Corrigendum to "CO2 behavior amidst the COVID-19 pandemic in the United Kingdom: The role of renewable and non-renewable energy development" [Renew. Energy 189 (2022) 492-501].

[This corrects the article DOI: 10.1016/j.renene.2022.02.111.].

Identifying the roles of energy and economic factors on environmental degradation in MINT economies: a hesitant fuzzy analytic hierarchy process.

Globally, research communities have been studying the different determinants of environmental degradation or pollution using different contexts and methods. In this study, we identify several energy and economic factors, such as energy consumption (EC), gross domestic product (GDP), energy production (EP), urbanization (URB), and foreign direct investment (FDI) as the most effective factors of environmental degradation by obtaining several environmental researchers' opinions and using the hesitant fuzzy analytic hierarchy process. In the later stage of the analysis, we use these variables as regressors of the ecological footprint (EF) as a proxy for environmental degradation. Since we find evidence of cross-sectional dependence among the members of the variables, we use second-generational panel tests. First, we test the stationarity of the variables using the cross-sectionally augmented IPS (CIPS) panel unit test. The results show that the regressors have different orders of integration. So, we employ the Durbin-Hausman panel cointegration test to test the existence of a long-run relationship between the variables. Having found a long-run relationship, we estimate the long-run coefficients using the common correlated effects mean group estimator, which reveals that energy consumption has an increasing effect on the EF in Indonesia and Turkey, while energy production has a negative impact in Mexico and Turkey. While GDP has an increasing effect in all countries, FDI has a similar effect in only Indonesia. Moreover, URB decreases the ecological footprint in Nigeria, while it increases in Turkey. Our approach to the evaluation of environmental degradation can be generalized to other regions as well as where there is a significant need to understand the roles of different drivers on environmental degradation or pollution.

The roles of organic farming, renewable energy, and corruption on biodiversity crisis: a European perspective.

The loss of biodiversity has profound implications for nature's contributions to people and their health. This study intends to examine the factors responsible for biodiversity loss as well as the coping mechanisms to address this crisis in the context of 35 European economies covering the 2009-2018 period. The study utilises both the static and dynamic panel estimation techniques to examine the above issue. Specifically, the study applied Driscoll and Kraay (1998a), Driscoll and Kraay (Rev Econ Stat 80:549-560, 1998b) and Panel Corrected Standard Approach (PCSE) for the static panel models. As for dynamic panel models, the study employs linear dynamic panel model by Arrelano and Bond (Rev Econ Stud 58:277-297, 1991) and Arrelano and Bover (J Econom 68:29-51, 1995)/Blundell and Bond (J Econom 87:115-143, 1998) system generalised methods of moments (GMM). Morandeover for robustness purposes, fixed and random effect models are also applied. The findings indicate that renewable energy use increases biodiversity crisis whereas organic farming is beneficial for biodiversity preservation in Europe. Corruption and gender gap were found to increase the biodiversity crisis. The evidence also suggests a positive and significant effect of forest area, e-governance and social progress on biodiversity. Finally, the study provides insightful implications for stakeholders and practitioners associated with energy and biodiversity conservation in Europe.

Inequality consequences of natural resources, environmental vulnerability, and monetary-fiscal stability: a global evidence.

Despite making significant progress in reducing poverty over the last several decades, the world has witnessed persistent surge in global inequality. The aim of this study is to investigate the relationship between natural resource, environmental vulnerability, monetary-fiscal stability, and inequality in a global perspective during 2005 to 2019 for 61 countries. We distinguish between consumption and income inequality to see whether the variables under study have different implications for different measurement of inequality. The study employs Driscoll-Kraay standard error method which can account for the cross-sectional dependence between the countries. The study divides 61 countries according to the World Bank income classifications to provide evidence of heterogeneity in the sample economies. The main finding highlights that natural resources induce both consumption and income inequality whereas greenhouse gas emissions have been found to reduce the inequality of both types. Quality of government and access to electricity decrease consumption and income inequality while technological innovation and monetary-fiscal stability have incremental impacts on inequality. The coefficient of natural disaster has been shown to be positive for consumption inequality but negative and insignificant for income inequality. When analyzing moderating impacts, we find that quality of government cannot moderate the positive impact of natural resources on consumption inequality, but it can exacerbate the resources' impact on income inequality. The result for sub-sample group also differs for consumption and income inequality. The study recommends management of natural resources in a sustainable way with the help of good governance.

The roles of energy, natural resources, agriculture and regional integration on CO2 emissions in selected countries of ASEAN: does political constraint matter?

This paper empirically examines the effects of energy, natural resources, agriculture, political constraint and regional integration on CO2 emissions in four ASEAN (Association of Southeast Asian Nations) countries of Cambodia, Malaysia, Indonesia and Thailand. We distinguish between renewable and fossil fuel energy consumption to see their individual impacts on CO2 emissions. The study employed a panel data from 1990 to 2019 derived from sources such as World Development Indicators, which were then analysed using Common-Correlated Effect Mean Group (CCEMG) and Augmented Mean Group (AMG) estimates. The findings show that renewable energy consumption has a negative impact on CO2 emissions while fossil fuel energy degrades the environment. The role of natural resources was found to be favourable for environmental quality with the impact of agriculture being found to be detrimental. For regional trade integration, its influence was not significant enough to offset CO2 emission. Furthermore, we discovered that political constraint induces CO2 emission. Based on the result, it is recommended that the selected ASEAN countries promote the use of renewable energy and clean technologies in their manufacturing processes, conserve natural resources, adopt eco-friendly political policies and intensify regional integration to accelerate the achievement of the SDGs.

A Gender Differentiated Analysis of Healthy Life Expectancy in South Asia: The Role of Greenhouse Gas Emission.

The sluggish progress concerning SDG-9 and SDG 13 has made South Asia an epicentre of household and ambient greenhouse gases emissions. Furthermore, the regional progress concerning attainment of SDG-3 is considerably low. The major research objectives are twofold. First, to explore the impact of GHGs emissions from agriculture, transportation, and manufacturing sector on disaggregated life expectancy. Second, to examine the mitigating impact of renewable energy use, trade integration, and human capital development for practice policy recommendations. These research objectives are realized by employing recently advanced cross-sectional auto regressive distributed lag (CS-ARDL) model on panel data of five South Asian countries such as Bangladesh, India, Pakistan, Nepal, and Sri Lanka from 1990 to 2019. The estimation outcome reveals that the emissions from transportation, manufacturing, and agricultural sectors significantly deteriorate healthy life expectancy of male and female healthy life expectancy in South Asia with different intensity. Especially, we find that long-run impact of GHG is more profound on male healthy life expectancy than female life expectancy. The result further shows that renewable energy and human capital substantially improve healthy life expectancy, whereas the effects of trade integration are insignificant. The finding of moderating variables shows that renewable energy, human capital development, and trade integration have high potential to reduce GHGs emissions. The findings of this study urge South Asia for investments in human capital development and renewable energy along with fostering regional integration to decrease GHG and improve healthy life expectancy.

Nexus between environmental vulnerability and agricultural productivity in BRICS: what are the roles of renewable energy, environmental policy stringency, and technology?

This study aims to examine the effect of carbon dioxide emission and air pollution on agricultural productivity while accounting for the effect of renewable energy use, ICT, technological innovation, environmental policy stringency, and democracy for Brazil, Russia, India, China, and South Africa (BRICS) during the period 1990-2019. Several econometric procedures including mean group estimates are employed. The result suggests that both carbon dioxide emission and air pollution negatively affect the productivity of the agricultural sector. The effects of renewable energy, ICT, technological innovation, and democracy are found to be increasing agricultural productivity. Environmental policy stringency coefficient confirms the porter hypothesis. The result from the causality test suggests that bidirectional causality exists between CO2, PM2.5, renewable energy, technological innovation, ICT, and agricultural productivity. Finally, the study provides several policy suggestions for the governments of the BRICS economies in order to increase agricultural productivity while tackling the environmental vulnerability.

Tourism adaptability amid the climate change and air pollution in BRICS: a method of moments quantile regression approach.

The main objective of this paper is to look at how environmental degradation in the form of climate change and air pollution affect international tourism for five countries such as Brazil, Russia, India, China, and South Africa (BRICS) over the years 1990-2019. Other independent variables include information and communication technology (ICT) and democracy. We also look at the role of environmental regulation to see the validity of porter hypothesis in the tourism sector. To achieve this objective, we apply a novel method of moments quantile regression approach as well as a robust causality technique. The result shows that at lower and medium quantile, CO2 emission has positive impact on tourism while at higher quantile, CO2 emission has negative but insignificant effect on tourism in BRICS countries. The result for PM2.5 is uniform across all the quantiles, showing the negative effect on tourism. ICT and human capital positively affect the tourism while democracy has negative impact on the tourism sector of the BRICS nations. The result also validated the Porter hypothesis for tourism sector. We conclude that tourism industry stakeholders and the environmental policymakers must work together to integrate tourism policies with BRICS countries' environmental conservation policies as part of the transition to sustainable tourism industry.

Measuring the poverty reduction effects of adopting agricultural technologies in rural Ethiopia: findings from an endogenous switching regression approach.

The purpose of this study is to understand how the adoption of different agricultural technologies can reduce poverty in rural regions of Ethiopia. To attain this objective, this paper uses a comprehensive socio-economic survey of Ethiopia, which allows us to securitize the household level information. The paper uses a multinomial endogenous switching regression model to estimate the impact of alternative technologies adoption on poverty reduction on a sample of 2316 farm households, and a multinomial logit model to estimate the determinants of alternative agricultural technologies adoption. The results showed that the decision to adopt alternative agricultural technologies depends on several variables such as education, regional heterogeneity, remittance income, extension visit, credit access, off-farm activity, soil quality, farm size, tropical livestock unit, distance, plot's potential wetness, and ownership certification. The impact results of the study show that household consumption increases when households adopt alternative agricultural technologies, thereby reducing their poverty. Furthermore, adoption of a package of technologies can result in higher food and total consumption per adult than single technology adoption. The paper recommends strategies for further disseminating and scaling up these technologies to help reduce poverty in Ethiopia.

Quantifying the effect of waste on soil health in European Union: what are the roles of technology, natural capital, and institutional quality?

With a surge in both hazardous and non-hazardous waste in recent decades, European Union countries are losing their soil quality which in turn affects the agricultural production of their economies. Taking this into account, this study presents the effect of hazardous and non-hazardous waste, plastic waste, and electronic waste on soil health for 24 European Union (EU) countries during 2004-2018 period. The impacts of several other variables such as technological innovation, ICT, natural capital, fossil fuel energy consumption, and institutional quality on soil health are also examined. To achieve the above objectives, we employ Driscoll-Kraay technique as the main methodology as well as panel spatial correlation consistent (PSCC) standard errors and quantile estimation at median. The results demonstrate that electronic waste has a negative effect on soil health while the effect of total hazardous and non-hazardous waste and plastic waste on soil health remains insignificant. Technological innovation, ICT, and institutional quality, as well as fossil fuel energy consumption, have positive impacts on soil health. Furthermore, natural capital moderates the effect of plastic and electronic waste on soil health. The study finally provides precise policy recommendations for the EU countries such as proper handling of wastes, promoting strong institutional quality as well as use of technology to enrich the soil nutrient balance.

Analyzing the Nexus Between Geopolitical Risk, Policy Uncertainty, and Tourist Arrivals: Evidence From the United States.

This study attempts to explore the causal linkage of the COVID-19 pandemic, economic policy uncertainty, geopolitical risk, and tourism arrivals in the United States taking data from January to November 2020. In order to analyze the above relationship, this study uses a novel time-varying granger causality test developed by Shi et al. (2018), which incorporates its three causality algorithms such as forward recursive causality, rolling causality, and recursive evolving causality. The findings from forward recursive causality could not confirm any significant causal relationship between COVID-19 and tourism, geopolitical risk (GPR) and tourism, economic policy uncertainty and tourism, and geopolitical risk and COVID-19 but found causality between economic policy uncertainty and COVID-19. The rolling window causality reported bidirectional causality between COVID-19 and tourism and unidirectional causality running from tourism to geopolitical risk. However, the recursive evolving causality identified a significant bidirectional causal relationship between all the variables. Based on the findings, policy implications for the tourism sector are provided.

Does political risk spur environmental issues in China?

China is one of the largest emitters of carbon dioxide (CO2) emissions in the world. Therefore, it is essential to explore the determinants of CO2 emissions in China. But previous studies so far have not examined how the political risk of this country can affect its CO2 emissions due to the lack of a long-term dataset. Hence, this study aims to capture the effect of political risk on China's CO2 emissions while controlling renewable energy consumption, technological innovation, and the economy's economic growth. We employ Bayer and Hanck cointegration, FMOLS, DOLS, CCR, and frequency domain causality tests to establish the relationship among the variables mentioned above. The outcome of the study reveals that political stability is an important predictor of environmental degradation in China. Moreover, political stability is helpful to lower CO2 emissions, while technological innovation and renewable energy consumption can reduce CO2 emissions, economic growth further deteriorates environmental quality by increasing its carbon emissions. Therefore, the present study recommends that policymakers in China should control political tension in the country to control CO2 emissions and, at the same time, promote technological innovation and renewable energy consumption.

CO2 behavior amidst the COVID-19 pandemic in the United Kingdom: The role of renewable and non-renewable energy development.

The spread of the COVID-19 pandemic since the end of 2019 has forced an unprecedented lockdown worldwide, and environmental quality was significantly affected by the pandemic and its induced lockdown. The objective of this study is to examine the role of renewable energy, non-renewable energy and COVID-19 case on CO2 emission in the context of United Kingdom. Several non-linear techniques such as Fourier ADL cointegration test, Non-Linear ARDL, Markov switching regression, and Breitung and Candelon (BC) causality test are employed to attain this objective. The result reveals that there is long run cointegration among the variables in this study. The results demonstrate that positive (negative) shift in renewable energy development decrease (increase) CO2 emissions while positive (negative) shocks in fossil fuel energy increase CO2 emissions. Moreover, negative (positive) variation in COVID case leads to a decrease (increase) in CO2 emissions. Moreover, an uni-directional causal impact was found to run from all the variables - renewable energy, fossil fuel, and COVID-19 case to CO2 emissions. Finally, several policy recommendations are provided.