relation between renewable energy, environmental taxes, environmental technologies, and environmental regulations in 29 OECD countries during 1996–2018. More precisely, we inspect the impact of the environmental regulations and environmental technologies on the renewable energy consumption. The authors employ CIPS and CADF unit root tests, panel Westerlund co-integration test, FMOLS, and Quantile regression methods for the econometric analysis. The econometric analysis suggests that the environmental regulations impede the renewable energy consumption in OECD economies. The study suggests that environmental policy initiatives should focus on implementing environmental strategies to inspire cohesiveness between environmental regulations and the development of environmental technologies in order to promote the renewables industry in the developed countries.

Attaining sustainable development and cleaner production is a major challenge both for developed and developing economies; income, institutional regulations, institutional quality and international trade are the key determinants of environmental externalities. The current work attempts to study the role of environmental taxes and regulations on renewable energy generation for developed economies. For that, the authors have used the annual dataset for the period 1994 to 2018. More specifically, the study investigates the impacts of environmental taxes, environment-related technologies and the environmental policy stringency index on renewable electricity generation in 29 developed countries. Given the short available data of these countries, the authors have developed panel cointegration and panel regressions models (fully modified ordinary least square (FMOLS), quantile regressions). The heterogeneous panel empirics stated that environmental regulations and income level support renewable electricity generation. The conclusions further mention that bureaucratic qualities such as decision making and trade openness tend to reduce renewable energy generation. The empirical findings allowed us to draw new narrative and implications. Overall, the conclusions argue that innovative regulations and policies can be useful for attaining specific sustainable development goals (e.g., SDG-7: cleaner and cheap energy).

Global production fragmentation generates indirect socioeconomic and environmental impacts throughout its expanded supply chains. The multi-regional input-output model (MRIO) is a tool commonly used to trace the supply chain and understand spillover effects across regions, but often cannot be applied due to data unavailability, especially at the sub-national level. Here, we present MRIO tables for 2012, 2015, and 2017 for 31 provinces of mainland China in 42 economic sectors. We employ hybrid methods to construct the MRIO tables according to the available data for each year. The dataset is the consistent China MRIO table collection to reveal the evolution of regional supply chains in China's recent economic transition. The dataset illustrates the consistent evolution of China's regional supply chain and its economic structure before the 2018 US-Sino trade war. The dataset can be further applied as a benchmark in a wide range of in-depth studies of production and consumption structures across industries and regions.

This paper examines the relationships among environmental regulations (ER), staff quality (SQ), R&D efficiency (RDE), green technology (GT), and profit. The research sample comprises 1197 firms in 16 manufacturing industries in China, during 2008 and 2015. DEA-based measures are employed to research firm RDEs, and the results show that SQ is essential for high RDE and GT (as expected), but the main effects of SQ are mixed. Importantly, we find that ER moderates the SQ-GT, SQ-RDE and SQ-profit relationships. Specifically, if ERs are eased, SQ is of limited benefit to GT or profit. However, at or above the ER threshold level, firms can improve SQ for further improvements in GT and profit. The implications of our findings on theory and practice are also discussed.

Transport infrastructure connectivity (TIC) has strong endogeneity issues, making it difficult to directly assess its impact on local conflict resolution. This study presents new evidence of the effects of TIC on conflict resolution by conducting a natural experiment and applying machine learning methods to overcome the endogeneity issue. Based on global conflict data from 2010 to 2017, the empirical results show the following: (1) TIC can significantly improve countries’ global ranking for conflict resolution; in particular, the marginal benefit of developed countries is greater than that of developing countries. (2) The mechanism behind this effect is the promotion of trade facilitation, a more balanced employment ratio across genders, and improved income levels through TIC, which further enhances the conflict governance capacity of countries. In light of the findings, policy-makers should consider the opportunity to combine TIC with greater security for the realization of economic and social benefits, taking into account the significant opportunities for developing countries and the importance of balance across genders and income levels.

During the past decades, environmental related taxes, energy, and carbon taxes has been recommended by environmental scientists as a policy tool to mitigate pollutant emissions in developed and developing economies. Among developed nations, Denmark, Finland, Sweden, the Netherlands, and Norway were the first regions to adopt a tax on carbon dioxide (CO2) emissions and research into the impacts of carbon tax on carbon emissions bring significant implications. The prime objective and goal of this work is to explore the role of carbon tax reforms for environmental quality in European economies. This is probably the first study to conduct a comparative study in European context for carbon-tax implementation and non-implementation policies. To this end, the present study reports new conclusions and implications regarding the effectiveness of environmental regulations and policies for climate change and sustainability. In the present study, the authors exhaustively explore the impacts of the carbon-tax on the mitigation of CO2 emissions. Using the propensity score matching method, the results of the estimation of the different matching methods allow us to observe a positive and significant impact of the adoption of the carbon-tax on stimulating the reduction of carbon emissions.

Purpose Technical progress is an important technique within improving China’s comparative advantages, as new and renewable technologies will be beneficial for energy security. Productive technical progress and green technical innovation are necessary to improve working conditions and productivity of industries. Therefore, the purpose of this paper is to study technical progress in China under such harsh competitive circumstances, as well as types of technical progress that can be promoted, productive technical progress or green technology progress, and how technical progress will affect China’s competitive advantages. Design/methodology/approach The authors perform a multi-index multi-factor constitutive model based on a sample of 468 Chinese industries, and divide the industries into four categories. Findings The results indicate that there is a “U”-shape relationship between green technology progress and comparative advantages and an inverted “U”-shape relationship between the intensity of market competition and comparative advantages. Research limitations/implications China has crossed the inflection point of the “U”-shaped curve. This, coupled with the slowing of economic growth, demonstrates the need for advocating green technology in China to decrease the pollutant discharge. Establishing Chinese national brands within overseas markets and earning a profit through the downstream of production chain enhance China’s international competitiveness. Originality/value One of the most original findings of this paper points out that China is faced with a situation in which exports are severely decreased and domestic environment pollution is increased. Vigorous promotion of green technology progress, improvement of the quality and the technical content of exported products, the establishment of national brand within the overseas market, as well as enhancement of China’s international competitiveness, is needed.

By collecting and analyzing sample from 384 employees in China, this study explored relationship between responsible leadership and organization citizenship behavior for the environment (OCBE) with structural equation model (SEM). The results are as follows: (1) responsible leadership is positively related to organization citizenship behavior for the environment. (2) responsible leadership has positive effects on both autonomous and external environmental motivation. (3) autonomous and external environmental motivation have a multiple-mediate role in the relationship between responsible leadership and organization citizenship behavior for the environment. Finally, this paper discusses the management implications of the research results and the future research direction.

This study is trying to examine the different renewable energy sources and their impact on the economic growth at the state level under sustainable development goal seven (SDG-7). The SDGs goal (7th) defines the importance of clean, affordable and modern energy system in the World. Moreover, this study is attempting to increase the influence of sustainable energy consumption by employing dataset of selected Asian countries. This study uses annual panel data set and applies Augmented Mean Group (AMG), alongside Common Correlated Effects Mean Group (CCEMG) methods for data analysis. The overall results indicate the consumption of renewable energy sources have significantly contribution towards the economic prosperity of these economies. Furthermore, policy makers should focus on expansionary fiscal policies to enhance the use of environmental friendly power generation in these regions.

This study analyzes the effects of increased income and renewable energy on environmental quality, which has been ignored in the existing literature. An important contribution of this study is to analyze the role of renewable and nonrenewable energy in relation to the rising level of carbon emissions in the leading emitting countries. This research further examines the heterogeneous impacts of rising income levels and EKC investigation for CO2 emissions. The Kao cointegration, generalized method of moments (GMM), random effects, fixed effect (FE) regression models, and panel causality techniques are employed for panel data estimations. The empirical outcomes mention that an increase in income moderates the ratio of consumption of renewable energy to CO2 emissions. Increased income contributes more to the energy mix, which contributes to environmental pollution, through nonrenewable energy. This research reports policy-relevant critical masses beyond which an increase in income negatively affects the link between renewable energy and CO2 emissions.