Are digital technologies an effective inhibitor of depression among middle-aged and older adults? Micro-level evidence from a panel study.

The increased number of middle-aged and older adults leads to depression in this stratum of the population as a topical social and public health issue. However, the new generation of information technologies has exerted a profound impact on the lives of middle-aged and older adults, and offers potential solutions for alleviating their depression. This study utilizes data from the China Health and Retirement Longitudinal Study (CHARLS) collected between 2011 and 2018 and combines them with city-level traits. The results demonstrate that digital technology can reduce depression levels effectively in this group. Mechanism analysis reveals that digital technology could improve life satisfaction and subjective health status levels, which, in turn, reduces depression levels. Heterogeneity analysis shows that the positive effects of digital technology on depression were more pronounced among middle-aged and older adults with urban household registration compared to the rural population. Finally, recommendations are provided for reducing depression levels among middle-aged and older adults.

Measuring the carbon shadow price of agricultural production: a regional-level nonparametric approach.

Climate change poses an urgent threat, necessitating the implementation of measures to actively reduce carbon emissions. The development of effective carbon emission reduction policies requires accurate estimation of the costs involved. In situations where actual prices of commodities are not available in the market, shadow pricing provides a useful method to calculate relative prices between commodities with and without price information. However, most studies focus on the industry, with few contributions on agricultural sector. This paper estimates the shadow price of carbon emissions in the agricultural sector from a provincial perspective, incorporating the impact of livestock into the calculation of carbon emissions and shadow pricing. Our findings indicate that ignoring livestock may overestimate CSP values. On the whole, the level of carbon shadow price is rising, indicating good green development in China's agricultural sector. The two types of convergence results show that there is sigma convergence and beta convergence in the western and central regions, demonstrating a significant improvement in environmental performance.

Energy productivity and GHG emission in the european agriculture: The club convergence approach.

The agricultural production plays an important role in food provision and income generation for the rural population. To mitigate the climate change and ensure food security, the agricultural sector has faced multiple initiatives, including the European Green Deal. Developing effective frameworks for measures under such initiatives requires identifying reasonable benchmarks. Accordingly, it is important to assess the patterns of input use and productivity in the agricultural sector. This paper focuses on the agricultural energy productivity in the European Union (EU) Member States during 2005-2019. Indeed, the EU allocates substantial support to improve resource efficiency and reduce climate pressures in the agriculture. To the best of our knowledge, this is the first paper to apply the club convergence approach for the energy productivity the EU agriculture. This particular approach allows identifying the homogenous groups of the EU countries and, subsequently, assess the dynamics of the agricultural energy productivity within these groups. The results indicate that the agricultural energy productivity still requires attention in the EU countries, as only partial convergence was observed during 2015-2019. The EU countries were grouped into five clusters with different levels of the agricultural energy productivity. The results imply that the differences among resulting clusters remained rather stable over time. Therefore, relevant policies addressing energy efficiency issues can be developed for these relatively homogeneous groups to ensure further cohesion. The results suggest that countries with high energy productivity may show high levels of greenhouse gas intensity (and low levels of, e.g., labour productivity). Therefore, energy conservation and introduction of clean energy is a complex task that can be guided by the proposed framework and adjustment in the Common Agricultural Policy measures.

Devising evidence-based strategies for progress towards zero-carbon energy at the country level: The by-production approach.

The development of the sustainable energy systems is crucial for economic growth and climate change mitigation. This paper proposes a nonparametric approach based on the by-production technology comprising the economic and environmental sub-technologies. We consider both renewable and fossil energy in the analysis. This approach allows identifying the most relevant energy development strategies at the country level. We examine 42 countries from the OECD, B(R)ICS and ASEAN. The results indicate that most of the countries (23) need to exploit both the energy intensity and carbon factor (energy-mix) effects to ensure sustainable energy development, yet four countries also need to increase the use of the renewable energy in order to secure the economic growth. During 1990-2018, an upward trend for the CO2 emission shadow price is observed for the selected countries which suggests an improving environmental performance. The results of this study provide further guidelines for adopting effective market-oriented policy measures in the energy sector.

Per capita CO2 emission inequality of China's urban and rural residential energy consumption: A Kaya-Theil decomposition.

With the increasing affluence, the differences in CO2 emission between urban and rural residential sectors are remarkable and show an increasing trend. In case of China, residential sector accounts for a substantial share of the national CO2 emission, bringing greater pressure to achieve the goal of carbon peak. Analyzing the emission inequality trend and its drivers is essential for formulating effective CO2 emission reduction policies. However, the existing literature lacks relevant analysis from the viewpoint of urban-rural disparity. Hence, this study decomposes the CO2 emission inequality of China's urban and rural residential consumption into four factors by combining the Theil index and Kaya decomposition. The results suggest that, in 2005-2020, the per capita CO2 emission of rural residential consumption increased to a higher extent than those of urban households, with large differences in spatial distribution. Decomposition of the per capita CO2 emission inequality for residential sector shows that the primary source is the inequality within the groups, mainly from the urban intra-group inequality. Based on the static decomposition, energy intensity appears as the main factor of urban-rural inequality. The dynamic decomposition shows that there have been differences in the factors of the change in the Theil index between urban and rural areas across sub-periods.

Stochastic MCDM with normal approximation of the uniformly distributed variables for assessing sustainable insulation materials.

The sustainability-related decision-making oftentimes involves uncertain information. One of the key solutions in representing the interval information is the use of the interval information (numbers). This paper proposes a multi-criteria decision-making approach that relies on the algebra of random variables in handling the interval information. The interval information is provided in the form of the uniform distributions that are represented by mean and variance parameters. Following the central limit theorem, the normal approximation is involved. Then, the pair-wise comparisons are facilitated to establish the probabilities of dominance and rank the alternatives accordingly. The proposed approach allows for effectively handling the uncertainty and is user-friendly. The empirical application dealing with selection of the sustainable insulation materials is presented to validate the proposed approach. The technological, economic, environmental, and social facets of sustainability are considered when comparing the insulation materials. Sensitivity of the results is then checked via the Monte Carlo simulation.

Energy-space concept for the transition to a low-carbon energy society.

Urban and regional development is indispensable from energy systems that function in a sustainable and resilient manner. The generation of renewable energy has seen significant upturn in the last decade. Renewables can be exploited to meet the global energy needs and climate change mitigation goals. Therefore, development of urban and regional energy systems must take into account the possibilities and challenges posed by the increasing penetration of the renewable. The achievement of goals of the energy system in the context of transition to low-carbon energy society rises numerous complex decisions over development of infrastructure and technologies. Although renewable energy devices generate clean energy, they also change landscape. The term of energy-scape encourages discussion about interactions between the energy system and the environment, and other ecosystem services at local level. The paper reviews previous studies analysing energy-scape elements and provides the insights towards the transition to low-carbon energy and low-carbon society in general. The systematic literature review allows clearly outlining the problem and gives reliable background for further studies. The main contribution of the article to the existing literature is the creation of framework for the analysis and assessment of new renewable energy technologies installation and infrastructure. The presented framework can be applied for all renewable energy technologies and infrastructure in both urban and rural areas and allows to attain a decision acceptable to the local community.

Evaluating Green Productivity Gains with the Exponential By-Production Technology: an Analysis of the Chinese Industrial Sector.

The conventional convexity assumptions frequently placed on piecewise linear frontiers of production technologies modeled using data envelopment analysis imply non-increasing marginal products. Assuming geometric convexity in the context of the exponential technology represents a more general alternative that imposes no underlying restrictions on the marginal products, while simultaneously reducing the impact of the outlying observations. In this paper, we propose an exponential by-production technology capable of generating the outputs deemed undesirable from the society's point of view. We subsequently rely on this technology to measure environmental productivity. Our empirical illustration uses data from the Chinese industrial sector, which is both a major energy consumer and polluter. By comparing our findings with the results from a conventional production model we demonstrate that our proposed indicator mitigates the impact of outlying observations when gauging the contributions of inputs and outputs to green growth. Our results suggest that the Chinese industrial sector experienced the annual productivity growth rate of around 0.40% during 1999-2016 and that the green productivity was mostly driven by technological progress. We also demonstrate that technological progress has been a bigger contributor to the growth in industrial output in China's east than its inland or western regions.

Capacity utilization and energy-related GHG emission in the European agriculture: A data envelopment analysis approach.

Capacity utilization (CU) measures may show the potential for production growth under improved availability of the (variable and fixed) inputs. However, the environmental constraints should be considered when taking the production decisions. These questions are important in the context of the agricultural sector that needs to ensure food security and sustainability. This paper proposes a novel approach that integrates weak disposability technology with observation-specific abatement factors with input- and output-orientated capacity utilization measures in the short and long run. The case of European Union agricultural sector is analyzed. The results indicate that the multiple output-oriented CU measures considered in the study yield often conflicting results. Italy, Germany and France show the highest levels of the agricultural capacity utilization. At the other end of spectrum, the underdeveloped economies often showed lower values thereof. The inclusion of the energy-related GHG emission in the model generally reduced the performance gaps among the countries considered. Results of the research are important in assessing the possibilities for sustainable agricultural growth and development in the European Union as the CU levels may vary for a certain depending on the inclusion of the environmental pressures in the model.

Measuring self-reported food loss in primary production: Survey-based insights from Central and Eastern Europe.

Food loss and waste occur along the whole food supply chain and need to be addressed by dedicated strategies. Among all the stages of the food supply chain, food loss in primary production has been the least studied to date. In order to address this gap, this paper focuses on on-farm food loss, using Lithuania as a case study. The research comprises eleven crop products and five livestock products prevailing in Lithuanian agricultural production. A survey-based method is utilized to collect primary data from farmers. The final data set consists of 408 completely answered questionnaires. The survey-based data are merged with those from the Farm Accountancy Data Network in order to devise an effective framework for estimating self-reported on-farm food loss. The results show that there exists substantial variation in on-farm food loss rates ranging from less than 1% for milk to slightly more than 20% for beets. Environmental factors and those related to consumer and buyer requirements are the main reasons for losses of crop products, while diseases appear as the main causes of death for animals. The food loss and waste reduction measures are derived based on the results of the survey.

Assessment of agri-environmental situation in selected EU countries: a multi-criteria decision-making approach for sustainable agricultural development.

In recent years, humanity has faced with multiple crises, both of economic and environmental nature. Among the key reasons for such turbulences, the deteriorating agri-environmental situation appears as an important facet. This article evaluates agri-environmental situation of selected European Union (EU) countries using the multi-criteria decision making methods (SAW, TOPSIS, and EDAS) to identify the potential strategies for improvement of agricultural activities and environmental situation in general. The set of indicators, compiled from the database, prepared by the European Commission (EC) was used for this research. The empirical results show that the trends in agri-environmental situation of selected EU countries are similar under all the methods used. The best agri-environmental situation both at the beginning and at the end of the research period was in Finland, Ireland, and Sweden. On contrary, the worst situation was identified in the Netherlands, Denmark, and Germany. The only case of decline in the agri-environmental performance is observed for Lithuania, whereas ascension in ranks is observed for Austria and Poland. The results are of particular importance in the period of development of agri-environment and climate schemes for the European Union Common Agricultural Policy post-2020.

A novel hybrid evaluation framework for public organizations based on employees' performance factors.

Performance evaluation is a comprehensive process for comparing activities compared with predetermined organizational criteria. Based on the results of performance evaluation, organizations can embark on purposeful actions to improve their situation. Obviously, the success of organizations and the economic development of the country depend on the performance of human resources (HR). This paper proposes a novel hybrid evaluation framework for analyzing the performance of public sector organizations. The suggested setting allows for performance evaluation based on a comprehensive approach involving expert knowledge. For this purpose, the research integrates the Balanced Scorecard (BSC) approach and fuzzy multi-criteria decision-making (MCDM) methods. Initially, the employees' performance factors (criteria) are identified from the literature based on the BSC dimensions. Then, the most relevant of them are finalized through the fuzzy Delphi method (FDM) questionnaires and experts' opinions. In the second stage, the weights of criteria are determined by adopting the fuzzy best-worst method (FBWM). Moreover, two fuzzy MCDM techniques, namely VIKOR and Grey Relational Analysis (GRA), are used to examine the performance of the eight important public sector organizations of Iran. Finally, a Monte Carlo simulation-based (MCSB) approach and a scenario-based (SCB) approach are applied to compare the effectiveness of fuzzy VIKOR and fuzzy GRA. The results suggest that the critical employees' performance factors include sharing knowledge with colleagues (0.136), optimal use of facilities (0.123) and participation in solving organizational issues (0.118). Additionally, based on the implemented sensitivity analysis approaches, fuzzy VIKOR generates more reliable results and also has higher robustness than fuzzy GRA.

Comparison of improving energy use and mitigating pollutant emissions from industrial and non-industrial activities: Evidence from a variable-specific productivity analysis framework.

This paper seeks to account for differences in productivity of the industrial and non-industrial activities in the productivity analysis framework. The Luenberger productivity indicator is widely applied to analyze the productivity change, and can be decomposed as it follows the additive structure. But there have been few studies on sector operation performance and industrial structure involving both the industrial and non-industrial inputs, output and air pollutant emissions. Resorting on the China's province-level data on energy, output and air pollutants from 2006 to 2019, we find that the industrial SO2 emissions, energy consumption and NOX emissions are the major factors leading to sector operation inefficiency. By decomposing the operation performance indicator (OPI), we observe that contribution to productivity change by energy consumption, air pollutant emissions and output is higher than contribution by the non-industrial variables. Furthermore, technical progress offsets negative efficiency growth. In order to implement energy conservation, emissions reduction and industrial restructuring at the provincial level, China's government should take efforts to improve the efficiency of non-industrial energy consumption and support the development of cleaner industries.

The challenges of COVID-19 control policies for sustainable development of business: Evidence from service industries.

Such large-scale disruptions as the pandemic increase the uncertainty and risk related to business. Therefore, the business continuity management (BCM) has become an essential technical solution for enterprise emergency response. Since the beginning of 2020, the COVID-19 has spread worldwide at an alarming rate causing many threats to sustainable development of the business sector. The decline in consumer demand has hugely impacted service industries, such as wholesale and retail sales, tourism. Enterprise production and operations have faced severe challenges. In this study, we develop a risk factor analysis of BCM under the presence of COVID-19 in China. Based on a statistical survey of 940 enterprises in Hangzhou City, China, this study employs ordinal logistic regression to explore the hindering effect of risk factors introduced by the epidemic on business performance. Then, the interpretive structure model (ISM) is applied to analyze the hierarchical structure of the factors under examination. The key factors influencing the enterprise production and operation during COVID-19 outbreak significantly differ across the sub-sectors of the service industry. Therefore, this paper assesses the resilience of the productive technologies and business models of different industries amid the pandemic. This paper proposes epidemic prevention and control strategy focusing on investment and government regulation to ensure sustainable business development.

Association between socioeconomic welfare and depression among older adults: Evidence from the China health and Retirement Longitudinal Study.

This study aims to examine the association between province-level socioeconomic welfare factors and depression symptoms among older adults in China. Province-level socioeconomic characteristics were merged with microdata for respondents over 65 years from the 2018 China Health and Retirement Longitudinal Study (CHARLS) Wave 4 (N = 6657). Principal component analysis (PCA) was used to extract three socioeconomic welfare factors constructed from 14 province-level variables. A Bayesian mixed-effects logistic model was applied to measure the association between the three socioeconomic welfare factors and depression symptoms while controlling for socio-demographic variables. The PCA showed that economic welfare, medical resource welfare, and social service welfare together explained 72.2 percent of the total variance of the 14 province-level variables. It was found that increasing economic welfare was significantly associated with a lower probability of depression symptoms (OR = 0.806, 95%CI: [0.674, 0.967]), while medical facilities were associated with a higher probability of depression symptoms (OR = 1.181, 95%CI: [1.029, 1.354]) among Chinese older adults. Uncertainty existed as to whether having access to social welfare (OR = 0.941, 95%CI: [0.835, 1.060]) was associated with prevalence of depression. Thus, improved socioeconomic welfare systems for older adults (which possibly require an increase in spending) are necessary to contribute further to reduced depression risk in China. Policymakers should also improve the utilization of medical resources to mitigate the incidence of depression among the elderly in China.

Are women neglected in the EU agriculture? Evidence from Lithuanian young farmers.

The agriculture in Eastern Europe has seen a number of economic and social transitions. This research examines the gender inequality in agriculture by taking the case of an Eastern European country - Lithuania - as an example. The questionnaire survey was employed in order to check the existence of gender inequality. The study focuses on the young farmers as they are more likely to implement innovations and shape the future agricultural activities. The demand for advisory services and participation in the Common Agricultural Policy measures were used to compare the activities and perceptions of men and women young farmers. We found that there are no significant differences in participation of support measures and demand for advisory services across the genders. This suggests Lithuanian agricultural sector is equally beneficial for men and women young farmers. Given the differences in the educational background, a positive effect is anticipated if women were more empowered in Lithuanian agriculture. Women's participation in agriculture could increase environmental awareness, propensity to innovate and economic resilience.

Is environmental regulation effective in promoting the quantity and quality of green innovation?

Green innovation (GI) is an important means of achieving a win-win outcome in the form of both economic development and environmental protection. Using a unique Chinese Patent Census Database to identify the quantity and quality of GI in each province and panel data for Chinese industrial sector in 30 provinces from 2002 to 2015, we investigated the impact of environmental regulation (ER) on GI in China. This study presents the first attempt to identify green innovation quality in China. Empirical results show that there is an inverted-U relationship between ER and GI. The heterogenous effects are further investigated in order to obtain more accurate policy implications. The results indicate that the impact of ER on GI is insignificant in the central and western regions, implying the necessity of adjusting ER policies in these regions. Second, the inverted U-shaped relationship between ER and GI only occurred in provinces with high state-owned enterprise (SOE) ratio, figuring out the special role of Chinese SOEs in promoting GI. Third, the impact of ER on GI is insignificant in regions with high levels of pollution, indicating high potential of green innovation and policy adjustments there.

Productivity change and its driving forces in Chinese healthcare sector.

Since the last medical reform in 2009, China's public hospitals have been facing the changes in the institutional environment. However, the effects of reforms have not been received enough attention to deliver evidence-based implications. In this paper, we first assess the efficiency of regional public hospitals from 2011 to 2018, employing a proposed method based on an additive indicator and an aggregate directional distance function (DDF). The method applied allows for decomposing total factor productivity (TFP) indicator into three components, including technical efficiency change (TEC), total productivity (TP) and scale efficiency change (SEC). Second, following the efficiency assessment, we carry post-efficiency analysis to identify the determinants of efficiency of the public hospitals. The results show that annual average TFP growth rate is 1.38%, which is driven mainly by TEC. Regional disparities of public hospitals' performance are expanding. Almost 75% of the regions considered show a positive TFP growth. The regression results show that the significant determinants of efficiency of regional public hospitals include the price of and demand for health services.

Technical Efficiency of Regional Public Hospitals in China Based on the Three-Stage DEA.

Many countries are facing the increasing cost of healthcare services and the low efficiency of public hospitals. These issues are also evident in China. This paper offers a comprehensive assessment of the efficiency of public hospitals operating in China's 31 regions. The impact of the third round of reform of the health system in 2009 is assessed based on the three-stage data envelopment analysis procedure. The time period from 2011 to 2018 is covered in this study. Due to different functions performed by the public hospitals and other ones, the number of patients with infectious diseases is incorporated as an output variable reflecting the social function. The outpatient visits and inpatient visits are considered to reflect the outputs related to the private functions. The results imply an increase in the mean efficiency of public hospitals from 0.927 to 0.981 after taking the impact of environmental variables and statistic noise into account. These results indicate that the efficiency of public hospitals is dependent in the operational environment. There are 11 regions whose hospitals operate on the efficiency frontier during the whole period covered. Therefore, the Chinese government should reasonably design and apply the regulatory tools to improve the efficiency of public hospitals.

The impact of income inequality on consumption-based greenhouse gas emissions at the global level: A partially linear approach.

The differences in consumption levels across different strata of income and income inequality give raise to differences in the effects of income inequality on the level of the consumption-based greenhouse gas (GHG) emission. However, the impact of inequality on consumption-based emissions has been scarcely analysed. Therefore, the aim of this study is to test the relationship between income inequality and consumption-based GHG emission per capita by applying the country-level data for 1990-2014. Due to the prevailing economic structures, those relationships may be non-linear and imposition of pre-defined functional relationships in the estimation may induce additional bias. In order to circumvent this issue, the partially linear regression is applied in this paper. The non-parametric part of the regression is applied to examine the linkages between the income inequality and GHG emission per capita, whereas the other controlling variables are included in the linear part of the model. The results indicate a non-liner relationship between income inequality and GHG emission per capita along with a U-shape relationship between GDP per capita and the GHG emission per capita. This suggests tailored environmental policies are required for regions with diverse economic structures. This paper reveals how to achieve the reduction of income inequality and climate change simultaneously.