Search

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.

In this paper we provide a highly selected review and synthesis on some of the recent and notable contribution to research in portfolio analysis. A unique perspective on this development in the literature is offered in this paper by judiciously identifying a few sample eigenvalues adjustment patterns in a portfolio that leads to an improvement in the out-of-sample portfolio Sharpe ratio when the population covariance matrix admits a high-dimensional factor model. These patterns unveil a key insight into a portfolio performance improvement and shed an important light on the effectiveness of a few recently introduced ”robust to estimation errors” covariance matrix estimation approaches, which were not originally designed with the goal to improve the out-of-sample portfolio performance.

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.

This paper analyses the COVID-19 crisis and its management, under the Austrian Economics. The attention is focused in the States’ coercive intervention, to evaluate the positive or negative effects of pandemic, according to the Principles of Political Economy and the theory of capital and economic cycles. The paper examines the specific case of massive intervention by governments and, especially, central banks in monetary and financial markets to deal with the pandemic by seeking to lessen its effects. Also, it is offered a critical analysis on simultaneous government policies involving taxes and an increase in public spending which are presented as the panacea and universal remedy for the evils that afflict the society, instead of promoting the transit to Wellbeing Economics. To conclude the review, there is a proposal of paradigm review, in the way to offer a sustainable model.

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

This paper extends the “sources of growth” explanation for the Environmental Kuznets Curve (EKC) proposed by Copeland and Taylor in a concise theoretical framework, that is, when the sources of growth are transformed from physical capital and labor to human capital and knowledge, the environmental pollution could at first rise and then fall with a sustainable growth in per capita income. Using the provincial panel data from 1995 to 2017 in the mainland of China, an empirical analysis is carried out by the System Generalized Method of Moment (sys-GMM). The results show that: first, the EKC hypothesis exists in China. The inflection point for SO2 emissions has been passed in all of the provincial regions, and for CO2 and comprehensive environmental pollution losses have not been passed in some regions, but the inflection point from the national average level in China has been passed, second, the main production factors of the traditional economy, physical capital and labor, are positively correlated with environmental pollution, while human capital and green technological progress, the main production factors of the knowledge economy, are negatively related to environmental pollution, third, human capital and green technological progress have become important factors to promote economic growth, and human capital, in particular, has become the primary factor, which indicates that China is in the process of transforming traditional economy into a knowledge economy. The stage of China’s economic development and the trend of environmental pollution is consistent with the extended “sources of growth” explanation for the EKC, which proved the theoretical hypothesis. This has an important practical significance for China’s current economic reform and important theoretical value for the economic transformation and sustainable development of developing countries. The paper finally puts forward corresponding policy recommendations.

Covid-19 pandemic lockdown has slow down the world economic system. The pandemic has cleared the roads, close factories and grounded planes causing severe economic challenges. The damaging impact of the pandemic amid lockdown has been a blessing in guise for the environment because of significant drop in pollution level as transport and industrial sectors shutdown. Transport and industrial sectors are major contributors to environmental degradation through various emissions as a result of fossil fuel consumption. Energy consumed by transport and industrial sectors will have to shift to viable, readily available, economically and environmentally friendly with no carbon build up post Covid-19 pandemic. Hydrogen energy remains the best alternative option technologies containing green house gas emission and pollutions of several forms. Hydrogen holds the potential to provide a clean, reliable, renewable and economical source of energy for meeting the growing and unending global energy needs post pandemic. The present paper explores the economic feasibility and potential of hydrogen to serve as a competitive fuel option post pandemic. In this paper, the role of hydrogen as an energy carrier hydrogen economy structure, potential of hydrogen economy, hydrogen production methods, hydrogen application and the economic and environmental importance of hydrogen as a viable fuel option post covid-19 pandemic were discussed. There will be a surge in demand and investment for hydrogen economy post Covid-19.

The main aims of this paper are to examine the technological trajectories of city innovation, to provide a picture of the current state in the most significant technologies, and to propose an explanation for the long-run evolutionary trajectories of technological developments that contribute to the quality of urban life through innovation. In the conceptual part of the paper, we develop the argument that the explanation may rest on the interrelationships between the concept of urban transformative capacity and the theory of path dependence. In the empirical part, we analyze patent data on city-related innovations to examine the trajectories of technological developments over the period 1980–2020. Our main findings at a technological field level (i) confirm the path dependence theory in general and the institutional approach in particular, (ii) acknowledge the rapid transformation towards ‘smart cities’ through the explosive growth of digital technologies, and (iii) confirm the environmental sustainability concerns when developing new technologies. In our study, we focus particularly on the technological sectors (‘clusters’) that provide a significant contribution to quality of urban life, namely environment, public services, and leisure and participation. Our findings provide theoretical, managerial, and policy implications for future research activities on the technological developments that benefit quality of urban life.

The growing risk of climate change caused by the emission of greenhouse gases poses new challenges to contemporary countries. The development of economies is usually related to increasing levels of greenhouse gas emissions. Therefore, the question arises whether it is possible to achieve sustainable economic and financial development and simultaneously reduce greenhouse gas emissions. This paper assumes it is possible if energy efficiency is increased. The aim of the paper is to show the link between energy efficiency and sustainable economic and financial development in Organisation for Economic Co-operation and Development (OECD) countries for the period 2000–2018 by using data envelopment analysis (DEA) and regression analysis. The results show a slight upward trend of total factor energy efficiency (TFEE) in OECD countries for the analysed period; however, there is a difference in TFEE levels. Developed OECD countries have higher TFEE levels than developing OECD countries. The links between total factor energy efficiency and sustainable economic and financial development reveal different impacts depending on the variables taken into consideration.

This paper studies the evolution of overconfidence over a cohort&rsquo, s working life. To do this, the paper incorporates subjective assessments into a continuous time human capital accumulation model with a finite horizon. The main finding is that the processes of human capital accumulation, skill depreciation, and subjective assessments imply that overconfidence first increases and then decreases over the cohort&rsquo, s working life. In the absence of skill depreciation, overconfidence monotonically increases over the cohort&rsquo, s working life. The model generates four additional testable predictions. First, everything else equal, overconfidence peaks earlier in activities where skill depreciation is higher. Second, overconfidence is lower in activities where the distribution of income is more dispersed. Third, for a minority of individuals, overconfidence decreases over their working life. Fourth, overconfidence is lower with a higher market discount rate. The paper provides two applications of the model. It shows the model can help make sense of field data on overconfidence, experience, and trading activity in financial markets. The model can also explain experimental data on the evolution of overconfidence among poker and chess players.

The core issue for China&rsquo, s economy to shift from high-speed growth to high-quality development is to raise total factor productivity (TFP). Based on the data of A-share listed companies from 2013 to 2017 and the air quality monitoring data released by the China National Environmental Monitoring Centre, this paper conducts an empirical test on the relationship between haze pollution, labor productivity, and firm-level TFP by using the mediation effect test model. The results show the following: First, haze pollution will reduce a firm&rsquo, s TFP. Second, labor productivity plays a partial intermediary role between haze pollution and a firm&rsquo, s TFP. Haze pollution will not only have a direct negative impact on a firm-level TFP but also reduce a firm-level TFP by reducing labor productivity. Subsequently, the robustness test was carried out by means of a substitution of independent variables and dependent variables, and the results all supported the hypotheses in this paper. In addition, the heterogeneity of the industry and the ownership of listed companies was analyzed, and the two-stage least squares (2SLS) method was used to solve the endogeneity problem. The conclusions of this paper are helpful to clarify the relationship between haze pollution, firm factor productivity, and firm-level TFP. The paper&rsquo, s findings also provide a practical basis for firms to further improve TFP from the perspective of air pollution problems such as haze.

In this paper, the aggregate index of national economies&rsquo, circularity (INEC) was proposed and empirically verified. For this purpose, the taxonomic linear ordering method was used, which is a multi-criteria decision-making procedure. This method replaces the analysis of the phenomenon described by a set of indicators with an analysis using one aggregate indicator: the so-called &lsquo, synthetic metric&rsquo, Based on 14 circular economy indicators that are available in the Eurostat database, the circularity indexes were constructed for 24 EU countries (including the United Kingdom). This allowed the author, on the one hand, to create a ranking of the countries, and on the other, to assign them to four groups, which were characterized by a similar level of circularity. This paper attempts to answer the following questions: how circular are the European economies? What are the main challenges in achieving circularity in Europe? Taking into account the INEC range [0,1], it should be noted that the level of circularity in the analysed European countries is low (an average of 0.3021). Therefore, the paper indicates the areas requiring improvement in this respect.

The main objective of the paper is to determine the impact of the COVID-19 pandemic on the level of energy poverty in Poland. In order to achieve such a goal, the first part of the article presents the definition of energy poverty and the nature of its measures, as well as the determinants and policies of the state addressing the issue of energy poverty mitigation. In the second part of the paper, the results of research into the level of energy poverty are analyzed and the variables affecting energy poverty in Poland during the pandemic are determined. It was established on the basis of these results that the present pandemic contributed to the aggravation of financial difficulties in Polish households with regard to financing expenditure on energy carriers. It was found that COVID-19 had a negative impact on the average disposable income of Polish households, which, with the increase in prices and expenditure on energy carriers, led to an increase in the proportion of disposable income spent on energy carriers. The most affected have been the poorest households. Moreover, the long downward trend in the level of energy poverty in Poland has reversed. Thus, it has been proved that COVID-19 has contributed to the intensification of energy poverty in Poland. The theoretical and empirical considerations contained in this paper may be a valuable source of scientific data on the impact of the pandemic on household energy poverty, while public institutions may find them a source of useful information, helping to create effective instruments to mitigate energy poverty in the Polish economy.

With the continuous increase of China’s foreign-trade dependence on crude oil and the accelerating integration of the international crude oil market and the Chinese finance market, the spillover effect of international oil price fluctuation on China’s stock markets increasingly attracts the attention of the public. In order to explore the impact of international oil price fluctuation on China’s stock markets and the time-varying spillover differences of industry sectors, this study proposes three research hypotheses and constructs a multi-time scale analysis framework based on wavelet analysis and a time-varying t-Copula model. In this paper, we use the Shanghai Composite Index as the representative of a general trend of the stock market, and we use the stock index of the China Securities Industry as the counterpart of industrial sectors. Based on the data from 5 January 2005 to 31 May 2020, this paper measures and analyzes the spillover effect of international oil price fluctuation on China’s stock markets, under different volatility periods. The results show that, firstly, the spillover effect of international oil price fluctuation on the Chinese stock markets is different. In the short and medium volatility period, the changes in international oil price are ahead of the changes in the Chinese stock markets, while the latter is ahead of the former under long-term fluctuations. Secondly, the spillover effect of international oil price fluctuation on China’s industry stock indexes is persistent. As the time scale increases, the tail dependency will increase. Finally, the impact of risk events aggravates the volatility of the stock markets in the short-term, while the mid- to long-term impact mainly affects the volatility trend. Investment risk control can make overall arrangement on the basis of the characteristics of oil price impact under different fluctuation stages.

China, taking the concept of sustainable development as the premise, puts forward Intended Nationally Determined Contributions (INDC) to reduce the greenhouse gas emissions in response to climate change. In this context, with the purpose of seeking solutions to a carbon financial market pricing mechanism to build China&rsquo, s carbon finance market actively and thus achieving the goal of sustainable development, this paper, based on the autoregressive integrated moving average (ARIMA) model, established a carbon price prediction model for the carbon financial market, and studied the relationship between Certified Emission Reduction (CER) futures prices and spot prices, as well as the relationship between European Union allowances (EUA) futures prices and CER futures prices in an empirical manner. In this paper, EUA and CER futures prices of the European Climate Exchange (ECX) and EUA and CER spot prices of the BlueNext Environmental Exchange were selected as research objects. Granger causality test, co-integration test, and ECM were used to form a progressive econometric analysis framework. The results show that firstly, the ARIMA model can effectively predict carbon futures prices, secondly, CER futures prices cannot guide spot price, and the futures pricing function does not play a role in this market, thirdly, EUA futures price can, in the short term, effectively guide the trend of CER futures prices, with the futures pricing function between the two markets. In the long run, however, the future pricing function of the two markets is not obvious. Therefore, great differences among maturity of the two markets, degree of policy influence, and market share lead to the failure of long-run futures pricing functions.

Human activity has led to degradation of the natural environment, with far-reaching impacts for society and the economy, sparking new conceptual framings for how people interact with, and depend upon, the environment. The bioeconomy and natural capital concepts both blend economics and natural sciences and propose new interdisciplinary, environmental sustainability framings. Despite this similarity, the two concepts are rarely applied together. This paper applies a natural capital lens to the bioeconomy at three different levels: environmental sustainability framings, experts&rsquo, principles for a sustainable bioeconomy, and a case study of EU policy. We first construct an integrated cascade model that combines the unrealised potential of bioresources alongside unrecognised environmental services that tend to be systematically undervalued or ignored. Subsequently, we present five cornerstones identified from the sustainable bioeconomy-related literature from a natural capital perspective and highlight avenues of complementarity. The paper concludes with a policy case study of the EU Bioeconomy Strategy through a natural capital lens. There is evidence that the EU strategy has become increasingly aligned with the natural capital concept, but there is scope for further integration. The natural capital concept and related toolbox is an asset for the future bioeconomy to ensure it meets its environmentally sound and ecologically conscious objectives.

This paper analyzes calorie consumption in Vietnam using the household survey data. The data suggest that food insecurity is still a major problem in Vietnam, with nearly 40 percent of the population being unable to meet their calorie requirement. Employing nonparametric and parametric estimation techniques, the paper examines the relationship between household calorie consumption and per capita household expenditure in Vietnam. The analysis indicates a positive and significant relationship between per capita expenditure and per capita calorie consumption. The mean calorie elasticity is estimated to be between 0.21 and 0.31 by the parametric method and 0.20 by non-parametric method. In addition, simulated income and food price changes indicate that undernutrition is very responsive to changes in income and food prices

Because of the crucial implications of the market power of OPEC, the aim of this paper was to investigate the oil asymmetric market reactions, such as the price and risk reactions, to OPEC’s announcements. Specifically, this paper first explored the oil price reactions to OPEC’s announcements and their heterogeneity to depict the directional role of OPEC based on event study methodology. Furthermore, this paper analyzed the oil risk reactions in the framework of a linear model. Our findings reveal several key results. The oil price reactions to OPEC production decisions behave quite heterogeneously in three kinds of decisions. Specifically, the reaction to announcements of a production increase shows an invert “U” shape, whereas there is a linear effect of cut announcements. Otherwise, when a maintain decision is announced, the oil prices have no obvious change over the sample period. Additionally, the oil risk reactions to OPEC’s announcements are heavily related to the interaction item between OPEC decisions and its production over full sample periods. Furthermore, OPEC’s role in promoting stability in crude oil markets by changing its production shows a heterogeneous condition after global financial crisis.

The aim of this paper is to examine the interdependence between higher education on the one hand and the competitiveness of the economy and sustainable development on the other hand. To examine the mentioned interdependence, we used a sample that includes EU member states and candidate countries. The paper applies correlation and regression analysis of comparative data sections. The research findings indicate a strong correlation between higher education on the one hand and the competitiveness of the economy and sustainable development on the other. The results obtained by research can serve as a &ldquo, global benchmark&rdquo, of future public policy in the field of higher education.

The Discounted Cash Flow (DCF) method is probably the most extended approach used in company valuation, its main drawbacks being probably the known extreme sensitivity to key variables such as Weighted Average Cost of Capital (WACC) and Free Cash Flow (FCF) estimations not unquestionably obtained. In this paper we propose an unbiased and systematic DCF method which allows us to value private equity by leveraging on stock markets evidences, based on a twofold approach: First, the use of the inverse method assesses the existence of a coherent WACC that positively compares with market observations, second, different FCF forecasting methods are benchmarked and shown to correspond with actual valuations. We use financial historical data including 42 companies in five sectors, extracted from Eikon-Reuters. Our results show that WACC and FCF forecasting are not coherent with market expectations along time, with sectors, or with market regions, when only historical and endogenous variables are taken into account. The best estimates are found when exogenous variables, operational normalization of input space, and data-driven linear techniques are considered (Root Mean Square Error of 6.51). Our method suggests that FCFs and their positive alignment with Market Capitalization and the subordinate enterprise value are the most influencing variables. The fine-tuning of the methods presented here, along with an exhaustive analysis using nonlinear machine-learning techniques, are developed and discussed in the companion paper.

The recent financial crisis offered an interesting opportunity to analyze the markets&rsquo, behavior in a high-volatility framework. In this paper, we analyzed the price discovery process of the Italian banks&rsquo, Credit Default Swap (CDS) spreads through the Merton model, extended with the inclusion of a redenomination risk proxy, as to say, the risk that Italy could leave the eurozone. This paper contributes to the literature by integrating the classic Merton model with a political-sensitive market variable able to explain the greatest variance in the Italian banks&rsquo, CDS spreads during the most relevant and commonly recognized periods of socio-political and financial distress. Results show that the redenomination risk is progressively becoming the main driver of the process during crises, in particular for the sovereign debt crisis and in 2018.

The core of agricultural development depends on agricultural production efficiency improvement, and total-factor productivity growth is its significant embodiment. Hence, it is essential to address the question of &ldquo, how to improve China&rsquo, s agricultural productivity and efficiency in order to achieve growth and sustainability of agriculture in the future&rdquo, This paper estimates indices of China&rsquo, s agricultural technical efficiency (TE) scores, total-factor productivity (TFP), and its two components, technological change/progress (TC) and technical efficiency change (EC), using provincial-level panel data of 30 provinces from 2002 to 2017 by applying a stochastic frontier approach (SFA). The paper also identifies determinants of TE, TC, and TFP using selected indicators from four hierarchical levels of the economy, i.e., farm level, production environment level, provincial level, and the state level, by applying a system-GMM method. Results reveal that agricultural labor, machinery, agricultural plastic film, and pesticides are the significant drivers of agricultural productivity, with no significant role of land area under cultivation. Constant returns to scale exist in China&rsquo, s agriculture. The agricultural technical efficiency level fluctuated between 80% and 91% with a stable trend and a slight decline in later years, while TFP improved consistently over time, mainly driven by technological progress. Among the determinants, government investment in agricultural development projects significantly drives TC and TE, while the experienced labor force significantly increases TE. The disaster rate significantly reduces TE but promotes TC and TFP. The literacy rate significantly improves TC and TFP. However, government expenditures in &ldquo, agriculture, forestry, and water&rdquo, significantly reduce TE, TC, and TFP. Policy recommendations include (1) increased levels of mechanization and agriculture film use while avoiding an increase in pesticide use, (2) a continued increase in government expenditure in agricultural development projects, R&amp, D to improve technological progress, and diffusion of modern agricultural technologies, and (3) investment in education targeted at the farming population in order to continue the growth in the productivity and sustainability of China&rsquo, s agriculture.

Population aging is a great human achievement, but the economic literature normally addresses its effects in a narrow way and as a &ldquo, problem&rdquo, to be solved. The objective of this paper is to provide a more balanced approach to aging by calling into question some widespread ideas in the economic literature on aging, such as its supposed negative influence on economic growth, its impact on labor productivity or the assumption that aging societies are incapable of applying reforms. The paper adopts the renewed civil economy framework and takes as a reference the existing literature about beliefs and wrong assumptions on aging. The innovative contribution of this analysis lies in its effort to foster a positive perspective in the population aging field of research and in challenging negative associations regarding old-age stereotypes.

According to Kuznets modern economic growth entails structural change. The share of the broad economic sectors (agriculture, manufacturing and services), in value added and employment, has undergone a significant transformation also in the post socialist Central Eastern European and the South Eastern European economies, just like in the developed countries with somewhat lower dominance of the service sector. This phenomenon was widely explained by economists through technological development having a characteristically negative impact on employment within the same industry in which it is adopted. As preceding empirical research focused mainly on developed industrial countries including old EU member states, the purpose of this paper is to examine structural change in 13 Central and South Eastern European EU member economies with special emphasis on the impact of own-industry productivity on employment with OLS and GMM panel regressions. This paper reveals that the productivity increase in all the sectors goes together with the decrease in employment within the sectors in the case of OLS estimations, whereas it produces less evident results in the GMM model framework when controlled for other sectors&rsquo, and countries&rsquo, productivity and employment processes. Involving further country-, time- and industry-specific variables in the regression, we find that it is mostly manufacturing that is negatively hit by these additional factors (such as relatively higher openness or EU level investment activity) whereas productivity does not necessarily harm the sustainability of workplaces in this sector. The paper also ascertains that there is a large diversity among the selected emerging European economies with regard to economic structures.

This paper aims to analyze the effects of Covid-19 on financial markets from the perspective of Complexity. The Covid-19 pandemic has caused turmoil in financial markets and is already one of the most important financial crises in history, causing a fall in several stock markets as well as great volatility. Unlike past crises, which in most cases were caused either by problems of fiscal deficits or in the financial system, this crisis has its origin in an epidemic disease, which occurred in Wuhan, China, and quickly spread across the globe affecting transport networks, commerce and finance, and will affect the public debt of many countries. This is a systemic situation in which there is a need to consider several interconnected systems, financial instability and high financial risk, something that econophysics and some complexity theorists already do. Therefore, this paper intends to show, theoretically, the systemic and complex character of the recent financial crisis caused by Covid-19.

This paper examines the dynamic relationship between crude oil prices and the U.S. exchange rate within the structural break detection context. Based on monthly data from January 1996 to April 2019, this paper identifies structural breaks in movements of oil price and examines the dynamic relationship between crude oil prices and the U.S. exchange rate movement by introducing the economic policy uncertainty and using the TVP-VAR (Time-Varying Parameter-Vector Auto Regression ) model. Empirical results indicate that shocks to crude oil prices have immediate and short-term impacts on movements in the exchange rate which are emphasized during the confidence intervals of structural breaks. Oil price shocks and economic policy uncertainty are interrelated and influence movements in the U.S. exchange rate. Since the U.S. dollar is the main currency of the international oil market and the U.S. has become a major exporter of crude oil, the transmission of price shocks to the U.S. exchange rate becomes complicated. In most cases, the relationship between oil prices and the U.S. exchange rate movements is negative.

Carbon emissions are a prominent issue for sustainable energy production and management. Energy policies under the growing competitive environment could change the priorities of emission reduction and investment decisions. This paper aims to forecast carbon emissions from China and to rank the importance of carbon emissions with interval type 2 (IT2) fuzzy sets (FS) for sustainable energy investments. For this purpose, the quadratic model is applied to measuring emission trends and the Qualitative Flexible Multiple Criteria Method (QUALIFLEX) is used for measuring sustainable energy investment alternatives by the several emission levels. Forecasted values of 29 provinces in China are converted into the linguistic and fuzzy numbers based on IT2 FS respectively to measure the priorities of emission reduction for sustainable economies. The novelty of this paper is to propose a hybrid decision-making approach based on quadratic modeling and the QUALIFLEX method and to discuss the overall energy emission trend and policies for sustainable economic growth. The results demonstrate that emission reduction policies are the most important phenomenon and the environmental factors should be widely considered to construct sustainable energy investments and production. National Social Science Foundation of China

Nowadays tourism is growing as a gigantic, global business accounting for 10.4 % of Global GDP and 10% of global employment (Joppe, 2020). This review paper aims to explore the risks borne for tourism sector by the outbreak of corona-virus in 2020. Tourism sector is a highly vulnerable sector and the costs that will be borne from corona-virus pandemic will be devastating, particularly for the countries relying on this sector as a basic source of income. The paper suggests possible solutions and adaptation routes, while at the same time reviews lessons of the past from other pandemics and crisis. This paper is very useful for tourism policy makers and governments in countries where tourism contributes a significant part of their GDP, but also for other economic sectors closely but indirectly connected in the tourism value chain.

This paper investigates energy use efficiency at the province level in China using the stochastic frontier panel data model approach. The stochastic frontier model is a parametric model which allows for the modeling of the relationship between energy use and its determinants using different control variables. The main control variables in this paper are energy policy and environmental and regulatory variables. This paper uses province level data from all provinces in China for the period 2010&ndash, 2017. Three different models are estimated accounting for the panel nature of the data, province-specific heterogeneity and province-specific energy inefficiency effects are separated. The models differ because of their underlying assumptions, but they also complement each other. The paper also explains the degree of inefficiency in energy use by its possible determinants, including those related to the public energy policy and environmental regulations. This research supplements existing research from the perspective of energy policy and regional heterogeneity. The paper identifies potential areas for improving energy efficiency in the western and northeastern regions of China. Its findings provide new empirical evidence for estimating and evaluating China&rsquo, s energy efficiency and a transition to cleaner energy sources and production.

This paper aims to examine whether there is inherent dynamic connectedness among coal market prices, new energy stock prices and carbon emission trading (CET) prices in China under time- and frequency-varying perspectives. For this purpose, we apply a novel wavelet method proposed by Aguiar-Conraria et al. (2018). Specifically, utilizing the single wavelet power spectrum, the multiple wavelet coherency, the partial wavelet coherency, also combined with the partial phase difference and the partial wavelet gains, this paper discovers the time-frequency interaction between three markets. The empirical results show that the connectedness between the CET market price and the coal price is frequency-varying and mainly occur in the lower and higher frequency bands, while the connectedness between the CET market price and the new energy stock price mainly happen in the middle and lower frequency bands. In the high-frequency domain, the CET market price is mainly affected by the coal price, while the CET market price is dominated by the new energy stock price in the middle frequency. These uncovered frequency-varying characteristics among these markets in this study could provide several implications. Main participants in these markets, such as polluting industries, governments and financial actors, should pay close attention to the connectedness under different frequencies, in order to realize their goal of the production, the policymaking, and the investment.

Rapid urbanization has seen a concurrent growth of informal economies, which play an important role in alleviating urban unemployment and poverty. Following international efforts to integrate divergent theories on informality, this paper examines the causes of urban informal economies in China by deploying a panel data regression model that considers multiple explanatory factors informed by these theories. Our estimation based on the latest China Population Census shows that the size of urban informal employment in China reached 215 million and 22% of gross domestic product (GDP) output share was from urban informal economies. Our model reveals that the causes of urban informal economies in China are mainly associated with the stages of economic development, tertiarization of industries, unemployment, rural-to-urban migration, and globalization of urban economies. This paper adds evidence from the Chinese context to the emerging argument that informal economies cannot be fully explained by each mainstream informality theory, suggesting that these theories should be seen as complementary rather than opposing alternatives. The paper concludes with policy implications for urbanization in China.

Based on the Driver-Pressure-State-Impact-Response (DPSIR) framework, this paper constructs the input, expected output, and unexpected output of China's sustainable development. This paper calculates the sustainable development efficiency of 31 provinces and cities in China using a super-slack-based measure (SBM) model that eliminates the influence of scale factors through a three-stage data envelope analysis (DEA) approach. Taking the level of science and technology as the control variable, and the relative scale efficiency as the threshold variable, this paper calculates the effects of the absolute scale of labor force, education, economy, enterprise, and transportation on sustainable development efficiency. The results show that: (1) there is an upward trajectory for sustainable development efficiency of China's provinces and municipalities overall from 0.65 in 2004 to 0.68 in 2017, with significant regional differences in which the ecological efficiency in the Eastern region is 0.26 higher than that of the Central region, (2) it enhances the absolute scale of the labor force, education, and transportation, in order to reduce the inhibition on sustainable development efficiency, and (3) shifts our attention to the promotion of absolute economic scale to the promotion of green economic development, and increases control of polluting enterprises.

As a rule, the economy regularly undergoes various phases, from a recession up to expansion. This paper is focused on models predicting corporate financial distress. Its aim is to analyze impact of individual phases of the economic cycle on final scores of the prediction models. The prediction models may be used for quick, inexpensive evaluation of a corporate financial situation leading to business risk mitigation. The research conducted is drawn from accounting data extracted from the prepaid corporate database, Albertina. The carried-out analysis also highlights and examines industry specifics, therefore, three industry branches are under examination. Enterprises falling under Manufacture of metal products, Machinery, and Construction are categorized into insolvent and healthy entities. In this study, 18 models are selected and then applied to the business data describing recession and expansion. The final scores achieved are summarized by the main descriptive statistics, such as mean, median, and trimmed mean, followed by the absolute difference comparing expansion and recession. The results confirm the expectations, assuming that final scores with higher values describe better corporate financial standing during the expansion phase. Similar results are achieved for both healthy and insolvent enterprises. The paper highlights exceptions and offers possible interpretations. As a conclusion, it is recommended that users need to respect the current phase of the economic cycle when interpreting particular results of the prediction models.

The Efficient Market Hypothesis states that it is impossible for an investor to outperform the market because all available information is already built into stock prices. However, some anomalies could persist in stock markets while some other anomalies could appear, disappear and re-appear again without any warning. To explore new theories with applications in this direction, in this editorial, we suggest ideas to authors on what types of papers we will accept for publication in the areas of on Efficiency and Anomalies in Stock Markets. We will discuss some papers published in the special issue of Efficiency and Anomalies in Stock Markets.

Over the past few decades, there have been major advances in crop productivity across the world, which has been made possible through a combination of productivity enhancing technological innovations. Beyond this achievement however, most parts of Africa are still battling with low crop productivity resulting in food shortages and food insecurity. The yields of many staple crops are still far below their agronomic potentials with output increases being attributed largely to area expansion. This paper examines the implications of the current trends of crop/plant productivity for food security and rural livelihood development in Africa using Ghana as a case study. The paper argues that crop production in Africa is becoming a less viable and unattractive livelihood activity with farmers diversifying out of agriculture into non-agricultural activities such as illegal small-scale mining, which have negative consequences on the ability of African countries to attain the Sustainable Development Goals (SDGs).