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Renewable Energy, Output, Carbon Dioxide Emissions, and Oil Prices: Evidence from South America
Abstract
This study utilizes panel cointegration techniques to estimate the long-run relationship as well as the causal dynamics between renewable energy consumption per capita, real gross domestic product (GDP) per capita, carbon dioxide emissions per capita, and real oil prices for a panel of 11 South American countries over the period 1980 to 2010. Specifically, we find the long-run elasticity estimates are positive and statistically significant with respect to real GDP per capita, carbon emissions per capita, and real oil prices. The results of the panel error correction model reveal a feedback relationship among the variables in question, indicative of the importance of renewable energy consumption in both the growth of output and the containment of carbon dioxide emissions.
... While a considerable body of literature explores the relationship between oil price and renewable energy consumption, the impact of oil price on REI has received less attention (Apergis and Payne, 2015;Dominioni et al., 2019;Rentschler, 2013;Sadorsky, 2009a;Salim and Rafiq, 2012). A majority of previous studies focus on the symmetric effects of oil price, assuming linear relationships between variables. ...
... In the context of our study regarding the impact of oil price on REI, exploring the asymmetric effects of oil price is crucial for a comprehensive understanding of the Table 1 Relevant literature on oil price and renewable energy investment. Author(s) Country/Area Period Method Results Apergis and Payne (2015) 11 South American countries ...
... The bulk of the research on oil price and renewable energy focuses on oil price's effects on renewable energy consumption (Apergis and Payne, 2015;Dominioni et al., 2019;Rentschler, 2013;Sadorsky, 2009aSadorsky, , 2009bSalim and Rafiq, 2012). These studies demonstrate significant heterogeneity between countries in the transmission effects of oil price on renewable en ergy consumption, indicating potential asymmetries (Dominioni et al., 2019;Cao et al., 2020;Ipcc and Report, 1969). ...
This study investigates the symmetric and asymmetric relationships between oil price and renewable energy investment (REI) in six African countries (Algeria, Angola, Egypt, Ethiopia, Nigeria, and South Africa), examining the differences between net oil-importing and net oil-exporting countries in Africa. The study employs autoregressive distributed lag bounds testing and the non-linear autoregressive distributed lag approaches to analyse the data. The results reveal symmetric and asymmetric relationships between oil prices and REI across the countries examined. Algeria, Egypt, and Nigeria exhibit symmetric relationships, whereas Angola, Ethiopia and South Africa demonstrate asymmetric relationships. Oil prices have statistically significant effects on REI in all countries, albeit with varying levels of magnitude. In symmetric relationships, oil price influences REI in the long run for Egypt and Nigeria, while Algeria shows significant effects in both the short-and long-term. In asymmetric relationships, a positive change in oil price has a significant negative impact on REI in the long run for Angola, Ethiopia, and South Africa, while a negative change in oil price positively affects REI. Notably, Ethiopia does not exhibit statistical significance regarding negative oil price change. Overall, the study provides valuable insights into the complex relationship between oil prices and REI in Africa, emphasising the need for strategic policies to promote renewable energy adoption and reduce dependence on fossil fuels.
... Evidence shows that renewable energy is just a compliment and not a perfect substitute for crude oil, at least in the short run. Apergis and Payne (2015) used a panel co-integration and error correction model to investigate factors influencing renewable energy consumption. The study revealed that in the short term, an increase in real oil prices raises the consumption of renewable energy per capita in response to a substitution of fossil fuel prices, with a retroactive effect of the increase in renewable energy consumption per capita on the fall in real oil prices. ...
... Considering the coefficient magnitudes, it is apparent that long-run elasticity has revealed significance compared with the short-run assessment. Our study findings suggest that oil price changes positively support renewable energy inclusion, which is supported by the existing literature (see, for instance, Omri, Daly (Omri et al., 2015), Apergis and Payne (2015), Sadorsky (2009), Kyritsis and Serletis (2019), and Managi and Okimoto (2013)). However, our findings are opposite to those found in the existing literature offered by Mukhtarov, Mikayilov (Mukhtarov et al., (2020). ...
... Korea. Our study findings suggest that oil price changes positively support renewable energy inclusion, which is supported by the existing literature; see, for instance, Omri, Daly (Omri et al., 2015); Apergis and Payne (2015), Sadorsky (2009), Kyritsis and Serletis (2019), Managi and Okimoto (2013). ...
This study aimed to gauge the impact of economic policy uncertainty, oil price, and technological innovation on renewable energy consumption in the top five oil-importing nations for the period 1990–2021. The study employed a linear and nonlinear framework in exploring the association and variable elasticities on renewable energy consumption. According to linear assessment, the study documented positive effects from technological innovation and oil price volatility, whereas economic policy uncertainty adversely caused renewable energy integration, especially in the long run. The study disclosed long-run and short-run asymmetric connections between TI, EPU, and REC for asymmetric assessment. For directional causality, the study documented feedback hypothesis that explain the nexus between oil price and renewable energy consumption in China [OIL←→REC]; economic policy uncertainty and renewable energy consumption [EPU←→REC] in China, India, Japan, and South Korea; and technological innovation and renewable energy consumption [TI←→REC] in South Korea. On a policy note, the study established that efficient energy transition from fossil fuel to renewable energy demands economic stability and, therefore, stability must be ensured. Furthermore, oil prices should be considered while formulating energy policies.
... In the past few decades, there has been a growing body of literature analyzing factors affecting the development of clean energy [2][3][4]. Among others, the impact of fossil fuel prices on renewable energy has been examined by many scholars, such as Murshed and Tanha [5], Zhao et al. [6], Brini et al. [7], and Apergis and Payne [8][9][10]. Two main conclusions may be derived when reviewing the literature on this subject. ...
... The second statement is the inconclusive and mixed results reached by prior studies. For instance, substantial research highlighted the favorable effect of oil prices on renewable energy [6][7][8][9][10]. Far fewer studies conclude that the linkage between oil prices and renewable energy is negative [11]. ...
... More specifically, findings reveal that renewable energy, economic growth, CO2 emissions, and oil prices all have a positive and significant relationship. In other work, Apergis and Payne [10] investigated the same relationship in 11 South American countries between 1980 and 2010. The authors conclude that the long-run association between carbon dioxide emissions, oil prices, economic growth, and renewable energy is positive and statistically significant. ...
The past few decades have been marked by a gradual but steady increase in the reliance on renewable energy. In this study, we examined whether the prices of fossil fuels, namely, oil, coal, and natural gas, have affected renewable energy consumption in China during the period 1980-2018. To this end, we employed the novel dynamic Autoregressive Distributed Lag simulations approach. In the light of the empirical investigation, some intriguing conclusions have been drawn. We found strong evidence of the cointegrating relationship between the prices of all fossil fuels and renewable energy consumption. Furthermore, rising oil, coal, and natural gas prices resulted in increased renewable energy consumption in the long run, confirming that renewable energy sources can substitute fossil fuel energy only in the long run. Nevertheless, there is no evidence of significant effects in the short run. When considering the presence of structural breaks, the findings confirm the robustness of the dynamic ARDL simulations, as we conclude that fossil fuel prices positively affect renewable energy consumption only in the long run.
... Apergis and Payne (2014) note that higher fossil fuel prices, specifically oil and coal prices, lead to a rise in the consumption of renewables, which in turn positively impacts CO 2 emissions levels in seven Central American countries. Apergis and Payne (2015) determine that increasing oil prices cause an increase in CO 2 emissions in South America. Al-Mulali and Ö ztürk (2016) prove that increasing energy prices enable a decrease in CO 2 emissions in 27 advanced countries. ...
... In this vein, Rout et al. (2008) show that oil price hikes decreases CO 2 emissions. Apergis and Payne (2015) conclude that oil price increases stimulate CO 2 emissions. However, Al-Mulali and Ö ztürk (2016) define that increasing energy prices decrease CO 2 emissions. ...
This study analyzes the impacts of oil and natural gas prices on China's carbon efficiency using wavelet transform-based time series methods. To this end, the study applies the continuous wavelet transform (CWT), wavelet transform coherence (WTC), and a time-varying wavelet causality test (TVWCT) to daily data during the period from October 31, 2012 to November 3, 2022. The CWT results show that there are volatilities in oil prices due to the coronavirus 2019 (COVID-19) pandemic, in natural gas prices because of the Russia-Ukraine war, and in carbon efficiency resulting from the Paris Climate Agreement. The WTC results demonstrate that increasing oil prices promote carbon efficiency in the 2014-2016 and 2018-2020 periods, while natural gas prices have a weak impact on carbon efficiency in 2022. Moreover, the TVWCT results prove that there is a strong causality leading from oil and natural gas prices to carbon efficiency in the long run. These results highlight that China can use volatilities in oil and natural gas prices as a policy tool to enhance carbon efficiency.
... Moreover, (Akbostancı et al., 2009) considered that economic growth is susceptible to the environment as pollution can be a significant element that affects a country's growth of GDP. Apergis and Payne (2015) found an interrelation between oil prices, output per capita, green energy and environmental degradation, as a rise in green energy can reduce emissions. Moreover, the same study revealed a bidirectional relationship between green energy and carbon emissions; therefore, green energy and environmental degradation declare a longrun relation. ...
... To achieve a sustainable environment, many studies used the indicator called carbon dioxide emissions to measure environmental degradation. Literature provided evidence that lesser carbon emissions lead to a higher degree of environmental sustainability (Ang, 2007); (Acaravci and Ozturk, 2010); (Kaika and Zervas, 2013); (Al-Mulali et al., 2015); (Apergis and Payne, 2015); (Bilgili et al., 2016); (Zandi and Haseeb, 2019); (Jebli et al., 2020); (Majeed and Luni, 2020). (Kaygusuz, 2009) Studied green energy usage along with carbon dioxide emissions in Turkey. ...
... Renewable sources of energy are believed to have a smaller impact on the environment . These estimated findings coincide with the conclusion of Apergis and Payne (2015), Usman and Radulescu (2022), Saqib et al. (2023) and Usman et al. (2023b) who verified that the deployment of renewable energy is helpful in curtailing ecological footprint levels in the long-term. However, till now, emerging countries have enhanced their utilization of renewable energy resources, which is an uncontaminated energy source that donates to the alleviation of ecological footprint levels. ...
... Given that the panel estimators employed in this analysis may yield estimates that do not accurately replicate the causality direction between the chosen panel series, the study provides the outcomes of causality tests for these variables (Onifade et al., 2021). Next to CSD, the D-H causality technique is trustworthy and stable, allowing investigators to assess the connection between GDP growth is evidenced by (Apergis and Payne, 2015;Dogan and Turkekul, 2016), innovation in climate technology is evidenced by (Kasman and Duman, 2015;Jiang et al., 2022), alternative energy sources, and environmental impact. Table 9 discovers that bidirectional causality presents between GDP, TI, CT, RE, and EF. ...
The correlation between technological innovation, economic growth, renewable energy, and ecological footprint carries significant policy implications for environmental sustainability. Furthermore, financial inclusion can drastically affect the technology-climate nexus across different countries and its moderating impacts have received sufficient attention. To do this, this study examined how technological innovation, financial inclusion, economic growth, and renewable energy affected emerging economies' ecological footprint from 1990 to 2019. Additionally, this study also scrutinizes the moderating role of financial inclusion with other regressors on ecological footprint. To account for structural shifts, disguised cointegration, and numerous breaks in panel regression, this study applies advanced panel estimation methods for empirical analysis. The estimated outcomes exhibit that the influence of technical innovation, climate technologies, and renewable energy significantly reduces the ecological footprint levels. Besides, economic growth and financial inclusion significantly increase the ecological footprint levels in the emerging economies. Furthermore, the integration of innovative technology and renewable energy in emerging countries mitigates the adverse effects of financial inclusion by making it easier for creative technologies and reducing ecological footprints. These results show that emerging countries' innovative technology and renewable energy sources should be integrated with financial inclusion to enable long-term mitigation of environmental damages and sustainable growth. Based on these estimated findings, the research recommends that emerging economies should hasten technological innovations along with stronger financial development to curtail ecological concerns without hindering the pace of sustainable economic growth.
... The literature highlights that energy consumption shows a positive effect on GHG emissions growth (Lean and Smyth, 2010). Another interesting evidence between income, pollution, and the energy consumption is found (Apergis and Payne, 2015). More specifically, the authors suggested that, for a panel of 11 South American countries, the results confirm the positive relationship between real GDP per capita (among other variables) and renewable energy consumption per capita. ...
... The methodology is built around an extended Cobb-Douglas function (Apergis and Payne, 2015) that includes traditional factors (labor and capital), but also other economic indicators (exports, foreign direct investment, economic freedom) and variables related to energy consumption (renewable energy consumption and nuclear energy consumption). Table 1 provides details of the datasets used in this analysis. ...
In view of, the recently launched European Action Plan to achieve zero pollution, the aim of this paper is to assess the impact of governance quality on pollution in the revised forms of the Environmental Kuznets Curve, namely the nuclear energy Kuznets curve and the renewable energy Kuznets curve. Using a methodological framework focusing on cross-sectional dependence and cross-sectional heterogeneity, the panel data approach is based on the Augmented Mean Group and Common Correlated Effects Mean Group estimators, as well as the panel causality test of Juodis, Karavias and Sarafidis (2021). Taking the reference period 2002–2019 the analysis for a sample of countries that were the largest consumers of nuclear energy in the European Union during this period, namely Belgium, Germany, France, Sweden, Czech Republic, Hungary, Slovakia, Spain, Finland, and The Netherlands, suggests that industry development is a source of pollution, while governance could control environmental degradation through certain measures. Specifically, a lack of sufficient environmental laws, regulations, and policies enhances pollution even in countries with political stability and effective governance. These findings form the basis for future policy recommendations that should consider more green jobs and green technology in industry and a better legislative framework for pollution control
... In recent years, the role of renewable energy has been increasingly emphasized and has attracted the attention of scholars and energy policy analysts around the globe. Most studies use the Johansen co-linkage test and the Granger causal relationship test to show the relationship between renewable energy and economic plates such as GDP and FDI (Grabara et al., 2021;Apergis and Payne, 2015;Lee, 2013;Sadorsky, 2009) and environmental variables such as CO 2 output, greenhouse effect output (Leitão, 2014). Despite the number of existing studies on the effects of renewable energy use, their results vary significantly due to differences in research data sets and various context-dependent factors. ...
... Zoundi (2017) contends that renewable energy consumption has a detrimental effect on the emission of CO 2 . Research conducted by Apergis and Payne (2015) in South American states yielded valid proof that per capita CO 2 emissions have a constructive impression on the long-term use of renewable energy and a bidirectional causal linkage between both variables from 1980 to 2010 period. ...
The increasing rate of economic growth and globalization of the global economy has raised concerns regarding sustainable development, and renewable energy is being explored as a possible solution. The interrelationship between economics, environment, and energy consumption has been widely researched amongst academics worldwide; however, due to the inconsistent results, further exploration is needed to clarify the matter. Thus, this study seeks to investigate potential factors such as foreign direct investment (FDI), gross domestic product (GDP), and carbon dioxide (CO2) emissions that impact renewable energy consumption in countries within Southeast Asia. This research suggests that FDI flows bring positive aspects to the region's renewable energy sector while GDP and CO2 emissions have negative impacts. These findings can thus be employed as baseline information for future policies that strive to expand renewable energy activities in the region.
... Awareness of the need for energy conservation measures and the use of alternative energy sources, particularly renewable energy (RE), has increased in response to concerns about greenhouse gas emissions and climate change. Numerous scholars have pointed out that while traditional fossil fuels promote economic expansion, they also release carbon dioxide (CO2) into the atmosphere, which contributes to climate change and accelerates global warming [2][3][4][5][6][7][8][9]. For climate change risk to be reduced, all countries need to act quickly. ...
... Similar evidence for the long-term relationship between RE use and CO2 emissions was found [13]. Recent studies have also highlighted the use of RE as an alternative to fossil fuels [7,9,[14][15][16][17][18][19][20]. ...
Global warming has become a major concern for countries around the world. In this context, developed countries have decided to reduce global emissions to achieve sustainable development. The energy mix of OECD countries consists of 80% fossil fuels and accounts for about 35% of worldwide carbon emissions. Therefore, it is important to analyze how environmental factors affect carbon emissions in OECD countries. This study uses fossil energy, renewable energy (RE), and GDP for the period 1990–2019. Unlike previous studies, we will estimate two separate models for FFE and RE. To evaluate the empirical results, advanced panel data estimation methods using the cointegration test and the CS-ARDL estimation technique are employed to examine the long-run relationship between the variables. The results of the study demonstrate that fossil fuel use and GDP increase carbon emissions both in the short and long term. However, the use of RE hurts carbon emissions and is associated with sustainable development in OECD countries. Therefore, it is assumed that although fossil fuel use degrades the environment, economic growth helps it by reducing carbon emissions. Overall, our study shows that the use of RE is essential for OECD countries to achieve their environmental sustainability goals because it reduces the share of fossil fuels in the overall energy mix. Furthermore, in order to achieve a sustainable environment, OECD countries are recommended to begin long-term planning to reduce carbon emissions.
... Murshed and Tanha (2021) used a panel data model to show that oil prices in India and Pakistan have a negative impact on REC. Moreover, in South America, a long-term association between the two variables (real oil prices and REC) is found by Apergis and Payne (2015). Similarly, Nilsson (2019) and Hsiao et al. (2019) demonstrate that oil prices might be regarded as a crucial influence in green energy consumption. ...
... Following Omri and Nguyen (2014), Apergis and Payne (2015), and Uzar (2020), the model specification for this study is as follows: ...
This study investigates the impact of carbon emissions, real oil prices, income inequality, economic growth, and trade openness on renewable energy consumption (REC) in twenty-three (23) OECD economies. The study employs the Westerlund panel cointegration technique to verify the existence of long-run equilibrium and the Augmented Mean Group (AMG) estimator to assess the long-run relationship between the variables, which allows for slope heterogeneity and cross-sectional dependency. Moreover, the panel causality test of Dumitrescu and Hurlin (DH) is utilized to gauge the causal relationship between the variables. The findings of our study reveal that REC is positively related to economic growth, real oil prices, income inequality, and trade openness, but negatively related to CO2 emissions in OECD countries. In addition, there is one-way causality from GDP per capita to renewable energy consumption and a bidirectional causality between income inequality and REC. Furthermore, the results indicate that OECD policymakers and governments should regard foreign trade as a “clean energy fostering mechanism” while developing energy demand policies that are environmentally friendly.
... They concluded a one-way association moving from the usage of green sources of energy to carbon emissions. Afterward, Apergis and Payne (2015) concluded similar findings while estimating the association of renewable energy consumption, production, carbon discharge, and crude oil in the context of eleven South American states with the application of the Engle and Granger (1987) method. Later on, Sharif et al. (2020) studied the relation between green energy and non-green energy consumption, agrarian production, and CO 2 emissions in BRICS. ...
This research is motivated by the urgent need to address environmental quality challenges in South Asian economies. By examining the interplay of financial development, globalization, energy consumption, and corruption control, the study aims to identify strategies mitigating environmental degradation and fostering sustainable development in the region. The prime objective of this research is to examine the correlation between financial development, globalization, and energy consumption with environmental quality in South Asian economies. Moreover the study has also examined the moderating role of corruption control in the relationship between financial development, globalization, and energy consumption with environmental quality in South Asian economies. The research incorporates data from 1996 to 2019. Panel co-integration technique is employed to investigate the long-term correlations, and fully modified ordinary least squares is utilized to determine the coefficients of co-integrating vectors, ensuring a comprehensive and robust analysis of the examined variables The study finds that energy consumption, financial development, and globalization negatively affect South Asia’s environment. However, the presence of corruption control measures can mitigate these impacts therefore, given the region’s corruption concerns, effective anti-corruption measures become crucial to address environmental degradation. The empirical results stress the need for implementing such measures to alleviate adverse environmental effects in this specific area. The results implies that policymakers should balance economic growth with environmental sustainability, recognizing the interconnectedness of these factors. Thre results of the study highlights that addressing corruption is crucial in environmental policymaking, and policymakers should prioritize anti-corruption initiatives alongside conservation efforts. The study also suggests strengthening institutional frameworks and governance structures to curb corruption, creating an environment conducive to sustainable development. Future policies should integrate anti-corruption measures into environmental conservation strategies. The study highlights the need for anti-corruption measures in South Asia, in line with Sustainable Development Goals 16 and 13, to combat environmental degradation caused by energy consumption, financial development, and globalization, thereby promoting peace, justice, and strong institutions.
... Energy prices typically include natural gas, crude oil, electricity, and coal. Numerous scholars have examined the relationship between energy prices and carbon emissions, as evidenced by studies conducted by Apergis and Payne (2015), Dowling and Russ (2012), Fisher-Vanden et al. (2004), Hammoudeh et al. (2015), Kanamura (2016), and Luo et al. (2022). On the other hand, reverse feedback studies examining the effect of carbon on energy prices typically utilize carbon prices as the key variable. ...
... Apergis and Payne 2015). On the other hand, studies such asPesaran et al. (2001) were prominently contributing to the literature on measurement and assessment of SDGs through analytical analysis(Arellano and Bond 1998;Pesaran et al. 2001). ...
The global focus on evaluating environmental performance means that sustainable development goals must be prioritized to preserve environmental sustainability. In order to accomplish the SDGs, it is crucial that activities be preferred and that methods be developed to assess their effectiveness. As a result, the techniques used for the measurement and assessment of the SDGs have increased in significance for all countries. Researchers and academics create these technologies through research and invention. By undertaking a bibliometric analysis, this study aims to identify the scholarship in the area of SDG assessment and measurement. The analysis was produced by collecting the related studies from the Web of Science database. The information was retrieved, and a thorough and organized analysis was done to give crucial insights on the chosen issue. The analysis revealed the most often cited articles, important institutions that contributed, leading research-involved nations, and institutions. To evaluate the varied collection of techniques accessible for the goal of evaluating SDGs, a thorough review of the most cited works is conducted and provides a bird’s eye view of research on mechanisms for measuring the outcomes of SDGs.
... They came to the conclusion that both green and non-green sources of electricity significantly contribute to stimulating CO 2 emissions. By utilizing data from 11 South American economies, Apergis and Payne (2015) found similar findings. For newly industrialized economies, Destek (2016) examined the linkage among clean energy use, and economic growth during 1971-2011. ...
Like other developing countries, Pakistan faces one of the most serious challenges of how to mitigate carbon emissions while achieving sustainable development. Although, it is widely accepted that the rising trend of carbon emissions and the resulting negative effects of climate change on human activities have emerged as major issues in recent years, the environmental effectiveness needed to clean the environment and promote sustainability is often overlooked. Using the PLSM 2018-2019 survey, this study attempts to examine the household sector's renewable and non-renewable energy usage magnitude, and the share of renewable and non-renewable energy in Pakistan. Furthermore, this study examines the impact of income, household size, biomass, non-renewable energy, and clean energy on carbon emissions using the STIRPAT model. It is obvious from the empirical findings that the coefficient of income is positive, whereas the coefficient of income square is negative and statistically significant, which indicates that carbon emissions in the household sector increase at lower income levels, while decreasing as income increases. The household size shows that the population has a positive impact on carbon emissions. The impact of biomass, non-renewable, and clean energy is particularly appealing, as the household sector consumes more biomass and non-renewable energy, which stimulates carbon emissions to rise. In the rural sector, clean energy has a negative but statistically insignificant impact on carbon emissions, showing a greater reliance on biomass and non-renewable energy consumption. Lastly, it is suggested that reducing the use of non-renewable energy in the household sector while increasing the use of green energy could be a policy option for making the environment clean and sustainable. KEYWORDS renewable energy, non renewable energy, carbon emissions, STIRPAT, Pakistan
... This study time periods are 24 years and 40 countries data. The System GMM estimate is more efficient by overcoming the issue of endogeneity by using a set of instrumental variables, heteroskedasticity and autocorrelation (Apergis and Payne, 2015). This study applied System GMM to Equations (4) to (7) by following the methodology of Roodman (2006). ...
The study aims to analyze the Financial Development, Economic Development, Governance, and consumption of Fossil Fuels impact on Environmental Quality. Panel data of 40 developing countries for the period of 1996-2019 were examined by applying the System Generalized method of moments (GMM) technique of Blundell and Bond (1998). The results show that financial and economic development in developing countries is at the stake of environmental degradation. The governance impact is negative but low compared to other variables in the study, which shows that governance in these developing economies is not up to the mark and needs continuous improvement to maximize the impact of governance on environmental quality. Fossil fuels consumption in the sample countries showed a devastating effect on environmental quality. Financial reforms are needed to encourage and give incentives to the firms to adopt environmentally friendly technologies, which will result in development in a more sustainable way in developing economies. Easy access to low-interest loans in developing economies will help farmers and live stockholders to adopt new technologies and rethink their approaches to using fertilizers and livestock production to mitigate the emissions of CH4 and N2O. Renewable energy sources (solar panel-generated energy in industries and households, electric cars, etc.) in these developing economies will help to tackle the increase in greenhouse gases emissions because of fossil fuel consumption.
... When the real interest rate is high, it means that borrowing money is expensive which can discourage investment. The oil price is an alternative to renewable energy, meaning that a higher oil price may lead to greater investment in renewable energy [48]. However, the expectation is negative since an increase in oil price could lead to increased production of non-oil energy [49]. ...
The shift to renewable sources of energy has become a critical economic priority in African countries due to energy challenges. However, investors in the development of renewable energy face problems with decision making due to the existence of multiple criteria, such as oil prices and the associated macroeconomic performance. This study aims to analyze the differential effects of international oil prices and other macroeconomic factors on the development of renewable energy in both oil-importing and oil-exporting countries in Africa. The study uses a panel vector error correction model (P-VECM) to analyze data from five net oil exporters (Algeria, Angola, Egypt, Libya and Nigeria) and five net oil importers (Kenya, Ethiopia, Congo, Mozambique and South Africa). The study finds that higher oil prices positively affect the development of renewable energy in oil-importing countries by making renewable energy more economically competitive. Economic growth is also identified as a major driver of the development of renewable energy. While high-interest rates negatively affect the development of renewable energy in oil-importing countries, it has positive effects in oil-exporting countries. Exchange rates play a crucial role in the development of renewable energy in both types of countries with a negative effect in oil-exporting countries and a positive effect in oil-importing countries. The findings of this study suggest that policymakers should take a holistic approach to the development of renewable energy that considers the complex interplay of factors, such as oil prices, economic growth, interest rates, and exchange rates.
... Therefore, the assumption is that it reduces bio productive resource demand. The literature indicates that REC has a smaller share of the energy mix, however, through technological progress, it can be maximized, to achieve a zero-carbon society (Apergis and Payne, 2015;Doroshenko et al., 2021). ...
Climate degradation is a significant issue around the globe, and climate change mitigation technologies and the
effective use of natural resources are significant factors in reducing climate degradation, which require research
attention. The current article analyses the impact of climate mitigation technology (renewable energy production
and consumption) and natural resource management (natural resource rent and depletion) on climate change
(greenhouse gas emissions) in China. A nonlinear ARDL technique is used to test the link between the constructs
over the period 1991–2021. The findings reveal that renewable energy (RE) output, RE consumption, natural
resource rent, and natural resource depletion have negative associations with greenhouse gas (GHG) emissions in
China, while industrialization and population growth have positive associations. The research provides guide-
lines for regulators formulating regulations related to climate change using climate mitigation technology and
effective use of natural resour
... In addition, we utilize a System Dynamics (SD) approach to examine the dynamic relationships and structure between the factors influencing economic growth, energy consumption, CO2 emissions, and sanctions. Many studies have been conducted on the connection between economic growth, energy consumption, and the environment, mostly using time series techniques and optimization models (Jayanthakumaran et al., 2012;Omri, 2013;Apergis and Payne, 2015;Wang et al., 2016;Chen and Lei, 2018;Wasti and Zaidi, 2020;Ahmad et al, 2016). ...
This study aims to simulate the future trends of carbon emissions under different international sanction scenarios in Iran. A System Dynamics (SD) model is developed and several variables that capture multiple levels of economic, social, and environmental concepts are taken into account. Our findings indicate that, despite Iran's sluggish economic growth, fossil fuel use and CO2 emissions will rise in the scenarios with international sanctions. Imposed sanctions on Iran exacerbate the environmental negative externalities through increasing energy intensity of economic sectors and consequently cause more CO2 emissions. Thus, based on our findings, prolonging international sanctions could be a major barrier to improving energy intensity and lowering CO2 emissions. Given the potential unintended environmental consequences of international sanctions, this study suggests that international communities, particularly sanctioning countries, should consider the environmental impacts of sanctions in their policy-making decisions in order to reduce emissions and related environmental damages.
... The findings indicate a positive and statistically significant estimated coefficient for fossil fuels (coal and oil), suggesting considerable substitution between renewable energy sources and fossil fuels. Furthermore, Apergis and Payne (2015) investigated the long-run causal dynamics between REC per capita, real GDP per capita, carbon dioxide emissions per capita, and actual oil prices, with a panel sample of 11 South American countries from 1980 to 2010. Using panel cointegration procedures, the author shows that an increase in real oil prices leads to an increase in REC per capita in the short run. ...
This study uses two empirical approaches to explore the asymmetric effects of oil and coal prices on renewable energy consumption (REC) in China from 1970 to 2019. As a conventional approach, we used the nonlinear autoregressive distributed lags (NARDL) model, while machine learning was used as a non-conventional approach. The empirical findings of the NARDL indicate that oil and coal price fluctuations have a significant effect on REC for both the short and long term. The results of the non-conventional approaches based on machine learning indicated that the SVM model was more efficient than the KNN model in terms of accuracy, performance, and convergence. Referring to the SVM model findings, the results show that an increase in the coal price has a higher ability to predict REC than the oil price. As a robustness check, we also find that an increase in Brent prices significantly decreases REC. The findings of this study support the view that there is a substitution effect from oil to coal before initiating the use of renewable energy in China.
... The second trend (Figure 3b) analyzes the interlinkages between oil prices and CO2 emissions. For example, Alkathery and Chaudhuri 2021;Apergis and Payne 2015;Royal et al. 2022;Sadorsky 2009;Zaghdoudi 2017) analyze the co-movements among oil prices, CO2 emissions, and renewable energy. The findings suggest that renewable energy improves environmental quality in both the short and long run; an increase in oil prices causes a decrease in CO2 emissions and has an important effect on Royal et al. 2022;Sadorsky 2009;Zaghdoudi 2017) analyze the co-movements among oil prices, CO 2 emissions, and renewable energy. ...
Wavelet power spectrum (WPS) and wavelet coherence analyses (WCA) are used to examine the co-movements among oil prices, green bonds, and CO2 emissions on daily data from January 2014 to October 2022. The WPS results show that oil returns exhibit significant volatility at low and medium frequencies, particularly in 2014, 2019–2020, and 2022. Also, the Green Bond Index presents significant volatility at the end of 2019–2020 and the beginning of 2022 at low, medium, and high frequencies. Additionally, CO2 futures’ returns present high volatility at low and medium frequencies, expressly in 2015–2016, 2018, the end of 2019–2020, and 2022. WCA’s empirical findings reveal (i) that oil returns have a negative impact on the Green Bond Index in the medium term. (ii) There is a strong interdependence between oil prices and CO2 futures’ returns, in short, medium, and long terms, as inferred from the time–frequency analysis. (iii) There also is evidence of strong short, medium, and long terms co-movements between the Green Bond Index and CO2 futures’ returns, with the Green Bond Index leading.
... In addition, the improvement in energy diversification and energy security due to renewables contributes to its popularity. Apergis and Payne (2015) identify a long-run positive relationship between oil price and renewable energy consumption in 11 South American countries. Bamati and Raoofi (2020) find a comparable result in a panel of 25 developed and developing countries. ...
Environmental degradation and energy security are placing greater emphasis on the development of renewable energy across the world. This study explores the driving forces of renewable energy in The Organisation for Economic Co-operation and Development countries from 1992 to 2019, focusing on technologies and regulations. Specifically, it applies the panel quantile regression to analyze the long-term impacts of environmentally related technologies and environmental regulations on renewable energy consumption. In this regard, the study offers a novel methodological contribution that makes it possible to explain the heterogeneous role of such factors in countries with low, medium, and high-development levels of renewable energy. The results indicate that while environmentally related technologies drive renewable energy positively, the higher beneficial impacts are realized at medium to high quantiles of renewable energy consumption. In contrast, environmental regulations greatly promote renewable energy at low and medium levels of renewable energy consumption. Moreover, higher stringency starts diminishing renewable energy consumption at its 90th quantile, indicating the existence of the “green paradox” effect. The results suggest the bi-directional linkage between green technologies and renewable energy while there is a uni-directional causality running from environmental regulations to renewable energy. These discoveries lead to valuable policy implications for different countries aiming to develop renewable energy. Countries in the initial phase of renewable energy development should strengthen environmental regulations while those at the later stage should encourage technological innovations and control the potential side effects of stringent environmental policies.
... All declared causality findings have policy suggestions as technological innovations are seen to encourage the protection of environmental sustainability without hindering the pace of economic growth trajectory. This relationship (between CO 2 emission and GDP growth) is evidenced by (Apergis and Payne 2015;Dogan and Turkekul 2016). This theory is supported by the literature, and it is crucial to highlight the fact that renewable energy and technological innovations are increasing ecological integrity in E-7 economies (Kasman and Duman 2015;Jiang at. ...
The present study examines the potential of the traditional environmental Kuznets curve (EKC) with an extension for growing industrialized economies, including Brazil, China, India, Indonesia, Russia, Mexico and Turkey (E- 7 economies) spanning from 1995 to 2019. Since the E-7 economies are still in a growing phase, this study adds to the EKC phenomenon by taking into description human development, the use of renewable energy, and technological innovations for investigation. Second-generational panel econometrics techniques, such as cross-sectional augmented autoregressive distributive lag (CS-ARDL), Augmented Mean Group (AMG), and Dumitrescu- Hurlin causality tests, form the basis of the experimental framework’s design. The study confirms the existence of the EKC phenomena in E-7 economies, where income expansion is prioritized in relation to environmental sustainability. The study’s findings demonstrate that technological modernization helps to mitigate pollution level. Therefore, human development, technological innovation, and the use of renewable energy are held up as the panacea for reducing carbon emissions over the time period under study. Finally, some further policy suggestions are provided.
... According to their results, there is a positive relationship between oil prices and carbon emissions in Venezuela. Apergis and Payne (2015) applied a panel data model to show that there was a positive and statistically significant relationship between oil price and carbon emissions per capita in 11 South American countries in the period 1980-2010. Simsek and Yigit (2017) applied the vector autoregression model to examine the relationship between carbon emissions and oil prices in Brazil, Russia, India, China, and Turkey. ...
The worldwide growing concern for environmental protection compels businesses to incorporate green orientation in their strategies. Crowdfunding has opened new possibilities to attract investors by encompassing green concerns in their agenda. This study investigates the relationship between green orientation and UK crowdfunding campaign success. We have used both qualitative and quantitative approaches to build the green orientation index, for which we have chosen 210 green campaigns out of 720 crowdfunding campaigns. Then we performed a cluster analysis to identify three clusters (social enthusiast, green fan, and tech-oriented) of green-oriented crowdfunding campaign. We performed a predictive validity analysis to identify which cluster is more effective in ensuring the crowdfunding’s performance. The results show that tech-oriented obtain the highest value and share a positive relationship with the amount raised and crowdfunding’s success. Social enthusiast effectively attracts more crowd through the social platform and thereby successfully raises funds. Green orientation, however, does not affect crowdfunding success or overfunding, which shows that there is a huge difference between the clusters, suggesting that the green orientation itself is not considered so important for the crowdfunding campaigns. It also highlights a crucial point the in the crowdfunding’s objectives, the realization of the environmental concern, society, and the long-term sustainability concern is not promising.KeywordsCrowdfundingGreen orientationSustainabilityCluster analysis
... There is a heated debate that to reduce the environmental effect of economic growth, efforts should be made to structurally transit from traditional fossil fuel energy consumption to alternative and clean energy systems (see Apergis and Payne 2015;Ben Jebli et al. 2015;Dogan and Seker 2016;Zafar et al. 2019;Ike et al. 2020b;Usman et al. 2020a;Iorember et al. 2022). Hence, both developing and developed countries, over the years, have been pushing energy-conservative policies amidst high levels of poverty and inequality among the people. ...
Promoting green energy is generally considered a crucial way to mitigate energy-related CO2 emissions. However, the level at which a country’s expenditure on green energy technologies interacts with renewable energy consumption to save the planet has been ignored in the literature. Within the context of the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, this study investigates the interaction effect of renewable energy and expenditure on green energy technologies in mitigating CO2 emissions in G7 countries over the period 1990–2017. The empirical results based on the Method of Moments-Quantile Regression (MM-QR) with fixed effects suggest that renewable energy and expenditure on green energy technologies have a negative and heterogeneous effect on CO2 emissions. The interaction term has a stronger negative and heterogeneous effect across quantiles distribution of CO2 emissions. This suggests that the extent to which renewable energy exerts downward pressure on CO2 emissions is dependent on countries’ expenditures on green energy technologies. In addition, the effect of the interaction term is stronger in countries with lower levels of CO2 emissions. Given these findings, the study suggests the need to promote investment in green energy technologies as a catalytic converter to mitigate CO2 emissions.
... They stated that oil prices, economic growth and CO 2 emissions could increase renewable energy consumption. Apergis and Payne (2015) examined the relationship between renewable energy, GDP, CO 2 emissions and oil prices in 11 South American countries from 1980 to 2010. The results indicated that CO 2 , GDP and oil prices positively and significantly affect renewable energy consumption. ...
Purpose
One of the most important ways to pay attention to sustainable economic development is to invest in green technology and alter the energy consumption structure (ECS) in countries. Changing the ECS can be important in two ways: first, it increases the diversity of energy consumption and reduces energy dependence on other countries. Second, the use of highly polluted nonrenewable energy sources (such as oil and coal) is reduced, leading to the transfer of energy to natural gas with less carbon emissions or renewable energy. To this end, the authors examined the asymmetric effects of eco-innovation on the US ECS from 1980 to 2019. This paper aims to address this issue.
Design/methodology/approach
In this research, the nonlinear autoregressive distributed lag (ARDL) (NARDL) model is used and the results are compared with the linear ARDL model.
Findings
The ARDL results also confirm the positive effects of oil prices and GDP per capita in the long run. On the other hand, short-term and long-term Wald test results confirm the nonlinear effects of eco-innovation (LPATENT) on US ECS. These results indicate that 1% positive shock in LPATENTˆ+ increases the ECS by 0.179, while 1% negative fluctuations (LPATENTˆ-) leads to a decrease (−0.085) in the ECS. However, the ARDL results, in general, show the positive effects of LPATENT on the ECS in long run. Evidence suggests that ignoring nonlinear effects can lead to inaccurate results. Policy suggestions for environmental technology innovation are presented in the results.
Originality/value
This research has innovations in various aspects so that the previous studies in this field have examined the effects of environmental innovation on renewable or nonrenewable energy consumption, and so far no study has been done on the ECS. In this research, the Shannon–Wiener index has been used to calculate the ECS.
... Studies examining the correlation between renewable energy consumption and environmental degradation criteria obtained different results in the literature. Accordingly, empirical results indicating that renewable energy consumption decreases environmental degradation Apergis et al. 2010;Shafiei and Salim 2014;Bilgili et al. 2016;Paramati et al. 2017;Sharif et al. 2019;Sharif et al. 2020a, b;Rauf et al. 2020;Destek 2016;Pham et al. 2020;Khan et al. 2020;Destek and Sinha 2020;Khan et al. 2021), there is no correlation between renewable energy consumption and environmental degradation Saidi and Mbarek 2016;Bento and Moutinho 2016;Cherni and Jouini, 2017;Jebli and Youssef 2017;Liu et al. 2017a;Chen et al. 2019;Alola et al. 2019), renewable energy consumption increases environmental degradation (Farhani and Shahbaz 2014;Apergis and Payne 2015;Khan et al. 2018;Yazdi and Beygi 2018,) or environmental degradation increases renewable energy consumption while renewable energy consumption decreases environmental degradation (Apergis et al. 2010;Dogan and Seker 2016;Waheed et al. 2018;Cai et al. 2018;Sharif et al. 2020a, b;Koengkan et al. 2020) were obtained. ...
In this study, it is aimed to analyze the effect of biomass energy consumption on environmental degradation for BRICS (Brazil, Russia, India, China, and South Africa) countries. For that purpose, the data of CO2 emission values, ecological footprint and its components, “cropland, grazing land, forest land, fishing ground, built-up land, and carbon footprint” from 1992 to 2018 are used as criteria of environmental degradation. The diversity of the variables used regarding environmental degradation is important in terms of evaluating the effect of biomass energy consumption in detail. Pedroni and Kao Co-integration tests and FMOLS and DOLS analyses are used to estimate long-term correlation coefficients. With these analyses used, it was aimed to make more reliable estimations with the number of observations in the sample analyzed. According to the result of this study, biomass energy consumption increases ecological footprint values but decreases CO2 emission in BRICS countries. In addition, economic growth increases ecological footprint and CO2 emission; however, urbanization decreases them in BRICS countries.
... Despite various empirical studies on the determinants of environmental degradation across regions, countries, and blocs, there is still no consensus among researchers on the issue (Ahmed et al. 2021b;Nathaniel et al. 2021c, d;Eregha et al. 2022;Ekeocha 2020;Liu et al. 2021;Omojolaibi and Nathaniel 2020;Akam et al. 2021a, b;Apergis and Payne 2015;Nathaniel et al. 2021a). The reasons for this could be differences in methodological procedures, choice of variables, data type, and sample size. ...
Military spending is required for national sovereignty, but it comes at a cost. The ecological consequences of military activities remain insufficiently investigated, especially in developing countries, where military spending is on the rise due to terrorism and civil unrest created by different secessionists’ groups. As such, this study has a maiden attempt to address this gap by exploring the effects of military spending on the ecological footprint (EF) using the bootstrap causality test and the Maki (2012) cointegration test under multiple structural breaks. The findings suggest that military spending increases the EF. Also, while energy consumption and economic growth degrade the environment, financial development enhances environmental wellbeing by reducing the ecological footprint. The causality results suggest a unidirectional causality from military spending to EF, while feedback causality exists between military spending and economic growth. The result of this study affirms the existence of destruction theory and also provides a better understanding of the links behind environmental degradation and is applicable for the design and implementation of environmental policies.
The energy transition in Central Asia faces multiple risks while lacking empirical assessment of renewable energy use from a sustainability perspective. This paper examined the relationship of renewable energy consumption with energy intensity and carbon intensity in Central Asia during 1993—2019, using the seemingly unrelated regression (SUR). Weighing the heterogeneity of countries in the region, the results showed that downstream countries build an inverted U‐shaped relationship between renewable energy consumption and carbon intensity, while the whole region indicates an inverted U‐shaped relationship between renewable energy consumption and energy intensity. Compared with hydrocarbon, nonfossil energy is expected to serve as a greater driving force for economic growth in the future, alleviating socio‐economic dependence on fossil fuels in downstream countries and generating additional revenues to ensure energy security in upstream countries. The findings suggest policymakers to considerably mitigate the risks of decarbonization across the region.
Purpose
This study aims to assess the nexus among oil price (OP), renewable energy consumption (REC) and trade balance (TB) for India using annual time series data for the time period 1985–2019. In particular, the authors examine whether REC improves India's TB in the context of high oil import dependence.
Design/methodology/approach
The study uses autoregressive distributed lags (ARDL) bound testing approach that has the advantage of yielding estimates of long-run and short-run parameters simultaneously. Moreover, the small sample properties of this approach are superior to other multivariate cointegration techniques. Fully modified ordinary least square (FMOLS) and dynamic ordinary least squares (DOLS) are also applied to test the robustness of the results. The causality among the series is investigated through block exogeneity test based on vector error correction model.
Findings
The findings based on ARDL bounds testing approach indicate that OPs exert a negative impact on TB of India in both long run and short run, whereas REC has a favorable impact on the TB. In particular, 1% increase in OPs decreases TBs by 0.003% and a 1% increase in REC improves TB by 0.011%. The results of FMOLS and DOLS corroborate the findings from ARDL estimates. The results of block exogeneity test suggest unidirectional causation from OPs to TB; OPs to REC and REC to TB.
Practical implications
The study underscore the importance of renewable energy as a potential tool to curtail trade deficits in the context of Indian economy. Our results suggest that the policymakers must pay attention to the hindrances in augmentation of renewable energy usage and try to capitalize on the resulting gains for the TB.
Social implications
Climate change is a major challenge for developing countries like India. Renewable energy sector is considered an important instrument toward attaining the twin objectives of environmental sustainability and employment generation. This study underscores another role of REC as a tool to achieve a sustainable trade position, which may help India save her valuable forex reserves for broader objectives of economic development.
Originality/value
To the best of the authors’ knowledge, this is the first study that probes the dynamic nexus among OPs, REC and TB in Indian context. From a policy standpoint, the study underscores the importance of renewable energy as a potential tool to curtail trade deficits in context of India. From a theoretical perspective, the study extends the literature on the determinants of TB by identifying the role of REC in shaping TB.
This paper investigates whether geopolitical conflicts play a critical role in stimulating countries to shift toward clean energy solutions. We use the panel regime-switching models, which allow us to capture the nonlinear dynamics of the energy transition. Our results for a panel of developed and emerging countries reveal that the geopolitical context does not impact the renewable-income nexus; however, we find that adverse geopolitical events would impact the diffusion of alternative energy sources depending on the level of economic development. Rising geopolitical conflicts would encourage high-income nations to switch toward low-carbon energy sources. Considering the increasing number of regional conflicts, less developed countries must urgently develop their economies away from traditional energy sources and enhance the contribution of the renewable sector.
A major challenge for humans in the twenty-first century is devising a way to minimize environmental pollution while fostering economic growth that will not deplete the planet's resources. Despite increased awareness of climate change and efforts to combat it, the amount of pollution emissions on the Earth continues to drop significantly. This study employs cutting-edge econometric methods to examine the long- and short-term asymmetric and causal impacts of renewable and non-renewable energy consumption and financial development on CO2 emissions in India at both aggregate and disaggregated levels. Thus, this work fills a significant gap in research. A time series from 1965 to 2020 was used for this study. Wavelet coherence was employed to investigate causal effects among the variables, while the NARDL model addressed long-run and short-run asymmetry effects. Our findings indicate that (i) REC, NREC, FD, and CO2 emissions are all interconnected in the long run, (ii) NREC and FD significantly trigger CO2 emissions in India in the long run, and (iii) the results of a wavelet coherence-based causality test support the long-term estimates of this study.
This research explores the relationship among renewable energy consumption (REC), trade openness, carbon emanations, income inequality on economic growth. This study takes fifteen (15) OECD nations data set start from 1997 to 2020 by employing the AMG assessor, which takes into account slope heterogeneity (SH) and CSD. The empirical outcomes confirm a significant favorable long-run relationship between these nexus, except for Carbon emanations, which are adversely related with REC, respectively. Notwithstanding, it has discovered that there is bi-directional causality between income inequality and REC.
JEL Classification: D47
This study examines the predictive power of oil shocks for the green bond markets. In line with this aim, we investigated the extent to which oil shocks could be used to accurately make in- and out-of-sample forecasts for green bond returns. Three striking findings emanated from our results: First, the three types of oil shock are reliable predictors for green bond indices. Second, the performances of the predictive models were consistent across the different forecasting horizons (i.e. H = 1 to H = 24). Third, our findings were sensitive to classifying the dataset into pre-COVID and COVID eras. For instance, the results confirmed that the predictive power of oil shocks declined during the crisis period. We also discuss some policy implications of this study's findings.
Understanding the interactions among climate change, carbon emission allowance trading, crude oil and renewable energy stock markets, especially the role of climate change in this system is of great significance for policy makers, energy producers/consumers and relevant investors. The present paper aims to quantify the time-varying connectedness effects among the four factors by using the TVP-VAR based extensions of both time- and frequency-domain connectedness index measurements proposed by Antonakakis et al. (2020) and Ellington and Barunik (2021) [8,48]. The empirical results suggest that, firstly, the average total connectedness among climate change, carbon emission allowance trading, crude oil and renewable energy stock markets is not so strong for the heterogenous fundamentals underlying them. Nevertheless, the time-varying total connectedness fluctuates fiercely through May 2005 to September 2021, varying from about 8% to 30% and rocket to very high levels during the global subprime mortgage crisis and the COVID-19 pandemic. Furthermore, the total connectedness mainly centers on the short-term frequency, i.e., 1–3 months. Secondly, climate change is generally the leading information contributor among the four factors, although not particularly strong, and its leading role also performs mainly on the short-term frequency (1–3 months). Thirdly, renewable energy stock market and crude oil market show tight interactions between them and they are the two major bridges of information exchanges across various time frequencies (horizons) in this system. Finally, we confirm the evidence that the primary net connectedness contributor and receiver switch frequently across different time frequencies, implying that it is extremely essential for policy makers, energy producers/consumers and investors to make time-horizon-specific regulatory, production/purchasing or investment decisions when facing the uncertain effects of climate change on the interactions among carbon emission allowance, crude oil and renewable energy stock markets.
One of the reasons behind environmental degradation and climate change is greenhouse gases that are mainly consisted of carbon dioxide (CO2) emissions. Besides, CO2 emissions negatively affect human health. Consequently, national institutions should understand which factors are affecting carbon emissions in order to achieve sustainable (environmental, social and economic) development. The main objective of this paper is to examine the symmetric and asymmetric effects of oil price, foreign direct investments and economic growth on carbon emissions in Italy. To this purpose, the long and short-run impact of these variables on carbon emissions have been investigated by applying the autoregressive distributed lag (ARDL) and non-linear ARDL methodologies to Italian data for the period 1970–2019. The symmetric results show that economic growth and foreign direct investments intensify carbon emissions both in the long and short-run, while the impact of oil price on emissions is negative in the long-run and positive in the short-run, suggesting that oil price is responsible for environmental degradation only in the short run. The asymmetric results reveal that both in the long and short-run an increase in the oil price imply reductions in carbon emission.KeywordsSustainable developmentCarbon dioxide emissionsARDL modelNon-linear ARDL model
Introduction: In recent decades, global economic growth and industrialization have increased the demand for the consumption of energy. The increasing energy demand is met by burning fossil fuels, which emit air pollution and greenhouse gas emissions. After the industrial revolution, energy generation abnormally increased the amount of greenhouse gases emission, critically damaging the environment. In this regard, the purpose of this study is to investigate the determinants of carbon dioxide emissions (CO2) as an indicator of environmental quality and air pollution.
Material and methods: This study has proposed a long-run relationship between CO2, economic growth, energy consumption, trade openness, financial development, and urbanization for a global panel of 11 countries spanning the period 2000–2015 using Fully Modified Ordinary Least Square (FMOLS) and Dynamic Ordinary Least Square (DOLS). In the first step, the LLC and IPS unit root tests were performed to examine the nonstationarity properties of the dataset. Then, Pedroni and Kao co-integration tests were applied to identify if there is a correlation between variables in the long term. In addition, the F (Chow) test was used to detect the best model. The software package used for estimation and analysis of the models was Eviews 10.
Results and discussion: This paper first performed a panel unit root test proposed by Levin, Lin, and, Chu (LLC) and Im, Pesaran and, Shin (IPS) to examine the null hypothesis that all the series have a unit root. The results of IPS test indicated that the null hypothesis was rejected only for urbanization, implying that this variable was stationary. However, all tests confirmed that variables were stationary after the first-difference. It is hereby informed that variables were first-difference stationary. Our results suggest that there is a need to examine co-integration among variables. In addition, we conduct Pedroni and Kao co-integration tests, the results of which rejected the null hypothesis of no co-integration. The results of the F-test indicated that the panel model was the right choice. To help us choose between the fixed effects or random effects estimators, we conduct the Hausman test, where the null hypothesis was that the preferred model has random effects. Our results from the Hausman test did not reject the null hypothesis, suggesting that the random effects estimator was more appropriate for our data than the fixed effects estimator. The results from the FMOLS and DOLS estimations indicated that energy consumption from renewable sources, trade openness, financial development, and urbanization had a negative impact on CO2 emissions, while the energy consumption from non-renewable sources had a positive impact.
Conclusion: The results of the research imply that policymakers should focus more on public awareness of renewable energy, mainly in solar and wind power to alleviate environmental pressure and CO2 emission. The findings also suggest that the governments should set a price per ton on carbon i.e. a carbon tax. Furthermore, developed countries should transfer sophisticated technology to emerging and undeveloped countries to generate electricity and avoid unsafe climate change.
Keywords: Air pollution, Greenhouse gases, CO2 emission, FMOLS, DOLS.
Bu çalışma, Türkiye ile AB ülkeleri arasında elektrikli motora sahip olan araçlara uygulanan vergi oranlarındaki farklılıkları ve sonuçlarını göstermeyi amaçlamaktadır. Durumun net olarak ortaya konulması sorunun çözümü için en önemli adımdır. Bununla birlikte elektrikli araç kullanmayı teşvik etmemenin bir sorun olduğu da tartışmalıdır. Bu konuda yapılan çalışmalarda henüz kesin bir sonuca ulaşılmamıştır. Bununla birlikte AB, bu konuda ısrarlı ve girişimci bir pozisyonda yer almaktadır. AB, dışsal maliyetlerin de göz önüne alınmasıyla, yenilenebilir enerjiye yapılacak olan her yatırımın uzun vadede hem daha karlı hem de daha çevreci olacağı görüşünü savunmaktadır. Bu nedenle elektrikli araçlara geçiş konusunda farklı tedbirler ve teşvikler uygulamaktadır. AB, taşıtların karbon bazlı olarak vergilendirilmesi gibi tedbirler alırken, elektrikli araçların satın alınması ve kullanılması sırasında da finansal ve mali teşvikler uygulamaktadır. Türkiye’de ise bu yönde vergisel teşvik çalışmaları AB ülkelerinin gerisinde bulunmaktadır. Her ne kadar elektrikli araçlardan, içten yanmalı motorlu araçlara göre satın almada daha az vergi alınıyor olsa da alınan vergiler AB düzeyinde yüksek boyutlarda olmaktadır. Elektrikli araç satın alınmasında ise herhangi bir finansal teşvik bulunmamaktadır. AB ülkelerinde elektrikli araç alımında ülkeden ülkeye değişmekle birlikte 5.000 €’ya kadar karşılıksız destek sağlanmaktadır. Bu nedenlere bağlı olarak, çalışma sonucunda görülmektedir ki, Türkiye’de ilk kez kaydı yapılan otomobiller arasında elektrikli otomobillerin oranı %0,3 iken, AB ülkelerinde bu oran %10 düzeyindedir.
Let n observations Y 1, Y 2, ···, Y n be generated by the model Y t = pY t−1 + e t , where Y 0 is a fixed constant and {e t } t-1 n is a sequence of independent normal random variables with mean 0 and variance σ2. Properties of the regression estimator of p are obtained under the assumption that p = ±1. Representations for the limit distributions of the estimator of p and of the regression t test are derived. The estimator of p and the regression t test furnish methods of testing the hypothesis that p = 1.
Increased economic growth and demand for energy in emerging economies is creating an opportunity for these countries to increase their usage of renewable energy. This paper presents and estimates two empirical models of renewable energy consumption and income for a panel of emerging economies. Panel cointegration estimates show that increases in real per capita income have a positive and statistically significant impact on per capita renewable energy consumption. In the long term, a 1% increase in real income per capita increases the consumption of renewable energy per capita in emerging economies by approximately 3.5%. Long-term renewable energy per capita consumption price elasticity estimates are approximately equal to −0.70.
Economic and societal issues related to energy security and global warming is placing greater emphasis on the consumption of renewable energy. This paper presents and estimates an empirical model of renewable energy consumption for the G7 countries. Panel cointegration estimates show that in the long term, increases in real GDP per capita and CO2 per capita are found to be major drivers behind per capita renewable energy consumption. These results are robust across two different panel cointegration estimators. Oil price increases have a smaller although negative impact on renewable energy consumption. Deviations from equilibrium are driven mostly by the error correction term as opposed to short term shocks. Short term deviations from the long term equilibrium take anywhere from between 1.3 years (France) and 7.3 years (Japan) to correct.
It is now quite common to have panels in which both T, the number of time series observations, and N, the number of groups, are quite large and of the same order of magnitude. The usual practice is either to estimate N separate regressions and calculate the coefficient means, which we call the Mean Group (MG) estimator, or to pool the data and assume that the slope coefficients and error variances are identical. In this paper, we propose an intermediate procedure, referred to as the Pooled Mean Group (PMG) estimator, which constrains the long run coefficients to be identical, but allows the short run coefficients and error variances to differ across groups. We consider both the case where the regressors are stationary and the case where they follow unit root processes, and for both cases derive the asymptotic distribution of the PMG estimators as T tends to infinity. We also provide two empirical applications: aggregate consumption functions for 24 OECD economies over the period 1962-93, and energy demand functions for 10 Asian developing economies over the period 1974-90.
This study estimates a panel error correction model to determine the Granger-causal relationship between renewable and non-renewable electricity consumption and economic growth for South America. The results show a long-run equilibrium relationship between real gross domestic product, renewable electricity consumption, non-renewable electricity consumption, real gross fixed capital formation, and the labor force with the respective long-run coefficient estimates positive and statistically significant. The Granger-causality results indicate bidirectional causality between renewable and non-renewable electricity consumption, respectively and economic growth in both the short-run and long-run.
This study examines the determinants of renewable energy consumption per capita for a panel of seven Central American countries over the period 1980 to 2010. Specifically, we find a long-run cointegrated relationship exists between renewable energy consumption per capita, real GDP per capita, carbon emissions per capita, real coal prices, and real oil prices with the respective coefficients positive and statistically significant. A structural break in the cointegrating relationship appears in 2002 which coincides with the establishment of the Energy and Environment Partnership with Central America initiative to expand the use of renewable energy sources. Recognizing the regime shift in 2002, we estimate a nonlinear panel smooth transition vector error correction model to show that for the post-2002 period, the influence of renewable energy consumption per capita upon real coal and oil prices strengthened relative to the pre-2002 period as well as a greater sensitivity of real GDP per capita to carbon emissions per capita.
This article analyses the determinants of renewable energy consumption in a panel of six major emerging economies, namely Brazil, China, India, Indonesia, Philippines and Turkey that are proactively accelerating the adoption of renewable energy. Using Fully modified ordinary least square (FMOLS), Dynamic ordinary least square (DOLS), and Granger causality methods this paper finds that in the long-run, renewable energy consumption is significantly determined by income and pollutant emission in Brazil, China, India and Indonesia while mainly by income in Philippines and Turkey. Causal link between renewable energy and income; and between renewable energy and pollutant emission are found to be bidirectional in the short-run. These results suggest that the appropriateness of the efforts undertaken by emerging countries to reduce the carbon intensity by increasing the energy efficiency and substantially increasing the share of renewable in the overall energy mix.
This article examines the causal dynamics between renewable energy consumption, real gross domestic product (GDP), carbon emissions, and real oil prices using the Toda-Yamamoto long-causality test procedure over the period 1949 to 2009. The results indicate that renewable energy legislation and policies since 1978 had a positive and statistically significant impact on renewable energy consumption. Though the results suggest that real GDP, carbon emissions, and real oil prices did not have a causal impact on renewable energy consumption, unexpected shocks to real GDP and carbon emissions yielded a positive impact on renewable energy consumption over time.
This chapter uses fully modified OLS principles to develop new methods for estimating and testing hypotheses for cointegrating vectors in dynamic panels in a manner that is consistent with the degree of cross sectional heterogeneity that has been permitted in recent panel unit root and panel cointegration studies. The asymptotic properties of various estimators are compared based on pooling along the 'within' and 'between' dimensions of the panel. By using Monte Carlo simulations to study the small sample properties, the group mean estimator is shown to behave well even in relatively small samples under a variety of scenarios.
This study examines the relationship between energy consumption and economic growth for a panel of nine South American countries over the period 1980–2005 within a multivariate framework. Given the relatively short span of the time series data, a panel cointegration and error correction model is employed to infer the causal relationship. Pedroni's heterogeneous panel cointegration test reveals a long-run equilibrium relationship between real GDP, energy consumption, the labor force, and real gross fixed capital formation with the respective coefficients positive and statistically significant. The Granger-causality results indicate both short-run and long-run causality from energy consumption to economic growth which supports the growth hypothesis.
We examine properties of residual-based tests for the null of no cointegration for dynamic panels in which both the short-run dynamics and the long-run slope coefficients are permitted to be heterogeneous across individual members of the panel. The tests also allow for individual heterogeneous fixed effects and trend terms, and we consider both pooled within dimension tests and group mean between dimension tests. We derive limiting distributions for these and show that they are normal and free of nuisance parameters. We also provide Monte Carlo evidence to demonstrate their small sample size and power performance, and we illustrate their use in testing purchasing power parity for the post Bretton Woods period.I thank Rich Clarida, Bob Cumby, Mahmoud El-Gamal, Heejoon Kang, Chiwha Kao, Andy Levin, Klaus Neusser, Masao Ogaki, David Papell, Pierre Perron, Abdel Senhadji, Jean-Pierre Urbain, Alan Taylor, and three anonymous referees for helpful comments on various earlier versions of this paper. The paper has also benefited from presentations at the 1994 North American Econometric Society Summer Meetings in Quebec City, the 1994 European Econometric Society Summer Meetings in Maastricht, and workshop seminars at the Board of Governors of the Federal Reserve, INSEE-CREST Paris, IUPUI, Ohio State, Purdue, Queens University Belfast, Rice University University of Houston, and Southern Methodist University. Finally, I thank the following students who provided assistance in the earlier stages of the project: Younghan Kim, Rasmus Ruffer, and Lining Wan.
Asymptotic distributions and critical values are computed for several residual-based tests of the null of no cointegration in panels for the case of multiple regressors, including regressions with individual-specific fixed effects and time trends. The associated cointegrating vectors and the dynamics of the underlying error processes are permitted considerable heterogeneity across individual members of the panel. Copyright 1999 by Blackwell Publishing Ltd
The relationship between cointegration and error correction models, first suggested by Granger, is here extended and used to develop estimation procedures, tests, and empirical examples. A vector of time series is said to be cointegrated with cointegrating vector a if each element is stationary only after differencing while linear combinations a8xt are themselves stationary. A representation theorem connects the moving average , autoregressive, and error correction representations for cointegrated systems. A simple but asymptotically efficient two-step estimator is proposed and applied. Tests for cointegration are suggested and examined by Monte Carlo simulation. A series of examples are presented. Copyright 1987 by The Econometric Society.
This paper examines whether electoral motives and government ideology influence short-term economic performance. I employ data on annual GDP growth in 21 OECD countries over the 1951-2006 period and provide a battery of empirical tests. In countries with two-party systems GDP growth is boosted before elections and, under leftwing governments, in the first two years of a legislative period. These findings indicate that political cycles are more prevalent in two-party systems because voters can clearly punish or reward political parties for governmental performance. My findings imply that we need more elaborate theories of how government ideology and electoral motives influence short-term economic performance.
The panel data unit root test suggested by Levin and Lin (LL) has been widely used in several applications, notably in papers on tests of the purchasing power parity hypothesis. This test is based on a very restrictive hypothesis which is rarely ever of interest in practice. The Im-Pesaran-Shin (IPS) test relaxes the restrictive assumption of the LL test. This paper argues that although the IPS test has been offered as a generalization of the LL test, it is best viewed as a test for summarizing the evidence from a number of independent tests of the sample hypothesis. This problem has a long statistical history going back to R. A. Fisher. This paper suggests the Fisher test as a panel data unit root test, compares it with the LL and IPS tests, and the Bonferroni bounds test which is valid for correlated tests. Overall, the evidence points to the Fisher test with bootstrap-based critical values as the preferred choice. We also suggest the use of the Fisher test for testing stationarity as the null and also in testing for cointegration in panel data. Copyright 1999 by Blackwell Publishing Ltd
Recent developments in the field of the econometrics of panel data with non-stationary series are reviewed and interpreted. In particular, we discuss tests for unit roots and cointegration, and the roles of mean and variance correction, non-parametric correction and full modification for the construction of these tests and estimators. A discussion of the key contributions of the papers in this special issue is placed within the framework of the current literature and areas for further development are propose. Copyright 1999 by Blackwell Publishing Ltd