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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.

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.

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.

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.

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.

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.

China’s recent development has been nothing short of remarkable, but energy-saving, and environmental protection is still a serious problem. The improvement of energy efficiency (EE) is an important factor for China to better follow the path of energy conservation, sustainable development, and environmental protection. Meanwhile, market segmentation is a unique phenomenon in the process of China’s economic development. Hence, studying market segmentation on energy efficiency has positive significance for improving energy efficiency. The major objective of this study is to investigate the relationship between EE and market segmentation. This paper measures market segmentation by the Price-Based Approach, calculating EE by super slack-based measure (super-SBM), and integrated spatial Durbin model and geographically weighted regression model. Based on the panel data of 30 provinces in China from 1995 to 2018, this paper finds that: (1) Regional market segmentation has a significant negative effect on EE. Moreover, in terms of spatial effect, market segmentation has a positive spatial spillover on EE estimated by 0-1 matrix suggesting that market segmentation in the surrounding area has a positive impact on local EE. (2) The negative effect of Market segmentation on EE demonstrates the obvious regional difference: Eastern region &gt, central region &gt, western region. In addition, geographically weighted regression results show that the impact of market segmentation on EE shows that in regional spatial distribution, Shanghai, Jiangsu, Zhejiang, and Anhui have the strongest negative effect, second in Fujian, Jiangxi, Shandong, Henan, Hubei, Beijing, Tianjin, and Hebei. (3) This paper confirms that market segmentation can affect EE through local protectionism, technological difference, and scale effect. Finally, through the above research basis, put forward the corresponding policy suggestions.

Investor emotional heterogeneity and oil dual attributes are the key factors that cause the asymmetry of risks in the international crude oil market. This paper uses the monthly data from April 2003 to October 2020 to identify the dynamic characteristics of oil’s commodity attribute and financial attribute, and this paper also analyzes the asymmetric characteristics of risk evolution and risk degree in the international crude oil market under the condition of oil returns heterogeneity. The empirical results show that: first, there is heterogeneity in the influence of oil attributes on the risk evolution and risk degree of the international crude oil market, second, the alternation of oil dual attributes has a significant asymmetric impact on the risk evolution of international crude oil market, third, the sudden change of international crude oil market risk caused by oil attributes is asymmetric under different oil returns trends. Based on the empirical conclusion, this paper puts forward the corresponding policy recommendations.

The sustainable environment has been a desired situation around the world for the last few decades. Environmental contaminations can be a consequence of various economic activities. Different socio-economic factors influence the environment positively or negatively. Many previous studies have resulted in the efficient allocation of inputs as an environment-friendly component. This paper investigates the effects of energy efficiency on ecological footprint in the ASEAN region using balanced panel data from 2001 to 2019. First, this paper technically derives the energy effi-ciency, using the stochastic frontier analysis (SFA) of the translog production type of single output and multiple inputs. Findings of the SFA show that the Philippines and Singapore have the highest energy efficiency (94%) and Laos has the lowest energy efficiency (85%) in the ASEAN region. The estimated average efficiency score of the ASEAN region was around 90%, ranging from 85% to 96%, indicating that there is still 10% room for improvement in energy efficiency. Second, this study employed the panel autoregressive distributed lag (ARDL) model to explore the short run and long run impact of technically derived energy efficiency on ecological footprint in the ASEAN region. Results of the panel ARDL model show that energy efficiency is a reducing factor of ecological footprint in the long run. Moreover, energy efficiency plays a significant role to control the environmental contaminations. In addition, results of this study also explored that urbanization is an increasing factor of ecological footprint, and investment in agriculture is also beneficial for the environment. Moreover, to obtain the directional nature of the associations between the ecological footprint and its independent variables, this paper has employed the paired-panel Granger causality test. The results of the paired wise panel Granger causality test also confirm that the energy efficiency, ur-banization, and investment in agriculture cause ecological footprint. Finally, this study recom-mends that efficient utilization of energy resources as well as investment in agriculture are neces-sary for sustainable environment. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. Funding: Project no. 132805 has been implemented with support provided from the National Research, Development, and Innovation Fund of Hungary, financed under the K_19 funding scheme and supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences (BO/00095/18 and BO/8/20).

The growth of agricultural total factor productivity (TFP) is seen as a driving force for the sustainable development of agriculture. Meanwhile, the promotion of urbanization in China has exerted a profound impact on agricultural production. This paper calculates the agricultural TFP and analyzes the effect of urbanization. Firstly, the DEA-Malmquist method is used to calculate the dynamic change in agricultural TFP in China from 2004 to 2016. Secondly, the spatial spillover effect of urbanization on agricultural TFP is investigated by the spatial Durbin model. We found that: the average annual growth rate of agricultural TFP in China is 4.8% from 2004 to 2016, and the spillover effect of urbanization on agricultural TFP shows a U-shaped relationship, which means that urbanization has exerted a negative effect first and then a positive effect on agricultural TFP. Finally, the paper puts forward policy suggestions from the perspective of sustainable coordination of urbanization and agricultural production.

The residential sector has become the second largest energy consumer in China. Urban residential energy consumption (URE) in China is growing rapidly in the process of urbanization. This paper aims to reveal the spatiotemporal dynamic evolution and influencing mechanism of URE in China. The spatiotemporal heterogeneity of URE during 2007–2018 is explored through Kernel density estimation and inequality measures (i.e., Gini coefficient, Theil index, and mean logarithmic deviation). Then, with several advantages over traditional index decomposition analysis approaches, the Generalized Divisia Index Method (GDIM) decomposition is employed to investigate the impacts of eight driving factors on URE. Furthermore, the national and provincial decoupling relationships between URE and residential income increase are studied. It is found that different provinces’ URE present a significant agglomeration effect; the interprovincial inequality in URE increases and then decreases during the study period. The GDIM decomposition results indicate the income effect is the main positive factor driving URE. Besides, urban population, residential area, per capita energy use, and per unit area energy consumption positively influence URE. By contrast, per capita income, energy intensity, and residential density have negative effects on URE. There is evidence that only three decoupling states, i.e., weak decoupling, strong decoupling, and expansive negative decoupling, appear in China during 2007–2018. Specifically, weak decoupling is the dominant state among different regions. Finally, some suggestions are given to speed up the construction of energy-saving cities and promote the decoupling process of residential energy consumption in China. This paper fills some research gaps in urban residential energy research and is important for China’s policymakers.

This paper explores the role of basic medical insurance in protecting family investment in child education. First, this paper establishes a two-phase overlapping generation model to theoretically analyse the impact of basic medical insurance on investment in child education under the influence of the impact of parental health. The results show that health shock reduces parental investment in child education, and medical insurance significantly alleviates the negative impact of parental health shock on investment in child education. Furthermore, this paper establishes a two-way fixed effect regression model based on the data of China Family Panel Studies (CFPS) in 2014 and 2016 to empirically test the above results. The results showed that parental health shocks negatively affect investment in child education, and paternal health shock has a more significant impact than maternal health shock. However, medical insurance significantly reduces this negative impact, provides security in investment in child education, and promotes the improvement of human capital.

The complexity of consumer behavior requires new research methods to overcome the limitations of conventional evident-based research. The aim of this paper is the comparison between two types of factor analyses, Q and R (PCA and cluster analysis) for subjectiveness measurement in the case of durable goods buying behavior in Romanian households with different levels of education and occupancy. Our study explores different subjective patterns of stimulus of 30 statements (Q-sample) by 30 Romanian households (P-sample) using the Q-sort method for collecting data. For the Q-sample inputs, results from the literature were used. Based on the 30 Q-sorts, we discovered four factors for both Q and R factor analysis, mostly different according to specific results from different methods. For the Q method, we used the labels “pragmatic”, “modern”, “traditionalist”, and “innovator. For R factor analysis and cluster, we used “traditional Romanian brands”, “real needs and power purchasing”, “sceptic versus optimistic subjectiveness”, and “negative subjectiveness”. This paper suggests the Q methodology as a structured and transparent approach to consumer behavior research by combining the in-depth subjectivity of qualitative methods and statistical rigor of factor analysis to identify groups in consumers. The research provides useful suggestions for selecting and approaching target consumer segments in the Romanian durable goods industry.

In the economic growth models, technological progress is either exogenous or endogenous. The endogenized theory is based on analytical modeling of the economic process in order to include the event of innovating. Theory around the subject innovation and economic growth also includes several independent parameters that have a strong impact over innovation. However, few of them established creativity as an independent parameter of innovation. The present paper aims to extend the endogenized theory in order to include creativity as an independent parameter of innovation, based on the evidence of a panel data of 28 countries, through 8 years. A theoretical model, a multiple linear regression, an ANOVA analysis and correlational matrixes were used in order to fulfill our purpose. Results show that innovation is determined by the level of knowledge twice as much as the level of creativity. A conceptual framework for an extension of endogenous growth models, in order to include creativity, is presented in the paper. The model can enhance economic growth by fostering creativity or knowledge and thus, the size of innovation, which is the main driver for economic growth in the model presented.

This paper investigates the relationship between economic policy uncertainty (EPU), an index capturing newspaper coverage of policy-related issues, and momentum profits. Momentum remains an unexplained anomaly. Our findings reveal a statistically negative association between EPU and hedge momentum portfolios. The short side portfolio dominates this effect as compared to the long side. EPU is statistically significant after controlling for macroeconomic variables. Further-more, the paper conducts a battery of time series analysis, which highlights that EPU has a causal relationship with the hedge portfolio in the short run. On the other hand, the hedge portfolio has along-term relationship with EPU, not the other way around. info:eu-repo/semantics/publishedVersion