The impact of agriculture production and renewable energy consumption on CO2 emissions in developing countries: the role of governance.

Environmental pollution has aggravated the climate change issues posing unusual challenges to the survival and growth of humanity, including extreme weather, loss of species, and sustainability of the ecosystem in developing countries. Unlike previous studies, this paper adds new dimension to the literature by incorporating corruption into agriculture production-environment nexus. This study adds new dimension to the literature by examining corruption, agriculture, and renewable energy on CO2 emissions. The study therefore examines the effects of governance (corruption) and agriculture production on CO2 emissions in 20 countries in Africa from 1990 to 2019. The study employed recent panel econometric approach which accounts for cross-sectional dependence in the variables. The findings of the fixed effect model and panel dynamic ordinary least squares (PDOLS) show that forest and renewable energy consumption decrease CO2 emissions. However, corruption, agriculture production, export, and urbanization escalate CO2 emissions in African countries covered in the paper. Moreover, the Dumitrescu-Hurlin Granger causality indicates a bidirectional causality between agriculture production and CO2 emissions, renewable energy use, agricultural output, and forest. Also, unidirectional Granger causality runs from corruption to forest and agriculture production. On these premises, consented efforts by governments should be made to support good institutions in order to promote good governance to avert pervasive consequences of corruption on the environment.

Environmental Regulation Effect on Green Total Factor Productivity: Mediating Role of Foreign Direct Investment Quantity and Quality.

Green total factor productivity (GTFP) is an excellent index for green development. The objective of this study was to check whether environmental regulation (ER) can affect GTFP through the mediating role of foreign direct investment (FDI) quantity and quality. Using the super-efficiency Epsilon-based measure (EBM) model and a Malmquist-Luenberger (ML) index, China's GTFP growth was measured during 1998-2018. On this basis, we adopted a Systematic Generalized Method of Moments (SYS-GMM) to analyze the effect of ER on GTFP. The findings show that China's GTFP declined first and rose again during the sample period. GTFP in the coastland was greater than that in the inland region. ER positively affected China's GTFP growth. FDI quantity and quality mediated the nexus between ER and GTFP growth in the whole nation. Specifically, this mediation role of FDI quantity and quality was only significant in coastal China. Additionally, financial development can also boost GTFP growth in China. Given the importance of developing a green economy, the government should improve the FDI quality and attract green FDI.

Examining the determinants of water resources availability in sub-Sahara Africa: a panel-based econometrics analysis.

With the rapid development of economies, the problem of water resources availability particularly in sub-Sahara Africa (SSA) has increased significantly. Specifically, in recent times, addressing the challenge of access to water resources has become a global issue of which countries in SSA are not exceptional since the adequate supply of potable water is as relevant as economic development. Consequently, this current paper seeks to estimate the determinants of water resources availability in sub-Sahara Africa. For this purpose, a panel-based regression model, which represents the availability of water resources, is specified based on the period 2000 to 2016 to examine a panel of 41 SSA countries sub-sectioned into low, lower-middle, and upper-middle-income nations. Considering the existence of residual cross-sectional reliance, outcomes based on the CIP and CADF unit root tests showed that the variables were not integrated at the same order. This thus leads to the employment of the PMG/ARDL estimation approach which unveiled that (i) agriculture production has a significant negative influence on H2O in the lower-middle and low-income panel of SSA countries whereas in the upper-middle-income panel, an insignificant impact is witnessed; (ii) CO2 emissions affect H2O palpably in the upper-middle-income SSA panel while for lower-middle and low-income panels, an adverse effect is identified; (iii) economic growth adversely influenced H2O resources in the lower-middle-income panel whereas in the case of the low-income panel, a significant positive liaison is evidenced; (iv) excluding low-income panel, industrial development concerning H2O has a significant negative influence in upper-middle and lower-middle-income panels; (v) urbanization homogeneously showed a positive relationship with H2O resources across all panels. The results are reconfirmed by the CCEPMG/CS-ARDL and MG employed as robust methods. Causality checks by Dumitrescu-Hurlin test finally revealed a mixture of results regarding the causal paths amid variables among the country panels. Policy recommendations have therefore been proposed based on the study findings.

The influence of technological innovation and human capital on environmental efficiency among different regions in Asia-Pacific.

This study employs super-efficiency DEA model with desirable inputs and an undesirable output in calculating environmental efficiency values in different regions in Asia-Pacific from 1990 to 2018. The study compares environmental efficiency index in South East Asia, South Asia and East Asia. The study also evaluates the determinants of environmental efficiency using truncated regression. The mean environmental efficiency score demonstrates that East Asia region is highly efficient whereas South East Asia is the least efficient. Results from the truncated regression established an inverted U-shape relationship between environmental efficiency and Technological Innovation (TI) in the main panel, and the three regions. Also, economic growth shows an inverted "U" shape link with environmental efficiency in the panels except in South East Asia. Human capital promotes environmental efficiency in the main panel and the rest of the regions. Moreover, while FDI promotes environmental efficiency in the main panel and East Asia, it reduces environmental efficiency in both South East and South Asia regions within the Asia-Pacific. In addition, an interaction effect between technological innovation and renewable energy use, advances environmental efficiency within the entire study countries. Based on the findings the study proposes several policy recommendations.

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.

The influence of trade openness on environmental pollution in EU-18 countries.

Trade openness is one of the main channels of globalization and technological transfers. In environmental economic literature, the implications of trade openness remain controversial and still could be potential drivers of carbon dioxide emissions. This study therefore explores the effect of trade openness in developed countries using EU-18 economies. We employed an econometric approach that accounts for cross-section dependence among study variables. The panel CIPS and CADF unit root show that the variables are stationary and the long-run relationship was confirmed in Westerlund cointegration tests. The mean group (MG) and augmented mean group (AMG) results show that trade openness increases CO2-emissions in EU-18. Again, energy consumption and urbanization escalate emissions. The study confirmed the environmental Kuznets curve. Finally, pollution halo and pollution haven hypothesis were confirmed at both estimation methods. The Dumetriscu-Hurlin Granger causality test results confirmed bidirectional causality between trade openness and energy consumption and between trade openness and economic growth. Again, unidirectional Granger causality is running from trade openness and CO2 emissions. Policy recommendations are further proposed.

Spatial and temporal heterogeneity of environmental efficiency for China's hotel sector: new evidence through metafrontier global Malmquist-Luenberger.

With the adding of tourist volume in China, carbon emissions from hotel sector increased greatly. Environmental efficiency of hotel sector considering technology heterogeneity is mainly analyzed across different regions of China from 2000 to 2013. Metafrontier global Malmquist-Luenberger (ML) is implemented to evaluate environmental efficiency of hotel sector. Furthermore, we analyze whether technology heterogeneity of different regions increased or not through technological gap ratio. The empirical analysis revealed that the east had the highest environmental efficiency under metafrontier after 2009. After 2009, technological gap ratio (TGR) in the east ranked highest among four regions in China. Environmental regulation positively impacts environmental efficiency under group frontier of hotel sector in the model of nation, east, and middle. Urbanization has U-shaped link with environmental efficiency of hotel sector for the east. It is important to strengthen environmental regulation to reduce carbon emissions. Last, it is important to enhance consciousness of energy abating and carbon emissions reduction of hotel customers.

Different impacts of export and import on carbon emissions across 7 ASEAN countries: A panel quantile regression approach.

ASEAN (Association of Southeast Asian Nations) has contributed numerous carbon emissions during the phase of industrialization. This study mainly compares the different effects of export and import on CO2 emissions across 7 ASEAN countries over 1990-2017. In addition, we investigate how technological innovation affects carbon emissions. Stationary tests are conducted through cross section dependence, unit root of panel data, and Westerlund cointegration. The results of panel quantile regression show that export and import both have adverse effects on CO2 emissions. EKC is valid in these countries. Moreover, population size and energy intensity increase carbon emissions. In particular, technology innovation significantly reduces carbon emissions by augmenting energy efficiency. It is important to improve eco-innovation, and expand knowledge-intensive industries in ASEAN countries.

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.

The effects of economic growth and innovation on CO2 emissions in different regions.

Economic growth and economic energy consumption have received greater attention due to its contribution to global CO2 emissions in recent decades. The literature on CO2 emissions and innovation for regional differences is very scanty as there is not enough study that considered different regions in a single analysis. We adopt a holistic approach by incorporating different regions so as to assess how innovation contributes to emission reduction. The study, therefore, examined the effects of innovation and economic growth on CO2 emissions for 18 developed and developing countries over the period of 1990 to 2016. The study used panel technique capable of dealing with cross-section dependence effects: panel cross-sectional augmented Dickey-Fuller (CADF) unit root to determine the order of integration, Westerlund cointegration tests confirmed that the variables are co-integrated. We employed panel fully modified ordinary least square (FMOLS) and panel dynamic ordinary least square (DOLS) to estimate the long-run relationship. The results show that energy consumption increases CO2 emissions at all panel levels. However, innovation reduces CO2 emissions in G6 while it increases emissions in the MENA and the BRICS countries. Environmental Kuznets curve (EKC) hypothesis is valid for the BRICS. The pollution haven hypothesis (PHH) and pollution halo effect were confirmed at different panel levels. Based on the findings different policy recommendations are proposed.

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.