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Improving energy efficiency is an effective way to address the issues of economic development, energy saving and emissions reduction. For any important industries it is therefore necessary to measure energy efficiency and set a practical target for it. In this paper, we use CCR, SBM and energy intensity to measure the energy efficiency of the paper industries of 22 EU countries. Results indicate that the SBM and CCR efficiency value is more meaningful for policy makers than that of energy intensity, as measurement results of energy intensity deviate from reality and economic efficiency. The CCR and SBM have roughly the same fluctuation trends and the average SBM energy efficiency value is 0.71, always 10 percent lower than CCR model, as it takes simultaneous account of both the optimal input-output and has more discriminatory power in efficiency measurement. Furthermore, EU policy makers could improve energy efficiency by raising energy prices. As for the 2030 EU target of energy saving and emission reduction, the EU should pay more attention to five major paper producers: Finland, Sweden, Germany, the United Kingdom and Italy.

This paper evaluates an editorial and seven invaluable and interesting review papers for the Journal of Risk and Financial Management (JRFM). The topics covered include the rising complexity of bank regulatory capital requirements from global guidelines to their United States (US) implementation, connections among big data, computational science, economics, finance, marketing, management and psychology, factors, outcome, and the solutions of supply chain finance, with a review and future directions, time-varying price-volume relationship, adaptive market efficiency, and a survey of the empirical literature, improved covariance matrix estimation for portfolio risk measurement, stock investment and excess returns, with a critical review in the light of the efficient market hypothesis, and a cross section analysis of country equity returns, and a review of the empirical literature.

The Journal of Risk and Financial Management (JRFM) was inaugurated in 2008 and has continued publishing successfully with Volume 11 in 2018. Since the journal was established, JRFM has published in excess of 110 topical and interesting theoretical and empirical papers in financial economics, financial econometrics, banking, finance, mathematical finance, statistical finance, accounting, decision sciences, information management, tourism economics and finance, international rankings of journals in financial economics, and bibliometric rankings of journals in cognate disciplines. Papers published in the journal range from novel technical and theoretical papers to innovative empirical contributions. The journal wishes to encourage critical review papers on topical subjects in any of the topics mentioned above in financial economics and in cognate disciplines.

Econometrics has had a distinguished start publishing over 92 articles since 2013, with 76,475 downloads.[...]

Lignin, the term commonly used in literature, represents a group of heterogeneous aromatic compounds of plant origin. Protolignin or lignin in the cell wall is entirely different from the commercially available technical lignin due to changes during the delignification process. In this paper, we assess the status of lignin valorization in terms of commercial products. We start with existing knowledge of the lignin/protolignin structure in its native form and move to the technical lignin from various sources. Special attention is given to the patents and lignin-based commercial products. We observed that the technical lignin-based commercial products utilize coarse properties of the technical lignin in marketed formulations. Additionally, the general principles of polymers chemistry and self-assembly are difficult to apply in lignin-based nanotechnology, and lignin-centric investigations must be carried out. The alternate upcoming approach is to develop lignin-centric or lignin first bio-refineries for high-value applications; however, that brings its own technological challenges. The assessment of the gap between lab-scale applications and lignin-based commercial products delineates the challenges lignin nanoparticles-based technologies must meet to be a commercially viable alternative.

In this short paper, we study the asymptotics for the price of call options for very large strikes and put options for very small strikes. The stock price is assumed to follow the Black-Scholes models. We analyze European, Asian, American, Parisian and perpetual options and conclude that the tail asymptotics for these option types fall into four scenarios.

The production of olives and olive oil in the Mediterranean region is one of the most important cultivation. The continuous changes of the European Common Agricultural Policy (CAP) towards strengthening the influence of market forces, has increased the necessity for assessing the efficiency of production protocols or patterns being implemented by the farmers. The case of olive trees cultivation, despite the fact that it is very important for both farmers and consumers, has not been in depth analyzed regarding the efficiency of inputs being used during the production process. This study evaluates the efficiency rates of 100 agricultural holding specialized on olive trees cultivation in Greece, by implementing a DEA input oriented model. The inputs being used are land, fertilizers, agrochemicals, labour, and energy. The output being used is the revenue of each holding. The results quantify the significant differentiation of efficiency scores, providing evidence that there is space for restructuring the production process, in order to improve efficiency and decrease by this way the production cost of inefficient farmers.

In recent years, Chinese manufacturing enterprises have competed to chase the wave of the “digital revolution”; digital empowerment has become an important strategic path of technological reform for many manufacturing enterprises. Based on the micro data of listed companies, this paper investigates the impact of digital transformation of Chinese listed companies on the quality of their export products. It is found that digital transformation can significantly improve the quality of enterprises’ export products. After a series of robustness tests, this conclusion is still valid, and there are two ways to improve innovation performance and total factor productivity. The export product quality enhancement effect of enterprise digital transformation also has the heterogeneity of ownership, region, and industry. Furthermore, this paper also examines the impact of digital transformation on the internal salary gap of enterprises, and finds that digital transformation may increase the internal salary gap of enterprises and form a “masking effect” on the quality of export products. To a certain extent, this paper deepens the understanding of the study of enterprise digital transformation on the quality of export products and its differences and provides certain guidance for enterprises to implement the strategy of digital transformation.

This review paper considers the disjuncture between the rapid pace of climate change and the more sluggish ability of cities to fully implement effective strategies of climate change adaptation and mitigation. We will refer to this as the ‘slow city–quick climate change’ dilemma. Climate change is accelerating, quickly rendering obsolete previous urban forms inadequate, while structural adjustments to cities are slower moving. Cities around the world were largely built for previous climate regimes. In the short to medium term, there is a mismatch between the climate regime that cities were designed for and the climate regime they now inhabit. The paper is divided into four parts: a brief review of climate change in general; climate change in cities; a review of climate change adaptation and mitigation in cities; and finally, a discussion of urban futures in the time of climate regime change.

As China put forward its “carbon emissions peak and carbon neutrality” goals, how to achieve carbon reduction had become a key for China’s goal. The manufacturing industry is an important source of carbon dioxide emissions. For a manufacturing country like China, adjustments in various aspects of the industry would have a huge impact on carbon emissions. As an important reform of contemporary production mode, the process of production automation in China will inevitably affect China's carbon emissions. Therefore, the analysis of the impact of production automation on carbon dioxide emissions was an important basis for judging the future carbon reduction in China. Refer to the traditional study of carbon Kuznets curve, this paper analyzed the impact of average wage on production automation and the role of production automation in the carbon Kuznets curve(CKC). This paper proposed that production automation plays a mediating role in the process of carbon emissions, and gives a verification model of the mediating role. By analyzing the relationship between average wage and production automation process, the U-shaped curve relationship between them was verified. By examining the relationship between carbon dioxide emission data and production automation industry in China, we verified that production automation plays a partial mediating role in the change of carbon Kuznets curve. Combined with the analysis of the two parts, this paper believed that with the continuous development of China's intelligent manufacturing industry, China's carbon reduction prospects were more optimistic, and there was a good industrial foundation to achieve the “carbon peaking and carbon neutrality” goals. Finally, this paper proposes policy suggestions as increase research investment in production automation, help promote the application of production automation, encourage the research and application development of low-carbon technology, especially encourage modular design, so as to give full play to the role of production automation in the process of carbon neutrality in China.

This paper examines the dynamic competition between platform firms in two-sided markets with network externalities. In our model, two platforms compete with each other via a contest to dominate a certain market. If one platform wins the contest, it can serve the market for a certain duration as a monopolistic platform. Our paper shows that platform firms can compensate for cost disadvantages with network effects. A head start (e.g., technological advantage) does not guarantee future success for platform firms. Network effects and cost efficiency are decisive for future success. Interestingly, higher costs of a platform can induce higher platform profits in our dynamic model. Moreover, we find that a platform’s size and profit are not necessarily positively correlated. Our model also provides new insights with respect to the underlying causes for the emergence of market dominance. The combination of technological carry-over and network effects can explain a long-lasting dominance of a platform that benefits from a head start. The necessary preconditions for this emergence are convex costs, small network effects and high carry-over.

The application of organic fertilizers plays a crucial role in achieving carbon sequestration in the agricultural sector. This paper discusses how farmers can more smoothly promote organic fertilizer extension services. An evolutionary game model is developed to describe the conflicting interests of Chinese farmers and local governments in organic fertilizer extension services, and the dynamic evolution of the game players and the influence of parameter adjustment on the strategic choices of both parties is presented. In this paper, the game model and the main results are validated with the help of simulation tools, and a sensitivity analysis of the selected parameters is performed. The results show that (1) the implementation of subsidy policy is less helpful for organic fertilizer extension services; (2) The ideal event probability of the game was found to be positively related to the cost of applying inorganic fertilizers, additional benefits to farmers, political returns to local governments, and penalties for not using organic fertilizers; (3) This is important for improving the performance of local governments, reducing government regulatory costs, improving policy support for organic fertilizer extension services, and reducing the cost of implementing organic fertilizer extension services.

The role of agricultural transport costs in core-periphery structures has habitually been ignored in New Economic Geography (NEG) models. This is due to the convention of treating the agricultural good as the numéraire, thus implying that agricultural transportation costs are assumed to be zero in these models. For more than three decades, this has been the standard setting in spatial equilibrium analysis. The paper examines the effects of agricultural transport costs on the spatial organisation of regional structures in Peru. In doing so, the Krugman’s formulation of iceberg transport costs is modified to introduce the agricultural transport costs into the dynamic of the NEG models. We use exploratory spatial flow data analysis methods and non-spatial and spatial origin-destination flow models to explore how the regional spatial structure change when real transportation data for agricultural goods is included into the iceberg transport costs formulation. We show that agricultural transport costs generate flows that are systematically associated with flows to or from nearby regions generating thus the emergence of spatial spillovers across Peruvian regions. The results of the paper support the contention that NEG models have overshadowed the role of agricultural transport costs in determining the spatial configuration of economic activities.

Energy poverty is high up on national and European Union policy agendas. A number of possible indicators to measure the issue have been identified in the literature, but comparable data with European coverage is scarce. The EU Commission thus proposes four independent indicators on the &ldquo, EU Energy Poverty Observatory&rdquo, based on self-reported items from the pan-European surveys on income and living conditions (SILC) and household budgets (HBS). It is of increasing public interest to analyse social impacts of energy policies, and quantify energy poverty indicators also from modelling. This paper first shortly outlines how the expenditure-based indicators using HBS micro data may be directly linked to existing macroeconomic models through their defining variables (energy expenditure and income). As endogenous modelling based on micro data is difficult, the link may be country-specific elasticities. The main contribution of the paper is a systematic in-depth sensitivity analysis of the two indicators to changes in income and energy expenditure following varying patterns in the underlying distributions of the micro data. The results may be used by future soft links to models. The results display sometimes counterintuitive effects. We find that whether these indicators increase/decrease after a change of income or energy expenditure largely depends on the specific country-wise income and energy expenditure distribution between households on a micro-level. Due to their definition, the examined indicators are especially sensitive, when income changes alter the indicator threshold values, which in these cases are the median values in underlying distributions. We discuss these findings and relate them to several indicator shortcomings and potential remedies through changes in indicator definition.

The results of empirical analyses confirm that analysed unsystematic factors, the Stock-to-Flow index (S2F), and information on the Bitcoin (BTC) are directly correlated with BTC values. These results are expected and in line with the economic theory, however, this research paper aimed to investigate the impact of unsystematic factors on the value of decentralised virtual cryptocurrency BTC. Its aim was also to analyse the reasons for significant oscillations of market values in relation to the S2F and S2FX model and thus confirm the reliability of these models in the estimation of BTC value. The research further confirms the strong influence of non-technical information directly linked with the BTC. The limitations of this paper are the lack of possibilities for examining the impact of non-technical information affecting the Bitcoin price deviation regarding the S2F model. In addition to all mentioned limitations, the research results indicate the relevance of the S2F and S2FX models and show a strong impact of (half) the information on the value of cryptocurrencies.

The social construction of the agri-food market has undergone revolutionary changes throughout history since the Anthropocene. This conceptual paper discusses the embeddedness of institutions in this market construction. To do so, this work analyses the geographical indication (GI) of agri-food market formation through the lens of critical theory. Through dialectics, it analyzes the historical process of agrarian systems’ shape according to their complexity, and the origins and effects of hegemonic interests in the construction of agri-food markets. Furthermore, this work shows how the market has evolved from different trade types as the capitalist system also evolved, changing the mechanics of trade and functions of food production. The results indicate that as agrarian systems evolved, food became more homogeneous and standardized in order to meet the demands of urban masses in capitalist economies. Regions where less complex systems predominate tend to hinder the creation, maintenance, and perpetuation of products such as GI, which may compromise their existence in the long run. Moreover, nations reproduce ideologically oriented interests according to the formation of dominant groups in each place, as also expressed in the agri-food market. This paper aims to provide new conceptual and theoretical insights into the institutional mechanisms and historical processes of agri-food market construction in terms of power interests.

This paper empirically examined relevant data on BRICS CO2 emissions, financial development, and economic growth in the past 40 years, and analyzed the correlation between them. Using the cointegration test, it found that there is a clear correlation between the variables in China and South Africa, which show that there is a two-way relationship between CO2 emissions, financial development, and economic growth in both countries. Using the quantile regression method in the analysis, the results demonstrated that at the 0.6th quartile, South Africa’s financial development had a negative impact on CO2 emissions, while Brazil’s CO2 emissions had a negative impact on financial development. Economic growth was subsequently added as a control variable, and the quantile-on-quantile regression method was used to test the correlation between the financial development of the BRICS countries and their CO2 emissions. Finally, based on empirical conclusions, this paper proposed that BRICS countries should focus on sustainable economic development; when government departments formulate emission-reduction policies, they must reasonably consider the relationship between financial development and emission-reduction policies.

In response to the inherent challenges of generating cost-effective electricity consumption schedules for dynamic systems, this paper espouses the use of GBM or Gradient Boosting Machine-based models for electricity price forecasting. These models are applied to data streams from the Irish electricity market and achieve favorable results, relative to the current state-of-the-art. Presently, electricity prices are published 10 h in advance of the trade day of interest. Using the forecasting methodology outlined in this paper, an estimation of these prices can be made available one day in advance of the official price publication, thus extending the time available to plan electricity utilization from the grid to be as cost effectively as possible. Extreme Gradient Boosting Machine (XGBM) models achieved a Mean Absolute Error (MAE) of 9.93 for data from 30 September 2018 to 12 December 2019 which is an 11.4% improvement on the avant-garde. LGBM models achieve a MAE score 9.58 on more recent data: the full year of 2020.

As was first stressed by the classical economists Adam Smith and David Ricardo, international trade plays a crucial role in the growth process. The paper aims to analyze the influence of foreign trade on economic performance in the wood processing industry (WPI) of Czechia and Slovakia. The multivariate regression method (MLR), assumption tests for MLR models, and Granger causality test were applied to identify association between foreign trade economic performance, and indicators were formed to measure the effects of foreign trade at the industry level. The Granger test revealed the unidirectional causality in the Slovak WPI and bidirectional causality in the Czech WPI. The results revealed that the net export growth has a positive effect on the economic performance of the industry, but only if the growth in imports is lower than in exports. The balanced trade balance indicated no influence of foreign trade on economic performance. The paper contributes to existing knowledge with indicators for evaluation of foreign trade effects on the performance of the industry. The paper also brings new empirical knowledge in trade balance effects on the economic performance of industries.

This paper reviews the low-resilience problem in many cities, poor designs of cities to cope with disasters, and the need for tolerance of urban constructions. It explores answers concerning the question of how shall we build cities resiliently? The method of this applied research is a multiphase process that considers all physical and socioeconomic elements of a city. It introduces six indicator groups of urban management (M), economy (E), built environments (U), Infrastructures (I), natural environments (N), and health protection (H). The groups include 55 indicators as variables in the mathematical calculations in this paper. This paper builds a mathematical model to maximize the profitability of resilient buildings by optimizing investments in the required projects. The projects will upgrade the firmness and tolerance of cities against nature-based and human-made dangers and risks. There is a linear programming in 55 variables to select optimal solutions from fifty-five factorial alternatives. Then, the programming will develop into non-linear programming. The unique innovation of this paper is its linear programming interpretation by non-linear to give optimal solutions for the problem. Applying the Lagrange function in the Kuhn-Tucker conditions proves the accuracy of the hypothesis that post-COVID urbanization requires maximum resilience. Only in this way, the urban economies will be free of risks. Outcomes in this paper will assist in the pre-planning, design, and building of built environments everywhere resilient and sustainable.

Recent times have witnessed an increasing number of countries and private firms pledging carbon neutrality by mid-century. Whilst representing a significant improvement in intentions to tackle climate change, such pledges lack substance and structure. For instance, individual pledges lack coordination and aggregation among peers, while strategies and measures to achieve ambitious targets are largely absent. Moreover, current disagreements obstructing progress in international climate change negotiations further undermine the reliability of carbon neutrality objectives. Effective international policies are needed to foster aggregate mitigation ambitions and the creation of adequate supporting mechanisms. This theoretical paper describes a governance innovation aimed at overcoming such shortfalls and disagreements through a unifying yet customizable pathway towards carbon neutrality. It does so by first outlining a political governance framework based on a climate club interpretation of Article 6 of the Paris Agreement. Secondly, it proposes carbon emission mitigation effort sharing on a per capita basis to ensure efficiency, equity and political feasibility. Thirdly, this paper describes how the supply of certified mitigations of carbon emissions required to satisfy effort sharing-based demand can be assetized as carbon credits by operationalizing Article 6 as a joint certification mechanism. The resulting governance architecture for managing demand and supply of mitigations shifts efforts to tackle climate change from a ‘problem-driven’ cost approach to ‘opportunity-driven’ value creation pathways towards carbon neutrality.

The most known and used abstract model of the financial market is based on the concept of the informational efficiency (EMH) of that market. The paper proposes an alternative which could be named the behavioural efficiency of the financial market, which is based on the behavioural entropy instead of the informational entropy. More specifically, the paper supports the idea that, in the financial market, the only measure (if any) of the entropy is the available behaviours indicated by the implicit information. Therefore, the behavioural entropy is linked to the concept of behavioural efficiency. The paper argues that, in fact, in the financial markets, there is not a (real) informational efficiency, but there exists a behavioural efficiency instead. The proposal is based both on a new typology of information in the financial market (which provides the concept of implicit information—that is, that information ”translated” by the economic agents from observing the actual behaviours) and on a non-linear (more exactly, a logistic) curve linking the behavioural entropy to the behavioural efficiency of the financial markets. Finally, the paper proposes a synergic overcoming of both EMH and AMH based on the new concept of behavioural entropy in the financial market.

To respond to global climate change and achieve a “carbon peak” and “carbon neutrality” as soon as possible has become a common goal around the world. Economic growth relies heavily on financial development, indeed, low-carbon economic development is inseparable from financial support. This paper studies the impact of financial development on carbon emission intensity and its mechanism from both theoretical and empirical aspects. Based on the 2005–2018 data on Chinese cities and the Spatial Durbin Model (SDM) research results, this paper finds that: (1) Financial development has significantly reduced China’s carbon emission intensity overall. After considering spatial effects, financial development increases local carbon emission intensity, although it may lead to a more significant decrease in the surrounding area. (2) The analysis of heterogeneity shows that only the financial development in the eastern region has a substantial detrimental impact on total carbon emission intensity and the carbon emission intensity of neighboring cities. The financial development in the central and western regions has no significant effect on carbon emission intensity. (3) The mechanism test shows that financial development mainly reduces carbon emission intensity through technological innovation and structural optimization, with the effect of technological innovation being 9.5%, and the effect of structural optimization being 12.15%. The expansion of the consumption effects of financial development has no significant impact on carbon emission intensity. Accordingly, this article believes that it is necessary to further support financial development, build large-scale financial centers, continue to optimize the structure of financial products, and encourage the development of green finance.

This paper investigates structural change in family farming in ten EU New Member States from Central and Eastern Europe which can be treated as a borderline between transition and developed economies. The paper proposes that farms using at least one Annual Work Unit (AWU) family labour are classified as family since it is considered that engaging less than one full-time family member may not show commitment to the family operation. The Oaxaca-Blinder decomposition is employed to analyse the drivers of structural change at a farm level, i.e., the extent to which it is technology or endowment driven. To compare the developments in different countries, the changes are presented in relative terms in order to reveal the relative distance travelled by the structural change in individual New Member States alongside the relative importance of technology and endowments changes. The estimation of a translog production function by country is used to derive the corresponding decompositions. Empirical analysis is based on data from the EU Farm Accountancy Data Network (FADN) for two time points—2007, when the last of the ten CEECs joined the EU—Bulgaria and Romania, and 2015 to investigate structural change during the first decade of EU membership. The results show that the differences in the initial conditions and the adjustments to the CAP have brought about quite a diverse picture concerning the changes in output in the family and non-family farms in the NMS. The a priori expected dynamics of positive output growth in family farms and negative in the non-family has only materialised in Latvia, Romania and Slovakia. The decomposition of output changes suggests a positive effect of technical change in family farms only in the early years of EU accession. Concerning endowments, their effect on structural change is mostly positive with the only exception of Slovenia. This suggests that the family farming sector grows by accumulating productive resources. However, this growth has not always materialised in increase of family farms output.

Financial cognitive ability is an important part of human capital, which has a direct impact on household income. The dual differences composed by rural residents’ cognition level and residents’ income make the relationship between the two complicated. Based on the analysis of the impact of financial cognitive level on rural household income, this paper takes into account the individual heterogeneity of financial cognition to build an unconditional quantile regression (UQR) model through the micro data of the China Household Financial Survey Project (CHFS). Incorporating the background of the rapid development of digital finance, this paper also studies the impact of rural residents’ financial cognition on household income. The empirical results of the article have the following conclusions: First, on the whole, the improvement of financial cognitive level promotes the increase of rural household income, but this promotion has significant differences at different quantile levels of household income. Second, the digital financial inclusion index in the region has a positive moderating effect on the impact of financial cognition on the income of rural households. Third, the heterogeneity of the impact of financial cognition on the income of rural households is reflected in the two aspects of regions and household assets.

Smart specialization strategies are a new EU approach to cohesion policy, meant to deliver growth and development at EU national and regional level. Bearing in mind its focus on place-based development strategies, this paper intends to shed some light on its appropriateness to tackle uneven development and regional growth divergence. The paper showcases Spanish Extremadura growth trajectory. Extremadura is a poor region in the European context that between 2008 and 2014 diverged from the EU average, despite being eligible for EU funding as a convergence region by cohesion policy. In the 2014–2020 programming period, there was a positive dynamic at the beginning, but from 2017 onwards convergence stopped, which indicates that thematic and regional programmes have not delivered results or have not compensated for higher growth level of other Spanish regions. Moreover, research and innovation strategies for smart specialization (RIS3) seem to have limited impacts on place-based economic transformation in less developed regions. From this example, the suitability of the smart specialisation strategy as the core of cohesion policy in the programming period is discussed. It concludes that this strategy is interesting for intermediate development regions with some industrial base but does not seem appropriate as a convergence driver for poorer regions.

How the financial structure promotes the development of real economy has always been a research topic in academia. By analyzing the characteristics of China’s financial system, this paper constructs the Finance Structure Index (FSI) from the perspectives of structural efficiency, financing structure and industry structure, and interprets the trend of the FSI. Based on the quarterly data of China from 2004 to 2020, this paper constructs a time-varying parameter-vector autoregression (TVP-VAR) model to study the dynamic impact of finance structure on the growth and optimization of the structure of the real economy. The empirical analysis results show that the response of the real economy has time-varying characteristics. Early on, financial structure has a promotion effect on the scale of the real economy, but the impact on the structure is not clear. In the middle, the effect of promoting the scale decreases slightly and then rebounds rapidly, while the optimization of the structure is inhibited. Later, it has a significant promoting effect and an obvious time-lag effect. Moreover, the impact of the financial structure is unstable. It is necessary to improve the efficiency and quality of the transmission of the optimization of the financial structure to the real economy.

The green transformation of the manufacturing industry is crucial for high-quality development of the Yangtze River Economic Belt, and environmental regulation and technological innovation may play key roles. Considering the undesirable output of the manufacturing industry, this paper adopted the undesirable-SE-SBM Model to measure the green transformation efficiency, which can reflect the core transformation performance. On this basis, this paper respectively adopted system generalized method of moments (SYS-GMM) and differential generalized method of moments (DIF-GMM) to explore the driving factors of green transformation, which fully considered the lag variable of transformation efficiency. The estimated results of green transformation showed that the efficiency of the Yangtze River Economic Belt has maintained an overall growth trend, while that of the eastern regions was higher than that of the central and western regions. The regional difference of transformation efficiencies showed a trend of convergence first and then expansion, however, a few regions such as Chongqing have achieved leapfrog development. The estimated results of driving factors showed the first-stage lag affected the green transformation positively, while the second-stage lag had a significantly negative effect. The ratchet effect and cumulative effect led to the continued efforts on green transformation, however, the timeliness of policy might cause a rebound in practice. As mentioned in green paradox, the environmental regulation had a negative effect, which might bring compliance costs. The technology innovation level indeed promoted the green transformation of manufacturing, but the scientific research investment did not exert the expected positive effect, while the utilization of many research funds lacked market orientation. Economic development level had a negative effect on green transformation, and it would play a positive effect only if it reached a certain stage. The industrialization and urbanization affected the efficiency positively, and the external dependence degree had a significant negative effect. It was not clear whether foreign direct investment (FDI) brought a pollution haven or pollution halo effect. In view of these conclusions, local governments should strictly enforce environmental regulations, build the regional green innovation system, improve marketization of research funds, optimize the export structure, and promote new urbanization and new industrialization.

Both developed and developing countries face energy poverty issues today. The growing interest over the last few years at the scientific level demonstrates the importance of the problem. It was a practice for many years to measure energy poverty by calculating the economic single indicators. In recent years, this practice was increasingly criticized and new, more comprehensive indices were developed. Review and analysis of indices developed can help scholars to dig deep into the specific aspects of the problem. The paper aims to review the indices for energy poverty assessment from households’ perspectives and to provide the main insights into the indicators selection process by providing the set of indicators for sustainable energy poverty assessment. The literature search and analysis follows the SALSA (Search, Appraisal, Synthesis and Analysis) and the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodologies. The literature search was carried out in the Web of Science (WoS) Core Collection database. The search covered the period 1994–2020. Thirty-four developed indexes for energy poverty were identified for assessment. In order to measure the most important dimensions and to reflect the modern concept of the energy poverty, the paper proposes a set of indicators for sustainable energy poverty assessment.

As the biggest renewable energy installation and generation country globally, it is important to deeply understand China’s wind power production determinants and draw implications for energy policy. This paper analyzes local electricity deployment, electricity consumption, investment in wind power, and price of wind power electricity on-grid apart from traditional GDP and CO2 factors in the panel data regression model, and some interesting results are found. The investment of installation and the price of wind power electricity on-grid have negative impacts on wind power generation, while local electricity consumption and inter-provincial power transmission capacity significantly impact wind power generation positively. GDP and CO2 emission per capita have negative and positive impacts on wind power production, respectively. As for different wind power zones, the most influencing factors are local electricity consumption. Hence, this paper concludes that local absorbing capacity is still an important limiting factor to Chinese renewable energy development. At last, some policies are suggested to enhance the local absorbing capacity of renewable energy.

In the aftermath of the COVID pandemic, the long-term sustainability of state budgetary expenses is intimately connected to tax compliance. The new solidarity tax is one of the policies designed to help. In the Czech Republic, solidarity tax, introduced in the aftermath of the financial crisis of 2008–2009, is still levied. This paper studies the tax compliance of different income groups in the presence of solidarity tax. Most existing studies suggest declining tax compliance with income, though others found the opposite. This paper argues that the association of tax compliance with income is more complex. This paper assesses tax compliance as related to income in a continuous setting and by comparing income groups employing a large sample from the Czech Republic (N = 1811, 60.6% female, aged 18–82, M ± SD: 51.3 ± 17.2, 19.3% with higher education). Methodologically we rely on ANOVA analyses with post-hoc tests, correlations, and ordinal regressions. We find that the associations of income and tax compliance of linear, quadratic, shift position, and slope were not statistically significant if controlling for age, gender, and education. The ethical acceptability of cheating on tax is the lowest in the middle-income group, presenting 33% of the sample. The lowest and the highest income group show more ethical flexibility in claiming state benefits if not entitled. The paper presents interesting ideas for policymakers on the tax behavior of different income groups.

In the past 30 years, China’s industrialization level has developed rapidly, and agricultural green development (AGD) is facing severe challenges. The research on the temporal and spatial features of the coupling and coordination of industrialization and agricultural green development is a key issue to promote the sustainable development of agriculture. This paper takes China’s industrialization and AGD level as the research object, and uses panel data from 31 provinces in China from 1990 to 2019 to construct an evaluation index system for industrialization and AGD. This paper uses the coupling coordination degree model and spatial autocorrelation analysis method to calculate, test and analyze the temporal and spatial features of the coupling coordination level of industrialization and AGD. The results show that: this paper compares the industrialization and AGD levels during the study period and finds that China’s industrialization development level is on the rise as a whole, and the AGD level shows a downward trend first and then rises later. Through the horizontal comparison of different regions, this paper finds that there is a large regional imbalance in the level of industrialization and AGD. The coupling and coordination level of industrialization and AGD has always been primary. From the time point of view, coupling coordination degree shows a trend of first decline and then rise. From a spatial point of view, coupling coordination degree varies greatly among provinces, with the eastern, central and western regions decreasing successively. The level of coupling coordination has obvious positive autocorrelation in spatial distribution, and presents significant spatial agglomeration characteristics in space. The research results can provide a theoretical basis for regionally differentiated governance of the coordinated development of industrialization and AGD, and promote coordinated development.

This paper focuses on examining the nonlinear impact of trade openness (TO) on economic growth (EG) in the Asean-6 countries (Indonesia, Malaysia, Thailand, Singapore, Philippines, and Vietnam). In order to achieve the set research objectives, the authors estimate the research model through the fixed-effect panel threshold approach. Unlike previous studies, this paper finds that there is a nonlinear impact of TO on EG, whereby TO has two threshold values. Specifically, before the first threshold value, TO plays an important role in boosting EG. However, this impact level decreases gradually when TO exceeds this threshold value. In particular, when exceeding the second threshold value, the impact of TO on EG is still positive but has a relatively low value. The research results show that if TO increases to a high level (beyond the threshold value) without combining with other complementary policies, this does not encourage high-efficiency EG. In addition, this study also shows that EG is positively affected by domestic investment and negatively affected by financial crisis. The findings in this paper are of great importance for the Asean-6 countries as well as researchers.

This paper empirically analyzes the relationship between digital inclusive finance and rural income, and demonstrates that digital inclusive finance plays a significant role in promoting rural income, based on the 2012-2018 panel data of 17 cities in Henan Province of China. Further dimensional research unveils that all of its breadth of coverage, depth of use and degree of digitization present significant positive correlation with rural income, and a robustness test was conducted through the sub-sample method. In addition, according to regression analysis on the influencing factors of digital inclusive finance through the Tobit model, the level of economic development, the Internet popularity rate and the urbanization rate have a positive effect on the development of digital inclusive finance in Henan, while the income gap between urban and rural areas and the degree of opening up have a negative effect. Finally, predicated on the analysis of the restrictive factors of Henan’s digital inclusive finance in increasing rural income, the paper puts forward specific policy proposals based on the native state quo.

In the paper, based on the 2012-2018 panel data of 17 cities in Henan Province of China, a panel regression model was constructed to empirically analyze the relationship between digital inclusive finance and rural income, and the empirical results demonstrate that digital inclusive finance plays a significant role in promoting rural income. Further dimensional research unveils that all of its breadth of coverage, depth of use and degree of digitization present significant positive correlation with rural income, and a robustness test was conducted through the sub-sample method. In addition, according to regression analysis on the influencing factors of digital inclusive finance through the Tobit model, the level of economic development, the Internet popularity rate and the urbanization rate have a positive effect on the development of digital inclusive finance in Henan, while the income gap between urban and rural areas and the degree of opening up have a negative effect. Finally, predicated on the analysis of the restrictive factors of Henan’s digital inclusive finance in increasing rural income, the paper puts forward specific policy proposals based on the native state quo.

With the gradual popularity of online sales and the enhancement of consumers’ low-carbon awareness, the low-carbon e-commerce supply chain (LCECSC) has developed rapidly. However, most of the current research on LCECSC assumes that the decision-making body is rational, and there is less research on the irrational behavior of the e-platform altruistic preference. Therefore, aiming at the LCECSC composed of a single e-platform and a single manufacturer, this paper establishes two basic models with or without altruistic preference. Additionally, this paper combines the characteristics of online sales and assumes that altruistic preference is a proportional function of commission, then establishes a commission-based extended model with altruistic preference to further explore the influence of commission on its altruistic preference. The current literature does not consider this point, nor does it analyze the influence of other parameters on the degree of altruism preference. By comparing the optimal decisions and numerical analysis among the models, the following conclusions can be drawn that: (1) different from the traditional offline supply chain, the profit of the dominator e-platform is lower than the profit of the follower manufacturer, (2) when the consumers’ carbon emission reduction elasticity coefficient increases, service level, sales price, carbon emission reduction, sales, supply chain members profits, and system profit increase, ultimately improving economic and environmental performances, (3) the altruistic preference behavior of the e-platform is a behavior of ‘profit transferring’. The moderate altruistic preference is conducive to the stable operation and long-term development of LCECSC.

Quality educational institutions are strategic tools for accelerating the attainment of Sustainable Development Goals (SDGs). All the 17 SDGs are interlinked. For instance, quality education (SDG4) reduces poverty (SDG 1,2) and inequalities (SDG10) and stimulates good health and wellbeing (SDG3). The paper applied unorthodox theoretical postulations such as convergence models, intergovernmentalism, neofunctionalism and neorealism in explaining how functional (educational) institutions are a necessary enabling environment in accelerating the attainment of SDGs. Empirically, the paper identified unclear modus operandi, lack of political will, political instability, small and fragmented markets and economies with heterogeneous characteristics, and lack of standardization of product and procedures, among other factors, as constraints to sustainability in tertiary education. A Vector Autoregressive (VAR) model was employed using data from 51 Sub-Saharan countries. The three variables were gross domestic product per capita (GDPP), governance and tertiary education expenditure. Results indicated significant short-run unidirectional causality from gross domestic product per capita and tertiary education expenditure to governance, but joint short-run causality was not established. However, transmission effects across the three variables became significant as the number of years increased to ten years. The study recommends a holistic approach from policymakers in order to ensure sustainability in tertiary education due to interlinkages, with emphasis placed on direction of causality.