Unleashing sustainability in uncertain times: Can we leverage economic complexity, uncertainty, and remittances to combat environmental degradation?

Rapid economic growth and human activities have seriously damaged the environment and hindered the achievement of Sustainable Development Goals (SDGs). Hence, this study aims to explore the impact of economic complexity, uncertainty, and remittance on environmental degradation in 134 countries from 2000 to 2022. In addition, it examines whether uncertainty moderates the relationship between remittance and environmental degradation. Two proxies (ecological footprint and CO2) were used to measure environmental degradation. The analysis was conducted using a cross-sectional dependency test, second-generation unit root test, and panel quantile regression. The results revealed that economic complexity significantly and positively impacted environmental degradation, while uncertainty and remittance significantly and negatively impacted environmental degradation. Furthermore, uncertainty weakened the negative relationship between remittance and environmental degradation. Accordingly, this paper discusses various recommendations and policy implications regarding economic complexity, uncertainty, remittance, and environmental degradation.

Coal consumption-environmental sustainability nexus in developed and developing major coal-consuming economies.

Coal is crucial for economic progress but equally baneful to the environment. Thus, the coal consumption-environmental sustainability nexus attracted the attention of both policymakers and scholars. This study evaluates the coal consumption-environment nexus in developed and developing countries over the period 2000-2020. We used panel data econometric techniques and the Augmented Anderson-Hsiao (AAH) two-step GMM estimator to assess and compare the impact of coal consumption on CO2. The findings revealed that the consumption of coal aggravates environmental pollution and hinders environmental sustainability. Thus, this study confirms the environment-destroying effect of coal consumption. However, the findings reveal that the negative consequence of coal consumption on the environment is more for the sample of developed countries than that of developing countries. This suggests that coal use harms the environment developed economies than the developing countries. Specifically, we found that the carbon emissions emanating from a one percent (1%) increase in coal consumption of the developed countries is about six-fold more than that of the developing countries. Therefore, this study suggests a gradual phase-out, rather than sudden phase-out, of coal consumption with greater emphasis on developed countries. The implementation of the coal phase-out policy and the removal of fossil fuel subsidies should start with the developed countries or be made more stringent in such countries than the developing economies. The developed countries should relinquish a greater proportion of their coal consumption than the developing countries.

The key to sustainability: In-depth investigation of environmental quality in G20 countries through the lens of renewable energy, economic complexity and geopolitical risk resilience.

The world is currently facing urgent climate and environmental issues, such as global warming, ecosystem collapse, and energy shortages. In this context, this study selected data from 2000 to 2021 and employed the Method of Moment Quantile Regression (MMQR) to thoroughly investigate the impact of renewable energy consumption, economic complexity, and geopolitical risks on the ecological footprint of the Group of Twenty (G20) countries. The results indicate that in countries with lower quantiles, renewable energy consumption significantly reduces the ecological footprint, whereas its effect is not prominent in countries with higher quantiles. Economic complexity has a negative impact on the ecological footprint, and this impact becomes stronger as the quantile of the ecological footprint rises. Additionally, economic complexity moderates the effect of renewable energy on the ecological footprint. Geopolitical risks facilitate the growth of the ecological footprint. Likewise, robustness tests such as DOLS, FMOLS, and quantile regression confirm these estimates in the same framework. This study has conducted a profound analysis of global environmental issues, offering innovative perspectives and recommendations for achieving goals related to sustainable energy utilization, mitigating climate change, and improving the ecological environment. The findings of this research will guide policymakers in G20 countries to adopt more effective environmental protection measures, thereby contributing to the construction of a sustainable future.

Role of natural gas and nuclear energy consumption in fostering environmental sustainability in India.

This paper investigates the role of nuclear energy in promoting ecological sustainability in India, focusing on three ecological indicators: ecological footprint (EF), CO2 emissions (CO2), and load capacity factor (LF). In addition to nuclear energy, the study considers the influence of gas consumption and other drivers of ecological sustainability using data spanning from 1970 to 2018. The analysis also takes into account the impact of the 2008 global financial crisis on the model, employing the autoregressive distributed lag (ARDL) and frequency domain causality approaches to assess the relationships. Unlike previous studies, this research evaluates both the Environmental Kuznets Curve (EKC) and load capacity curve (LCC) hypotheses. The ARDL results support the validity of both the EKC and LCC hypotheses in the Indian context. Furthermore, the findings reveal that nuclear energy and human capital contribute positively to ecological quality, while gas consumption and economic growth have a negative impact on ecological sustainability. The study also highlights the increasing effect of the 2008 global financial crisis on ecological sustainability. Additionally, the causality analysis demonstrates that nuclear energy, human capital, gas consumption, and economic growth can serve as predictors of long-term ecological sustainability in India. Based on these findings, the research presents policy recommendations that can guide efforts towards achieving SDGs 7 and 13.

An empirical assessment of the tripartite nexus between environmental pollution, economic growth, and agricultural production in Sub-Saharan African countries.

A lot of attention has been paid to environmental pollution worldwide, due to the increase in anthropogenic activities. Massive investment in non-renewable energy options raises questions regarding environmental sustainability and how to maximize food and non-food output while still preserving a healthy ecosystem. To this end, the present study explores the three-way nexus between economic growth, CO2 emission, and agriculture-value added will accounting for other control variables across a balanced panel of selected African economies from 1997 to 2020. Panel econometrics method of the generalized method of moments (two-step difference GMM) is used to obtain a robust result. From the present study, the environmental pollution model shows that economic growth significantly contributes to environmental pollution in Africa. Additionally, the food price index, capital, and FDI promote pollution, while agricultural production and labor decrease pollution. In the case of the economic growth model, the findings reveal that environmental pollution supports the growth-led pollution hypothesis. Also, the food price index and capital ameliorate economic growth, while foreign direct investments decrease economic growth. Finally, the agricultural production model indicates that economic growth increases agricultural production when the interaction term between GDPC and FDI is included in the model. In summary, the combination of explanatory variables, environmental pollution, capital, and foreign direct investment decreases agricultural production. On the contrary, the food price index and labor promote agricultural production in Africa. Furthermore, the study provides a lot of policies for authorities and stakeholders in Sub-Saharan African countries and other developing economies.

The Dynamic Nexus Between International Tourism and Environmental Degradation in Top Twenty Tourist Destinations: New Insights From Quantile-on-Quantile Approach.

Tourism is one of the important factors that can affect the environmental and economic situation of any economy. This study investigates the relationship between tourist arrivals and CO2 emission in the top 20 tourist destinations using data from quarterly observations from 1995 to 2018. A unique technique via quantile-on-quantile regression and Granger causality in quantiles was used. In particular, how the quantiles of tourist arrivals impact quantiles of CO2 emission was analyzed. The empirical results suggest a combination of both positive and negative effects of tourist arrivals and CO2 emission in most tourist destinations. Predominantly, at both high and low tails, in the USA, Spain, Hong Kong, and Austria, tourist arrival has a positive effect on CO2 emission, whereas in the case of Canada, France, Germany, Mexico, and Malaysia, the association was negative. On the other hand, China, Greece, Russia, Japan, Italy, South Korea, Thailand, and Turkey have both positive and negative effects of tourism on CO2 emissions at low and high tails. Tourism can be an important factor while formulating policy for environmental and climate aspects.

Globalization and renewable energy use: how are they contributing to upsurge the CO2 emissions? A global perspective.

The present study major aim was to examine the impact of globalization, economic growth, population growth, renewable energy usage and nuclear energy on CO2 emissions globally by taking the annual data varies from 1985 to 2020. Stationarity among study variables were tested via unit root testing, while nonlinear autoregressive distributed lag (NARDL) technique was used to demonstrate the linkages among variables with the estimation of long-run and short-run. Study results reveal that both in the short run and long run, negative globalization and economic growth shocks positively and negatively influence CO2 emissions, respectively. Besides, higher population growth is found to positively influence CO2 emissions while renewable energy consumption cannot influence the CO2 emission figures. Lastly, positive and negative shocks to alternative nuclear energy consumption are evidenced to negatively influence CO2 emissions both in the short run and long run. Hence, in line with these findings, several new policies and strategies are recommended for reducing carbon emissions globally.

Environmental degradation and sustainable development of economies: empirical evidence on economic performance.

The present paper aims to analyze the influence of environmental practices over the sustainable development of economies which create economic resilience for the economies classified according to different income levels. The authors aim to assess the impact of high environmental degradation (HED) on GDP growth volatility and GDP growth for economies over the long term and short term for the period of 1955-2020 in 124 countries. The findings of empirical analysis conclude that HED economies will have high growth in the long term than their counterparts. The economies of HED have a significant mean difference in volatility with their counterpart control group that implies HED economies have low volatility than the control group. Economies with HED have higher financial development relative to their control economies. The empirical analysis of robustness checks shows that economies with HED have low volatility in GDP and higher growth rates. HED economies enjoy high and sustainable financial development and high gross fixed capital formation, which signifies a high level of investment in their economy than their control counterpart.

Revealing the dynamic effects of fossil fuel energy, nuclear energy, renewable energy, and carbon emissions on Pakistan's economic growth.

The primary goal of this study was to examine the relationship between fossil fuel energy, electricity production from nuclear sources, renewable energy, CO2 emissions, and economic growth in Pakistan. Data ranging from 1975 to 2019 were utilized, and the stationarity of this data was verified through the unit root testing. The dynamic connections between variables were investigated by utilizing the linear autoregressive distributed lag technique. Long-run analysis results uncover that fossil fuel energy, renewable energy use, CO2 emissions, and GDP per capita have a productive relationship with economic progress in Pakistan, whereas electric power consumption, electricity produced from nuclear sources, and energy utilization have an adverse effect on economic growth. Furthermore, the consequences revealed that fossil fuel energy, renewable energy consumption, carbon dioxide emissions, and GDP per capita have a significant linkage to Pakistan's economic growth via short run, whereas we revealed that the variables electric power consumption, electricity produced from nuclear sources, and energy usage have an adversative linkage to Pakistan's economic growth. Feasible progressive policies are required from the Pakistani government to pay more attention for tackling the energy and power sectors' issues in terms of fulfilling the country's energy requirements.

Environmental pollution and agricultural productivity in Pakistan: new insights from ARDL and wavelet coherence approaches.

The most serious challenge to the global facade is figuring out how to mitigate pollution levels without compromising agricultural productivity. The spillover effect of environmental change is predicted to be very high, although it will differ by region and crop. Considering this view, this study tries to address this issue by adopting comprehensive methodologies to assess the influence of carbon dioxide (CO2) emissions, agricultural labor, land, feeds, and fertilizers on agricultural productivity in Pakistan from 1961 to 2018. The autoregressive distributive lag (ARDL) and wavelet transform coherence (WTC) approaches are applied to estimate the long-run and short-run elasticity estimates. The empirical findings discover that CO2 emissions, agricultural land, labor, feed, and fertilizers exert high pressure on agricultural productivity which is backed up by the WTC findings. Furthermore, the gradual shift causality test results reveal the presence of a unidirectional causality relationship between all regressors and agriculture productivity, demonstrating that all the factors significantly influence agriculture productivity. Moreover, these findings are robust to different robustness tests that we perform to test the reliability/accuracy of our core results. From policy perspectives, regulations must be developed to explore a practicable expansion strategy that includes the use of efficient fertilizers and feed at optimal levels, as well as environmental protection through public-private investment in the agricultural sector.

Assessing the long- and short-run asymmetrical effects of climate change on rice production: empirical evidence from India.

In recent years, environmental change has arisen as a ubiquitous problem and gained environmentalist's attention across the globe due to its long-term harmful effects on agricultural production, food supply, water supply, and livelihoods of rural households. The present study aims to explore the asymmetrical dynamic relationship between climate change and rice production with other explanatory variables. Based on the time series data of India, covering the period 1991-2018, the current study applied the nonlinear autoregressive distributed lag (NARDL) model and Granger causality approach. The results of the NARDL reveal that mean temperature negatively affects rice production in the long run while positively affecting it in the short run. Furthermore, positive shocks in rainfall and carbon emission have negative and significant impacts on rice production in the long and short run. In comparison, negative rainfall shocks significantly affect rice production in the long and short run. Wald test confirms the asymmetrical relationship between climate change and rice production. The Granger causality test shows feedback effect among mean temperature, decreasing rainfall, increasing carbon emission, and rice production. While no causal relationship between increasing temperature and decreasing carbon emission. Based on the empirical investigations, some critical policy implications emerged. Toward sustainable rice production in India, there is a need to improve irrigation infrastructure through increasing public investment and to develop climate-resilient seeds varieties to cope with climate change. Along with, at the district level government should provide proper training to farmers regarding the usage of pesticides, the proper amount of fertilizers, and irrigation systems.

Modeling the impact of climatic and non-climatic factors on cereal production: evidence from Indian agricultural sector.

The underpinned study examines the effects of climatic and non-climatic factors on Indian agriculture, cereal production, and yield using the country-level time series data of 1965-2015. With the autoregressive distributed lag (ARDL) bounds testing approach, the long-term equilibrium association among the variables has been explored. The results reveal that climatic factors like CO2 emissions and temperature adversely affect agricultural output, while rainfall positively affects it. Likewise, non-climatic factors, including energy used, financial development, and labor force, affect agricultural production positively in the long run. The estimated long-run results further demonstrate that CO2 emissions and rainfall positively affect both cereal production and yield, while temperature adversely affects them. The results exhibit that the cereal cropped area, energy used, financial development, and labor force significantly and positively impact the long-run cereal production and yield. Finally, pairwise Granger causality test confirmed that both climatic and non-climatic factors are significantly influencing agriculture and cereal production in India. Based on these results, policymakers and governmental institutions should formulate coherent adaptation measures and mitigation policies to tackle the adverse climate change effects on agriculture and its production of cereals.

Investigating the asymmetry effects of crude oil price on renewable energy consumption in the United States.

The reduction in oil prices might make crude oil a cheaper alternative to renewable energy (RE). Given this, the present paper examines the effect of fluctuation of oil prices on the use of RE in the United States (US) during the period 1970 to 2018. We constructed two nonlinear autoregressive distributed lag (NARDL) models to examine the effect of the positive and negative oil price shocks on the use of RE in the US. The RE consumption is taken as the dependent variable and the gross domestic product (GDP), Brent crude prices, population density, trade openness, and price index as independent variables. The result revealed that the rise in crude oil price, GDP, and population density will increase RE use in the short run and in the long run as well. Moreover, the study finds that any decrease in oil prices will decrease RE use in the short run and its effect will eventually diminish in the long run. On the policy front, it is suggested that US should raise its energy security by reducing its dependency on imported crude oil and increase the role of RE through the imposition of taxes on oil and increase the base of production and consumption through a series of measures.

Examining the carbon emissions and climate impacts on main agricultural crops production and land use: updated evidence from Pakistan.

One of the major challenges to the survival of life on earth is the increasingly evolving climate change. The key source of environmental pollution is global warming. With the combustion of fossil fuels, greenhouse gas (GHG), which is generated in the external environment, is increased and air pollutant as well. The present analysis key intention was to examine the CO2 emission and climatic effects on major agricultural crop production and land use in Pakistan. The study used time span annual data varies from 1970 to 2019, and data stationarity was rectify by utilizing the unit root tests. A generalized method of moments with two-stage least squares technique was applied to expose the variables' association with CO2 emission. The study consequences uncover that the wheat, maize, sugarcane, cotton, bajra, gram, sesamum crops, and land use have constructive association with CO2 emission having positive coefficients with probability values (0.3762), (0.0435), (0.2287), (0.2303), (0.2272), (0.0192), (0.4535), and (0.0017) correspondingly, while rainfall, temperature, rice, jowar, and barley uncovered an adversative linkage to CO2 emission in Pakistan. As Pakistan is an emerging country, potential constructive measures must be introduced in directive to reduce CO2 emissions to improve the agricultural productivity.

Sustainable development and pollution: the effects of CO2 emission on population growth, food production, economic development, and energy consumption in Pakistan.

Population growth has been a leading driver of global CO2 emissions over the last several decades. CO2 emission and greenhouse gas emissions are a key issue in the world that affects food production and also causes the climate change. The core purpose of this study was to inspect the influence of carbon dioxide emission to population growth, food production, economic growth, livestock and energy utilization in Pakistan. The STIRPAT (Stochastic Impact by Regression on Population, Affluence and Technology) model with the extension of an ARDL (Autoregressive Distributed Lag) method was utilized to demonstrate the linkage amid variables. Outcomes during short-run investigation reveal that variables population growth, economic growth, rural population growth, livestock production uncovered a productive association with CO2 emission. Furthermore, via long-run population growth, economic growth, rural population growth, livestock production and energy utilization have positive interaction with CO2 emission, while the variables food production and urban population growth demonstrated an adverse influence to CO2 emission during long- and short-run interaction. Similarly, the error correction model exposed that population growth, economic progress, livestock and energy utilization have constructive interaction to CO2 emission, while the variables food production, urban and rural population growth exposed an adverse impact to CO2 emission. On the basis of this analysis, we will address the strategic consequences.

Tourism-induced pollution emission amidst energy mix: evidence from Nigeria.

In recent years, there is concerted efforts to boost the tourism industry in Nigeria, and regulatory bodies were created for the tourism industry. This study is contributing to the ongoing debate on the tourism-energy-environment literature. Thus, we explore the linkage between tourism development, energy consumption, carbon dioxide (CO2) emission, and renewable energy consumption in Nigeria for the period of 1995-2016. The present study leverages on Bounds testing to cointegration in a carbon-income function environment while incorporating renewable energy consumption to the econometric framework. Subsequently, autoregressive distributed lag methodology alongside dynamic ordinary least square (DOLS) is utilized for robustness of estimations. Empirical results give credence to the energy-induced emission hypothesis in Nigeria. This outcome is suggestive to policymakers as fossil fuel-based energy consumption deplete the quality of the environment. Similarly, the study also affirms the environmental Kuznets curve (EKC) phenomenon. The emphasis on Nigerian growth trajectory (real income level) relative to her quality of environment via the channel of economic development and energy consumption from fossil-fuel source is indicated. On the other hand, renewable energy consumption in Nigeria shows significant ability to reduce emission level in Nigeria. This result is insightful, which implies that environmental quality is not threatened with an increase in tourist arrivals, hence tourism does not degrade the environment but is sustainable to the environment. Interesting and laudable for stakeholders' international tourism arrival did not deplete the quality of the environment. The plausible explanation is attributed to the scale of tourism in Nigeria which at the moment is still low or much more there is caution/awareness on ecotourism for sustainable environment.

Mirroring risk to investment within the EKC hypothesis in the United States.

In reality, economic expansion cannot be paced-up enough. This account for a potential trade-off between income and environmental degradation that is expectedly feasible at a maximum level of income. On this note, the current study looked at the validity of income-environmental degradation (Environmental Kuznets Curve, EKC) hypothesis especially amidst risk to investment in the United States over the period 1984-2017. Considering that the burning of fossil fuels constitutes the largest source of Greenhouse gas (GHG) in the United States, this study employed energy carbon emissions as a proxy for environmental quality and as a dependent variable. While the study employed renewable energy production as additional explanatory variable, it implemented the Autoregressive Distributed Lag (ARDL) technique in addition to a set of cointegration techniques. Importantly, the study found that the EKC hypothesis is valid for the case of the United States but not without a non-significant trade-off of risk to investment. Additionally, renewable energy production exhibits a statistically significant and desirable impact on environmental quality in both the short and long-run. In general, the study posited that while environmental sustainability is achievable at maximum level of income, it is likely attainable at the detriment of risk to investment. Hence, this observation should trigger a potential policy mechanism that minimizes risk to investment in light of the attainment of the country's sustainable development goals (SDGs).

Towards long-term sustainable environment: does agriculture and renewable energy consumption matter?

This work analyzed the long-run (LR) and short-run (SR) effects of renewable and non-renewable energy (RE and NRE) usage, economic development (ED), agricultural value-added (AVA), and forestry area (FA) on the environmental quality (EQ) in China spanning from 1990 to 2015. The autoregressive distributed lags (ARDL) bounds testing method and the Johansen cointegration approach are applied to produce empirical estimates. The empirical results of the ARDL and the fully modified ordinary least square (FMOLS) estimators established that renewable energy usage and forest area reduce CO2 emissions and improve the environmental quality, while non-renewable energy consumption, economic development, and agricultural output increase the level of CO2 emissions in China. The robustness of outcomes is checked through the Granger causality test, impulse response function (IRF), and variance decomposition method (VDM) suggesting that fossil fuel usage in the agriculture production process is mainly accountable for China's CO2 emissions. These findings have inherent policy implications for the central and local Chinese government, which are exhibited in the "Conclusions" section.

Examining the direct and indirect effects of financial development on CO2 emissions for 88 developing countries.

The previous literature presents conflicting outcomes on the relationship between financial development and CO2 emissions. This study fixes this puzzle by testing both the direct and indirect effects of financial development on environmental pollution using Environmental Kuznets Curve (EKC) framework. Our empirical investigation relies upon difference and system generalized method of moments for a large sample of 88 developing countries during 2000-2014 period. The estimated outcomes, based on five different indicators of financial development, support the pollution inhibiting role of financial development for the selected countries. We also validate the existence of EKC hypothesis for the panel of economies. More importantly, the results of the indirect channels show that financial development also reduces the adverse effects of income, trade openness and FDI on the pollution emissions. Further, the validity of pollution heaven hypothesis (PHH), tested through trade openness and FDI variables, is also contingent upon the existence of weak financial structure. When financial development traverses certain limits, PHH ceases to exist for both these variables. Lastly, population size augments pollution emissions while human capital reduces the later. Based on these results, we propose some very important policy implications for the sample economies.