The environmental consequences of foreign aid and key economic indicators: the Sino-Africa perspective.

The study differs substantially from earlier studies, by probing the environmental consequences of foreign aid and selected key economic indicators with a special focus on Sino-Africa. The study focused on China and its top foreign aid recipients in Africa in the last decade. This paper utilizes the Dynamic Augmented Mean Group Estimator (AMG), a robust and recent econometric approach to provide better statistical inferences; crucial for policy formulation and future reforms on foreign aid, trade, energy, pollutions, and economic growth of economies. The findings of the study revealed the China's Foreign aid oriented towards infrastructure has varying impacts on the economic growth and the environment of most recipient African Countries. The findings revealed the incidence of foreign aid ameliorating pollution of the countries: Nigeria and Morocco under strong domestic institutions. The study is of key relevance for policymakers and stakeholders as it explicates the key pillars, policies, and guidelines needed for foreign aid, trade, economic growth, and related internal reforms for mitigating resulting environmental pollution across a wider international context.

Towards Ecological Sustainability: Assessing Dynamic Total-Factor Ecology Efficiency in Africa.

Ecological footprint (EF) and human development index (HDI) are two critical indicators for assessing sustainable development worldwide. Past studies in Africa have ignored dynamic sustainable total-factor ecological efficiency (DSTFEE) assessment. This present study proffers a novel dynamic sustainable total-factor ecological efficiency (DSTFEE) that comprehensively assesses the ecological efficiency among 44 sampled African economies from 2010 to 2016. Our study incorporates EF and HDI in the model. Second, the study evaluates regional DSTFEE heterogeneity efficiency as well as the technological gap efficiency in Africa. Further, projection analysis is done to offer a viable solution path to address the inefficient African countries. Third, the study investigates the determinants of ecological efficiency using the bootstrap truncation regression technique. The results from the implemented models are as follows: first, the DSTFEE for the 44 sampled African countries is very low (0.403), indicating enormous potential for improvement. Second, the heterogeneity of DSTFEE across the five Africa regional blocs is evident. The southern bloc had the highest efficiency score, followed by the northern, central, western, and eastern regions. The technology gap ratio also reveals a massive gap among the five Africa regional blocs. Third, the bootstrap truncation regression results established a U-shape nexus between growth and DSTFEE in Africa. REC and trade openness is positively corrected to DSTFEE for African countries. In contrast, financial development, foreign direct investment (FDI), and urbanization impede dynamic ecological efficiency in Africa. The study's results equip African countries with adequate knowledge of their ecological efficiency situation and provide them a viable path to improve environmental efficiency, thereby boosting their ecological sustainability.

Predicting the carbon dioxide emission of China using a novel augmented hypo-variance brain storm optimisation and the impulse response function.

For the past decade, the level of carbon dioxide emission in most cities in China is on the ascendancy. Yet, better prediction of environmental pollution is at the fringes of recent studies. Several erstwhile researchers have attempted predicting pollution whilst utilising approaches including the ordinary linear regressions, multivariate regressions, autoregressive integrated moving average (ARIMA), evolutionary and some conventional swarm intelligence. These conventional approaches, however, lead but to imprecise predictions owing to the inherent parameter problems characterised in those approaches. Consequently, there is the need for a better prediction of the key antecedents that affect air pollution whilst using robust techniques. This current study, therefore predicts the carbon emissions levels of China into the next decade, in response to changes in key economic variables: energy consumption, economic growth, trade, and urbanisation. This is to aid in monitoring and implementing of tailored policies and transformations in China and in similar developing and emerging economies. Our findings revealed a steadily rise in emissions as the economy grows during the initial years but decline in the ensuing forecasted period. The findings of the impulse response function, revealed that in the next decade, urbanisation, and trade (import and export) will be the major contributors of carbon dioxide emission. The proposed Brainstorm optimisation algorithms prediction model was verified and validated with actual data. Our study revealed that the Brainstorm Optimisation algorithm predicts better with less prediction error even under uncertainty information.

Environmental pollution of China to foreign investors: detrimental or beneficial?

This study investigates the dynamic linkage among foreign direct investment, energy consumption, and environmental pollution of China spanning from 1990 to 2014. Despite the extant literature on the FDI-energy-growth-environmental pollution nexus, most of the conclusion seems inconsistent. Hence, this study utilized recent econometric techniques such as the dynamic ordinary least square (DOLS), autoregressive distributed lag (ARDL) bounds test approach, Gregory and Hansen structural cointegration, and the bootstrap Granger causality. The study also disaggregated energy consumption into various sources to identify their respective distinct impact on the environment. Our study confirmed the presence of the EKC curve for China in a quadratic equation applying the DOLS. The result of the bootstrapped Granger causality confirmed the presence of a unidirectional Granger causality running from CO2 emission to economic growth and export; non-renewable energy to economic growth, export to economic growth, and renewable energy; and urbanization to economic growth. Moreover, our study recognized the presence of a bi-directional connection between FDI and economic growth. Our study highly recommends that China modify its energy mix by incorporating more renewable energy resources such as hydro, wind, geothermal. Additionally, the regulatory bodies should strictly implement improved energy efficiency in the various sectors that complement total proper urban land usage as the urban population to total population significantly impelled an upsurge in environmental deterioration in China.

Dynamic analysis of green investment decision of manufacturer.

With the continuous development of green manufacturing concept, more and more enterprises attempt to increase their green investment to promote the utilization of resources. In order to help enterprises make the optimal green investment decision, firstly, this paper constructs a duopoly competition game model based on the manufacturer's limited rationality. Then, the Nash equilibrium solution of the system is discussed by using the reverse induction method. Finally, the system is simulated to study the green input decision and the impact of green input cost on the manufacturer's output and profit. By adding external control signals, the chaos state of duopoly competition game model is restrained. The results show that the manufacturer's optimal green investment portfolio lies in the stable region of Nash equilibrium. Secondly, in the duopoly competition game model, when the initial value of green input adjustment rate and cost changes slightly, the evolution of production and profit of manufacturing enterprises will be greatly different. Thirdly, the study revealed that the addition of external control signals can effectively control the chaotic situation of the market and subsequently restore the order of the participants and the market. Therefore, our research provides a reference for enterprises to make green input decision; improve the efficiency and rationality of enterprise management and further promote the green development of enterprises.

Innovation and CO2 emissions: the complimentary role of eco-patent and trademark in the OECD economies.

Increasing global emissions has led to research on the role of innovations play combating emissions. Mitigations from innovation perspective have mainly been focused on the role of patent, ignoring the role of trademarks. We therefore investigate the mitigating power of patent and trademarks in the OECD economies, benchmarking patent as the traditional mitigation strategy. Examining the complimentary role, we created an interaction term between patent and trademark. Our study divided the OECD economies into four subpanels which are OECD America, OCED Asia, OECD Europe, and OECD Oceania. We employed the Im, Pesaran and Shin W-stat, Augmented Dickey-Fuller, and Phillips Perron unit root tests, as well as cross-sectional dependence and Westerlund cointegration tests for the preliminary test on the variables. We also adopted ARDL approach to cointegration, Granger causality test, and OLS in examining the relationship between CO2 and patent, trademark, urbanization, and economic growth. Findings show that jointly, eco-patents and trademarks mitigate CO2 emissions. Also, bidirectional or unidirectional causal relationship was established between our variables of study, an indication that most of our variables can be used in forecasting one other.

Rejuvenating The Concept Of Work Alienation Through Job Demands-Resources Model And Examining Its Relationship With Emotional Exhaustion And Explorative And Exploitative Learning.

PURPOSE: The purpose of the present study was twofold. First, this study examined the relationships of work alienation with explorative learning and exploitative learning. Second, the study tested the role of emotional exhaustion as a mediator of the relationships of work alienation with explorative learning and exploitative learning. Job Demands-Resources model was used as the underlying theoretical foundation to establish these relationships. METHODS: Two-source time-lagged data were collected from 225 middle-level managers and their 222 immediate supervisors in 87 Pakistani firms spanning different industries. Structural equation modeling and bootstrapping were used to test the hypothesized relationships,. RESULTS: The study revealed that work alienation is negatively related to both explorative learning and exploitative learning. Moreover, the study also established emotional exhaustion as a mechanism underlying the relationships work alienation with explorative learning and exploitative learning by showing that work alienation enhances emotional exhaustion, which, in turn, negatively influences both explorative learning and exploitative learning. CONCLUSION: By conceptualizing and providing empirical evidence of the negative relationships of work alienation with explorative learning and exploitative learning, both directly and via emotional exhaustion, the study signified some of the important but largely ignored dynamics of the employment relationship within the current regime of organizational structures. The findings suggest that the managers' sensed estrangement from work and work context need to be addressed, as it can exhaust them emotionally and hinder their search and acquisition of new knowledge and competencies.

A study on the causal effect of urban population growth and international trade on environmental pollution: evidence from China.

This study seeks to contribute to the recent literature by empirically investigating the causal effect of urban population growth and international trade on environmental pollution of China, for the period 1980-2014. The Johansen cointegration confirmed a long-run cointegration association among the utilised variables for the case of China. The direction of causality among the variables was, consequently, investigated using the recent bootstrapped Granger causality test. This bootstrapped Granger causality approach is preferred as it provides robust and accurate critical values for statistical inferences. The findings from the causality analysis revealed the existence of a bi-directional causality between import and urban population. The three most paramount variables that explain the environmental pollution in China, according to the impulse response function, are imports, urbanisation and energy consumption. Our study further established the presence of an N-shaped environmental Kuznets curve relationship between economic growth and environmental pollution of China. Hence, our study recommends that China should adhere to stricter environmental regulations in international trade, as well as enforce policies that promote energy efficiency in the urban residential and commercial sector, in the quest to mitigate environmental pollution issues as the economy advances.

The effect of innovation on CO2 emissions of OCED countries from 1990 to 2014.

Human activities are accelerating CO2 emissions all over the world most especially in high-income nations, spurring the rise in greenhouse gas emissions. For decades, technologies have been developed and patented in response to the environmental problems. There is an outcry for innovative ways to combat the environmental menace. This attests to the enormity of research being done, in recent years, to investigate how innovation can help mitigate CO2 emissions. This research aims at investigating into the effect of innovation on CO2 emissions in 28 OCED countries at an individual level for the recent period 1990 to 2014. The source of data for our utilized variables is the World Bank Indicators. Our study employed three key models based on the STIRPAT model, the economic-EKC growth model, and the innovation-EKC model. The findings of our study revealed that innovation plays a key role towards mitigation of CO2 emissions in most OECD countries. Its impact, however, varies across the countries, depending on some key factors and channels elucidated in this paper. Additionally, our study asserts that improvement in GDP per capita leads to the rise in CO2 in most OECD economies, although mitigate emissions in few OECDs; hence, the economic-EKC model is not valid for most economies. Non-renewable energy accelerates emissions whiles renewable energy sources mitigate emissions. Research and development (R&D) improves environmental quality and the EKC for both economic growth and innovation, valid for a few economies of the OECDs. We conclude that innovation is necessary in mitigating CO2 emissions; hence, governments and policy makers should invest and promote innovative renewable energy sources.

Carbon dioxide emission and economic growth of China-the role of international trade.

This study investigates the role of international trade in mitigating carbon dioxide emission as a nation economically advances. This study disaggregated the international trade into total exports and total imports. A multivariate model framework was estimated for the time series data for the period of 1970-2014. The quantile regression detected all the essential relationship, which hitherto, the traditional ordinary least squares could not capture. A cointegration relationship was confirmed using the Johansen cointegration model. The findings of the Granger causality revealed the presence of a uni-directional Granger causality running from energy consumption to economic growth; from import to economic growth; from imports to exports; and from urbanisation to economic growth, exports and imports. Our study established the presence of long-run relationships amongst carbon dioxide emission, economic growth, energy consumption, imports, exports and urbanisation. A bootstrap method was further utilised to reassess the evidence of the Granger causality, of which the results affirmed the Granger causality in the long run. This study confirmed a long-run N-shaped relationship between economic growth and carbon emission, under the estimated cubic environmental Kuznet curve framework, from the perspective of China. The recommendation therefore is that China as export leader should transform its trade growth mode by reducing the level of carbon dioxide emission and strengthening its international cooperation as it embraces more environmental protectionisms.