Search

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.

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 (CO

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.

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.

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.

Carbon dioxide emission and GHGs are associated with fossil fuels which have adverse effects on the environment. The key intention of this paper was to determine the asymmetric effect of CO2 emission on expenditures, trade, FDI, and renewable energy consumption in Pakistan. An asymmetrical technique (nonlinear autoregressive distributed lag) was employed to validate the constructive and adverse relation among variables. Furthermore, the Granger causality test was also used to verify the unidirectional association amid variables. Study outcomes revealed that the adverse shocks of renewable energy consumption exposed expressively to upsurge CO2 emission in the short-run dynamics. Conversely, constructive shocks of renewable energy consumption display an adversative association with CO2 emission. Furthermore, the decreasing trend in foreign direct investment tends to impede the detrimental effects of CO2 emission. Additionally, the variable expenditures also create the non-eco-friendly impacts and manifest the positive linkage through CO2 emission. Trade possesses statistically insignificant linkage with environmental degradation. The results also disclose that positive as well as negative variations in the foreign direct investment expose to degrade the environmental eminence. Long-run results suggest the direct association between downward trend in renewable energy consumption and CO2 emission signifying that the pollution level decreases, and the upward trend in renewable energy consumption, however, demonstrates insignificantly positive effects. The results also disclose that positive as well as negative variations in the FDI lead to degrade the CO2 emission. Moreover, it is found that the expenditures soar the issue of pollution again in the long run. Finally, the consequence of trade on CO2 emission is adverse, as the outcome suggests. In order to improve the environmental policies for sustainable growth, the study provides direction toward a sustainable environment by reducing carbon dioxide emission.

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.

The present study aims to investigate the effects of information and communication technology, foreign direct investment, trade and renewable energy use with GDP growth in Pakistan using time series data ranging from 1985 to 2017. Stationarity of data was verified by using unit root tests including ADF and P-P, while an autoregressive distributed lag (ARDL) model was used to check the dynamic association amid prescribed variables with long- and short-run analysis. Furthermore, cointegrating regression analysis with FMOLS, DOLS and CCR was applied to validate the variables causality. The outcomes during long-run analysis show that ICTE, trade and renewable energy have constructive linkage to GDP growth, while foreign direct investment has adverse influence to GDP growth in Pakistan. Similarly, the outcomes from cointegrating regression technique exposed that all variables including foreign direct investment, ICTE and trade have positive and constructive association with GDP growth except renewable energy that causes the adverse association to GDP growth in Pakistan. On the basis of outcomes, we will discuss the policy recommendations.

Carbon dioxide emissions have been the primary source of extreme environmental pollution and have detrimental consequences on human life, irrespective of an economy being developed or underdeveloped. For the developing economies, in particular, it is imperative to reduce such emissions in order to sustain the growth of the respective economies. However, for designing appropriate emission reduction policies, it is appropriate to identify the sectors which contribute the most to carbon dioxide emissions and dampen the growth of overall economy. Against this background, the key intention of this study was to examine the influence of carbon dioxide emissions generated from various sources on the economic progress in Pakistan between 1971 and 2017. This study is important for Pakistan to sustain its economic progress and enable the nation to comply with commitments of the Paris Agreement and Sustainable Development Goals. The econometric analysis conducted in this study considers a nonlinear autoregressive distributed lag model which is applied to ascertain the short- and long-run economic growth impacts associated with positive and negative shocks to CO2 emissions generated from various sources. The choice of this model is driven by its capacity to perform an asymmetric analysis which is relevant for suitable policy-making purposes. The overall results, in a nutshell, reveal that carbon dioxide emissions from Pakistan’s transportation sector influence the country’s economic progress. Positive shocks to such carbon dioxide emissions are originate to reduce economic progress in the long run while negative shocks are evidenced to boost economic growth both in the short and long run. In contrast, carbon dioxide emissions from other major sectors are found to be ineffective in influencing Pakistan's economic growth both in the short and long run. Hence, keeping into consideration the prospects of attaining sustainable economic growth, the Pakistan government must prioritize the implementation of CO2 emissions-inhibiting policies within the transportation sector. Simultaneously, the traditional fossil fuel dependency within this sector should also be phased out.

The dispute between economic growth and greenhouse gas emissions is one of the major challenges of the twenty-first century. The central issue of the emerging economies revolves around the decoupling of economic growth and the rising carbon dioxide (CO2) emissions. This study examines the decoupling the CO2 emissions from the economic growth through the employment of the Tapio decoupling index and decomposition of CO2 emissions into its pre-determined factors through the Log Mean Divisia Index (LMDI) decomposition technique for Pakistan, India, and China (PIC) for a time span of 1990–2014. The findings of the Tapio elasticity analysis depict that in a few years, environmental impact has been seen to be decoupled from the economic growth in the respective PIC countries. However, relatively Pakistan experienced expensive negative decoupling; India mostly experienced weak decoupling and expensive coupling, while China exhibited weak decoupling in multiple years. In addition, the analysis of Tapio decoupling elasticity showed that energy intensity is the key factor supporting the decoupling in PIC countries, while population, affluence (GDP per capita) and energy structure have weakened the progress of decoupling. Furthermore, the analysis of the LMDI decomposition suggested that population, energy structure and affluence in PIC countries increase the CO2 emissions, while energy intensity reduces CO2 emissions, while mixed effects are reflected by carbon intensity.

Globally, the use of modern technologies is increasing along with carbon emission due to the consumption of fossil fuels to operate modern technologies. Therefore, in this study, we aimed to investigate the relationship between carbon emission, renewable energy consumption, forestry, and agricultural value added per capita from 1998 to 2018. The auto-regressive distribution lag model was estimated for long-run and short-run correlation analysis. The results of this study revealed that carbon emission decreases owed increases in forest areas in the long and well as short-run nexus. Furthermore, in the short run, carbon emission decreases due to an increase in renewable energy consumption. In addition, the carbon emission was run in an upward direction parallel to agricultural financial development. Furthermore, this study confirmed that the unidirectional causality between variables by estimating the non-Granger causality test. Therefore, this study suggests that to combat carbon emissions with carbon emission, it is necessary to switch from nonrenewable energy to renewable energies and organic fertilizer consumption along with afforestation to make the climate free from carbon.

The accelerated urbanization in China was already coupled with a steadily increasing demand for energy usage. The present study major aim was to determine the asymmetric influence of urbanization, energy utilization, fossil fuel energy and CO2 emission on economic progress in China by using an annual time series data varies from 1975 to 2017. Stationarity amid variables was verified by applying the unit root tests, while non-linear autoregressive distributed lag (NARDL) bounds testing model was used to examine the asymmetric impacts on variables with short- and long-run dynamics. Outcomes revealed that via short-run estimates, the negative shocks of energy usage cause significantly to increase the economic efficiency, but positive shocks of energy utilization display the adverse linkage with the economic progress. Similarly, the negative shocks of GDP per capita growth demonstrate a substantial upsurge in the economic progress, and the positive shocks establish the adverse influence towards economic growth. Further, the outcomes of short-run dynamics also exposed the negative shocks of urbanization significantly affected the economic growth, but positive shocks exposed the adversative influence on economic growth. The outcomes display that fossil fuel energy consumption showed a constructive impact to economic progress, and additionally, the variable CO2 emission also uncovered a positive shocks having significant impact on economic progress. Furthermore, the outcomes of long-run analysis express that energy utilization has negative and positive shocks that expose the adverse influence on economic progress of China. GDP per capita growth exposed the constructive influence on the economic growth in both shocks. The negative and positive shocks of urbanization demonstrate a noteworthy influence on economic growth. The variable fossil fuel energy consumption also exposed an optimistic influence on economic progress, and finally the influence of CO2 emission on economic growth is insignificant as the results exposed. The reducing carbon alteration target aims to be reached for China, and in the next several decades, it will encourage the green energy options in order to decrease carbon dioxide emission to avoid environmental pollution by raising its energy intensity.

Maintaining a balance between environmental quality and economic growth is now one of the common goals of fiscal and monetary policies in developed and developing economies. This study examines the asymmetric impacts of fiscal and monetary policy instruments on environmental pollution in Pakistan over the period 1985–2019 by employing the asymmetric or nonlinear autoregressive distributed lag (NARDL) framework. The outcomes indicate that in Pakistan, a positive and negative shock in fiscal policy instruments has a significant increasing influence on carbon emissions in the short run, while a positive and negative shock in fiscal policy instruments has a significant decreasing impact on environmental pollution in long run. However, negative and positive shock in monetary policy instruments enhances carbon emissions in short-run, whereas positive shock in monetary policy instruments decreases carbon emissions in the long run. Therefore, the policymakers may consider the usage of fiscal and monetary policy instruments to maintain economic growth along with lowering the environmental pollution.

The present study seeks to investigate the sector-level energy consumption of oil and natural gas and to explore the linkage between economic growth, households, agriculture, industry, power, fertilizers, and commercial sector in Pakistan for the period of 1980–2016. The energy sector of Pakistan is facing severe crisis from the last few years due to inadequate production and supply. Long-lasting deficits of natural gas and oil, the two supreme types of fuel in Pakistan, had detrimental consequences for the growth as well as for the economic development. An autoregressive distributed lag (ARDL) method and Granger causality test under vector error correction model (VECM) were employed to check the association among the variables. Furthermore, the innovative accounting method was used to investigate the responsiveness of each variable to another within the study framework. Empirical results show long-run association among the variables, as oil consumption in the agriculture and power sector show a positive effect on Pakistan’s economic growth. Similarly, energy consumption from natural gas in the households and fertilizers as well as in the industry sector has had a constructive association with economic growth. In contrast, energy consumption from oil in the households and industry sectors has adverse association with economic growth, while natural gas consumption in the commercial sector has negative linkage with economic growth. Possible steps should be taken by the Government of Pakistan to enhance the production of oil and natural gas from other alternatives to meet the requirements of these sectors.

This research has examined the dynamic linkages among climate change factors, such as CO2 emissions, temperature, rainfall, and cereal yield in Turkey from 1968 to 2014. At first step, we tested stationary properties of the climatic factors and crop yield by using both traditional and breakpoint unit root tests. After the confirmation of given properties, we used the autoregressive distributed lag (ARDL) model to capture the dynamic relationship among the variables in the given span of time. The empirical results show that there is a long-run equilibrium relationship that exists between climate change factors and cereal yield. CO2 emissions and average temperature have a diverse effect on the cereal yield, whereas average rainfall has a positive effect on the cereal yield in both the long run and short run. To check the causality, we use the Granger causality test that reveals a significant effect of climate change variables on the cereal yield. The unidirectional causal link is significant among temperature and rainfall factors. The results show that the cereal yield is affected by more climate factors like rain fall and temperature due to CO2 emissions as compared to land and labor use. Based on the findings of the study, few suggestions have been made to address the climate change factors. Devise agriculture-specific adaptation policy for the farmers to build their capacity and resilience to tackle climate changes, for example, farm practices. Agriculture research and development should work on cereal crop varieties that can tolerate the high temperature and precipitation. These policies could help the agriculture sector to sustain production and allocation efficiency in the long run.

This article revisits the nexus between financial development and environmental degradation by incorporating economic growth, electricity consumption and economic globalization in the CO2 emissions function for the period 1975QI–2014QIV in the United Arab Emirates. We apply structural break and cointegration tests to examine unit root and cointegration between the variables. Further, the article also uses the Toda-Yamamoto causality test to investigate the causal relationship between the variables and tests the linkages of the robustness of causality by following the innovative accounting approach. Our empirical analysis shows cointegration between the series. Financial development increases CO2 emissions. Economic growth is positively linked with environmental degradation. Electricity consumption improves environmental quality. Economic globalization affects CO2 emissions negatively. The relationship between financial development and CO2 emissions is U-shaped and inverted N-shaped. Further, financial development leads to environmental degradation, and environmental degradation in turn leads to financial development in the Granger sense. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

Sustainable development inculcates the process of preserving the environment for future generations while maintaining existing human needs. This study attempts to empirically investigate the relationship between CO2 emissions, GDP, energy consumption, and imports and exports using yearly data between 1980 and 2014 for the panel of eight developing countries (i.e., Bangladesh, Egypt, Iran, Indonesia, Malaysia, Nigeria, Pakistan, and Turkey). All the tests for cointegration establish the long-run association among the variables and confirm the environmental Kuznets curve (EKC) hypothesis for the panel of eight countries. GDP and energy consumption remained significant factors for emission intensity both in the long and short run. However, exports found to be positive factor for emissions in the long run only and imports spur emissions in the short run. The country-specific results validate EKC hypothesis for Bangladesh, Iran, Nigeria, Pakistan, and Turkey. The findings are policy oriented and suggest that the countries’ economic growth along with energy consumption and exports are highly emission intensive which require necessary adjustments at sustainable development policy front.

The objective of this research is to examine the effects of stock market on air pollution in Malaysia during the period 1980–2017. To realize this aim, a nonlinear autoregressive distributed lag (ARDL) model is constructed. The short results in general revealed that the increase in stock markets will increase CO2 emissions and its significance increases in the long run. Moreover, the decline in stock market will reduce Malaysia’s CO2 emissions but only in the long run. From the outcomes obtained, a number of policy recommendations were provided for the investigated country.

WOS: 000445273500091, PubMed: 30141168, This paper explores the direct impact of new technology on the energy intensity in China. The autoregressive distributed lag (ARDL) bounds test approach to cointegration is utilised over the extended period of 1985-2013. The variables found cointegrated and confirm the long-run association among all the underlying vectors. Furthermore, the results of long- and short-run analysis reveal that new technology spurs energy intensity in China. A 1% increase in technological innovation boosts energy intensity by 0.4% and 0.03% in the long and short run, respectively. The findings suggest that the establishment of smart grids and solar energy parks followed by the reforms in energy sector is yet to achieve plausible efficiency in China. The existing investment and innovation policy reforms are insufficient to assist the energy sector to cope up with the country's exceptional economic growth trend. Unlike other studies, this paper accommodates structural break in the series. During sensitivity analysis, the model is found stable. Hence, the findings possess important policy implications for China and open up new discussion in the field.

WOS: 000399401700088, PubMed: 28293824, The objective of this study is to explore the influence of the real income (GDP), renewable energy consumption and non-renewable energy consumption on carbon dioxide (CO2) emissions for the United States of America (USA) in the environmental Kuznets curve (EKC) model for the period 1980-2014. The Zivot-Andrews unit root test with a structural break and the Clemente-Montanes-Reyes unit root test with a structural break report that the analyzed variables become stationary at first-differences. The Gregory-Hansen cointegration test with a structural break and the bounds testing for cointegration in the presence of a structural break show CO2 emissions, the real income, the quadratic real income, renewable and non-renewable energy consumption are cointegrated. The long-run estimates obtained from the ARDL model indicate that increases in renewable energy consumption mitigate environmental degradation whereas increases in non-renewable energy consumption contribute to CO2 emissions. In addition, the EKC hypothesis is not valid for the USA. Since we use time-series econometric approaches that account for structural break in the data, findings of this study are robust, reliable and accurate. The US government is advised to put more weights on renewable sources in energy mix, to support and encourage the use and adoption of renewable energy and clean technologies, and to increase the public awareness of renewable energy for lower levels of emissions.

WOS: 000382674800089, PubMed: 27421853, This paper attempts to investigate the emissions embodied in Australia's economic growth and disaggregate primary energy sources used for electricity production. Using time series data over the period of 1990-2012, the ARDL bounds test approach to cointegration technique is applied to test the long-run association among the underlying variables. The regression results validate the long-run equilibrium relationship among all vectors and confirm that CO2 emissions, economic growth, and disaggregate primary energy consumption impact each other in the long-run path. Afterwards, the long- and short-run analyses are conducted using error correction model. The results show that economic growth, coal, oil, gas, and hydro energy sources have positive and statistically significant impact on CO2 emissions both in long and short run, with an exception of renewables which has negative impact only in the long run. The results conclude that Australia faces wide gap between emission abatement policies and targets. The country still relies on emission intensive fossil fuels (i.e., coal and oil) to meet the indigenous electricity demand.

WOS: 000384555200008, PubMed: 27335019, In terms of today, one may argue, throughout observations from energy literature papers, that (i) one of the main contributors of the global warming is carbon dioxide emissions, (ii) the fossil fuel energy usage greatly contributes to the carbon dioxide emissions, and (iii) the simulations from energy models attract the attention of policy makers to renewable energy as alternative energy source to mitigate the carbon dioxide emissions. Although there appears to be intensive renewable energy works in the related literature regarding renewables' efficiency/impact on environmental quality, a researcher might still need to follow further studies to review the significance of renewables in the environment since (i) the existing seminal papers employ time series models and/or panel data models or some other statistical observation to detect the role of renewables in the environment and (ii) existing papers consider mostly aggregated renewable energy source rather than examining the major component(s) of aggregated renewables. This paper attempted to examine clearly the impact of biomass on carbon dioxide emissions in detail through time series and frequency analyses. Hence, the paper follows wavelet coherence analyses. The data covers the US monthly observations ranging from 1984:1 to 2015 for the variables of total energy carbon dioxide emissions, biomass energy consumption, coal consumption, petroleum consumption, and natural gas consumption. The paper thus, throughout wavelet coherence and wavelet partial coherence analyses, observes frequency properties as well as time series properties of relevant variables to reveal the possible significant influence of biomass usage on the emissions in the USA in both the short-term and the long-term cycles. The paper also reveals, finally, that the biomass consumption mitigates CO2 emissions in the long run cycles after the year 2005 in the USA.

WOS: 000368640300016, This study investigates the environmental Kuznets curve (EKC) hypothesis in Kenya using the time period of 1980-2012. To achieve the objective of this study, the ARDL approach was utilized. To prevent any estimation errors and unreliability in the model, the Narayan and Narayan (Energy Policy 38:661-666, 2010) approach was used to control the multicollinearity problems in the regression. The outcome of this research revealed that fossil fuel energy consumption, GDP, urbanization, and trade openness increase air pollution mutually in the long run and short run. However, renewable energy consumption mitigates air pollution in the long run and the short run. Moreover, financial development also reduces air pollution, but only in the long run. Based on the results, the EKC hypothesis does exist in Kenya. From the findings of this research, few policy recommendations were provided to help Kenya for reducing its air pollution levels.

2nd International Conference on Water, Energy, and Environment (ICWEE) -- SEP 21-24, 2013 -- Kusadasi, TURKEY, WOS: 000350331300067, PubMed: 25277709, The present study is aimed to explore the relationship between coal consumption, industrial production, and CO2 emissions in China and India for the period of 1971-2011. The structural break unit root test and cointegrating approach have been applied. The direction of causal relationship between the variables is investigated by applying the VECM Granger causality test. Our results validate the presence of cointegration among the series in both countries. Our results also validate the existence of inverted U-shaped curve between industrial production and CO2 emissions for India, but for China, it is a U-shaped relationship. Coal consumption adds in CO2 emissions. The causality analysis reveals that industrial production and coal consumption Granger cause CO2 emissions in India. In the case of China, the feedback effect exists between coal consumption and CO2 emissions. Due to the importance of coal in China and India, any reduction in coal consumption will negatively affect their industrial value added as well as economic growth., Izmir Katip Celebi Univ, Amer Univ Sharjah, United Arab Emirates Univ