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This study provides insight into sustainability challenges in Venezuela by exploring the causal interactions between oil price, energy consumption and carbon dioxide (CO2) emissions in Venezuela. Economic growth, government consumption expenditure and trade openness are included as additional determinants in the analysis. The auto-regressive distri...
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... expenditure is incorporated using general government final consumption expenditure. Table 2 presents the definition and data sources of all the variables used in this study, while the plots of the series are presented in Fig. 2. ...Context 2
... lnEngy t = α 0 + α 1 lnOil t + α 2 lnCO 2 t + α 3 lnRgdpc t + α 4 lnGCE t + α 5 lnTrd t + ε t , (2) lnCO 2 t = b 0 +b 1 lnOil t +b 2 lnEngy t +b 3 lnRgdpc t +b 4 lnRgdpc 2 t +b 5 lnGCE t +b 6 lnTrd t +ε t , Model 3: economic growth where ε t is the white noise error term. Oil, CO 2 , Engy, Rgdpc, GCE and Trd are as defined in Table 2. 'ln' indicates that all variables are in natural logarithm. ...Context 3
... also allows for simultaneous testing of the long-run and short-run relationships between variables in small and large sample sizes and provides unbiased coefficients of variables along with valid t-statistics even when the explanatory variables are endogenous ( Pesaran et al. 2001). These statistical features have made ARDL bounds approach to cointegration popular among researchers in recent years (see Shahbaz et al. 2013; Ali (3) lnRgdpc t = δ 0 + δ 1 lnOil t + δ 2 lnEngy t + δ 3 lnCO 2 t + δ 4 lnGCE t + δ 5 lnTrd t + ε t , Crude Oil Price (US$ per barrel) Table 2) ...Context 4
... is a dummy variable that captures the possibility of structural breaks in the data series. All the variables are as defined in Table 2. The null hypothesis of no cointegration among the variables in Eq. (4) H 0 : α 7 = α 8 = α 9 = α 10 = α 11 = α 12 = 0 is tested against the alternative hypothesis H 1 : ...Context 5
... expenditure is incorporated using general government final consumption expenditure. Table 2 presents the definition and data sources of all the variables used in this study, while the plots of the series are presented in Fig. 2. ...Context 6
... lnEngy t = α 0 + α 1 lnOil t + α 2 lnCO 2 t + α 3 lnRgdpc t + α 4 lnGCE t + α 5 lnTrd t + ε t , (2) lnCO 2 t = b 0 +b 1 lnOil t +b 2 lnEngy t +b 3 lnRgdpc t +b 4 lnRgdpc 2 t +b 5 lnGCE t +b 6 lnTrd t +ε t , Model 3: economic growth where ε t is the white noise error term. Oil, CO 2 , Engy, Rgdpc, GCE and Trd are as defined in Table 2. 'ln' indicates that all variables are in natural logarithm. ...Context 7
... also allows for simultaneous testing of the long-run and short-run relationships between variables in small and large sample sizes and provides unbiased coefficients of variables along with valid t-statistics even when the explanatory variables are endogenous ( Pesaran et al. 2001). These statistical features have made ARDL bounds approach to cointegration popular among researchers in recent years (see Shahbaz et al. 2013; Ali (3) lnRgdpc t = δ 0 + δ 1 lnOil t + δ 2 lnEngy t + δ 3 lnCO 2 t + δ 4 lnGCE t + δ 5 lnTrd t + ε t , Crude Oil Price (US$ per barrel) Table 2) ...Context 8
... is a dummy variable that captures the possibility of structural breaks in the data series. All the variables are as defined in Table 2. The null hypothesis of no cointegration among the variables in Eq. (4) H 0 : α 7 = α 8 = α 9 = α 10 = α 11 = α 12 = 0 is tested against the alternative hypothesis H 1 : ...Similar publications
In order to contribute to the ongoing discussions on the environment-economy relationship, the relationship between renewable energy consumption, export diversification, economic growth and CO2 emission in the countries considered as transformation economies was investigated in the period between 1997 and 2014 in the current study. In the study, IP...
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... At the same time, some studies (Appiah et al., 2023;Liu et al., 2023;Song et al., 2024)show that higher GDP growth increases green innovation. Likewise, several studies (Agbanike et al., 2019;Chen & Lei, 2018;Tao et al., 2023) indicate that renewable energy use plays a more substantial role in promoting sustainable economic growth. Based on the previous studies, in this study similarly, we conclude that the positive and significant interactions of climate change and clean energy innovations affect economic growth. ...
This paper examines whether accelerating climate change adaptation and clean energy innovations is an effective way to promote sustainable development and mitigate environmental risks. Based on this, the main purpose of this study is to investigate the potential effect of climate change adaptation and clean energy innovations with casual factors of social, political, human development, environmental, and climatic determinants as drivers of economic growth in 38 Organization for Economic Cooperation and Development (OECD) countries from 1990 to 2020. Employing the system-generalized method of moments (GMM) method, this study shows that causal factors of social, political, educational , and environmental development have a positive effect on the economic growth process. Additionally, the interaction between climate change adaptation and temperature has a constant positive impact on economic growth. The findings highlight that policymakers should thoroughly evaluate the potential impacts of the climate change adaptation process and clean energy innovations in all aspects and implement measures and approaches that promote sustainable development, increase the adoption of environmentally friendly technologies, and address the challenges posed by climate change.
... The ARDL model for testing cointegration (the ARDL bounds test) was employed to examine the model [44], whether the variables were stationer at level or the first difference (I(0) or I(1)) or mutually cointegrated (I(0) and I(1)), allowing for the simultaneous testing of the long-term and short-term relationships among them. The application of the ARDL bounds tests involved testing for the presence of a long-term relationship, in this study, based on the log linear form, by using the dynamic unrestricted error correction model (UECM) to integrate the short-term relationship with the long-term equilibrium [44,45]. ...
... The ARDL model for testing cointegration (the ARDL bounds test) was employed to examine the model [44], whether the variables were stationer at level or the first difference (I(0) or I(1)) or mutually cointegrated (I(0) and I(1)), allowing for the simultaneous testing of the long-term and short-term relationships among them. The application of the ARDL bounds tests involved testing for the presence of a long-term relationship, in this study, based on the log linear form, by using the dynamic unrestricted error correction model (UECM) to integrate the short-term relationship with the long-term equilibrium [44,45]. ...
Despite having a strong production capacity for fresh coconut, Indonesia has a certain deficiency in coconut processing, particularly coconut oil products, which is reflected in the declining market demand rates. The skyrocketing price of palm kernel oil (PKO) had been observed to impact the shifting demand for coconut oil. The cross-price competition with PKO was estimated to uncover the potential market demand for Indonesian coconut oils, especially during the periods of price discrepancies between 2020 and 2022. Thus, our study aimed to analyze the Indonesian coconut oil and palm kernel oil (PKO) market relationship as the markets reacted during the period of price volatility. This study is essential for Indonesian market evaluation, as both commodities are considered to be perfect substitute goods and are similar substances that contain high levels of lauric acid called “lauric oils”. We deployed an ARDL analysis utilizing secondary data from 1964 to 2022, focusing on the cross-price elasticity between coconut oil and PKO prices with the addition of prominent concerned variables. In the long-term estimations, the observational results indicated that the coconut oil and PKO prices had distinctive impacts on Indonesian coconut oil exports of −1.85% and 1.88%, respectively. In the short-term estimations, we found inverse values: the coconut oil price had positive impacts in the short-term period of 1.29% (D1.) and 2.35% (LD.), while the PKO had a negative impact on Indonesian coconut oil exports of −2.17%. This indicated that a PKO price reduction would increase the demand for Indonesian coconut oil exports due to the PKO price volatility and uncertainty perceived by the buyers in the short term. Our study also observed that rival producers, such as the Philippines, had a negative impact (−1.80%), representing the intense competition between Indonesia and the Philippines. Therefore, the Indonesian government has to elevate its coconut oil competitiveness to acquire the potential to expand the market and compete with other major coconut-producing countries.
... Venezuela's developmental narrative is one that embodies both potential and pitfalls, set against a backdrop of immense natural wealth, historical trajectories, and contemporary realities (Pradhananga et al., 2021;Zimmerman & Chu, 2013). By examining a wide array of socio-economic, political, and policy-related dimensions, this article contributes to the discourse on development studies in Venezuela, aiming to provide a foundational resource for policymakers, researchers, and stakeholders seeking to engage with the country's developmental intricacies (Rodriguez & Guerrero, 2020; Agbanike et al., 2019). ...
... The present article contributes to this ongoing discourse by conducting a comprehensive analysis of development studies in Venezuela. By examining the challenges that have hampered progress and the prospects that may offer avenues for positive change, this study seeks to provide a holistic understanding of the forces at play (Agbanike et al., 2019). ...
This journal article delves into the multifaceted landscape of development studies in Venezuela, shedding light on the country's ongoing socio-economic challenges, policy interventions, and potential pathways towards sustainable development. By examining the intricate interplay of political, economic, and social factors, this study seeks to provide a nuanced understanding of the complex dynamics that have shaped Venezuela's development trajectory. Through a comprehensive review of scholarly literature and empirical data, the article aims to contribute to a deeper comprehension of the obstacles and opportunities facing the nation, offering insights that can inform policy decisions and academic research in the field of development studies.
... Natural resources are recognized as a crucial element in sustaining social well-being and economic growth (Kongbuamai et al., 2020;Redmond & Nasir, 2020). However, overexploitation of these resources can cause ecological disruption by degrading the environment, either directly through their use and extraction for economic purposes (Wu et al., 2017) or indirectly through the increase in economic activities generated by revenues from trade in certain natural resources, e.g., oil (Agbanike et al., 2019). ...
... This is partly because, as economic activity intensifies, so does the demand for energy, which is mainly met by burning fossil fuels, thus contributing to CO 2 emissions. In addition, the excess demand for oil with the rise in its price will boost revenues from oil resource exports, thus leading to an increase in economic activity (Agbanike et al., 2019). This demand surge can also encourage additional trade openness through increased exports. ...
This study explores the impact of natural resource exploitation, trade openness, and economic growth on carbon emissions in a sample of oil‐exporting nations for the period 1971–2014. To examine this relationship, we used the panel autoregressive distributed lag model and a set of econometric techniques accounting for cross‐sectional dependence. Our results indicate that the exploitation of natural resources and trade openness have a long‐term negative impact on environmental quality. Furthermore, our analysis confirms the validity of the Kuznets Environmental Curve for oil‐exporting countries. An assessment of causality reveals a bidirectional link between natural resources, economic growth, and CO 2 emissions, as well as a unidirectional link between trade openness and CO 2 emissions. In the light of our findings, appropriate policies could include the imposition of more stringent regulations on the exploitation of natural resources, the application of taxes on carbon emissions, and the promotion of clean and renewable technologies. Greater international cooperation is also needed to address these environmental issues on a global scale.
... There is a complex and interdependent relationship between carbon emissions and economic development. Specifically, for countries rich in petroleum resources, the impact of carbon emissions on economic growth is generally negative, as increased CO 2 emissions often lead to inhibited economic growth [15,16]. However, at the global level, an increase in carbon emissions can actually stimulate economic growth in the short term [17]. ...
While the environmental issues resulting from carbon emissions are widely recognized by the public, there is a lack of in-depth research on whether controlling carbon emissions will have an impact on social development at the national level. In this study, we used panel data from 166 countries worldwide from 2005 to 2020 to construct coupled coordination models, panel regression models, and spatial Durbin models to assess the impact of carbon emissions on the coupled coordinated development of sustainable development goals (SDGs) in different countries around the world. This study is the first to investigate the features, heterogeneity, and spatial effects of carbon emissions on the SDG coupling coordination degree. We found that: (1) Globally, the SDG coupling coordination degree was generally low from 2005 to 2020. Despite the slow improvement in the global SDG coupling coordination degree over the past 16 years, it has always been in a barely imbalanced transitional development state. At the same time, there was a phenomenon of “high-income > high–middle-income > low–middle-income > low-income” difference in the SDG coupling coordination development level among countries of different income types. (2) Carbon emissions have a significant promoting effect on the SDG coupling coordination degree for low-income and low–middle-income countries while having a significant inhibitory effect on the SDG coupling coordination degree for high–middle-income and high-income countries. In addition, the impact of carbon emissions on the SDG coupling coordination degree also exhibits regional heterogeneity. (3) Carbon emissions have a significant spatial spillover effect on the SDG coupling coordination degree, with a positive promoting effect on the SDG coupling coordination degree in one’s own country and a significant inhibitory effect on the SDG coupling coordination degrees of neighboring countries. Our research can help decision-makers develop targeted carbon reduction plans to avoid social development losses caused by controlling carbon emissions in a crude manner. Our research findings provide crucial evidence for the formulation of international policies aimed at reducing carbon emissions, in order to avoid the inequities that may result from the adoption of extreme carbon reduction policies.
... Indeed, a rise in oil prices may induce a fall in demand for oil and, consequently, would lead to lower greenhouse gas emissions. The relationship between oil prices and CO 2 emissions was analyzed by several scholars including Andersson and Karpestam (2013), Nwani (2017), Zou (2018), Mensah et al. (2019), Wang et al. (2019), Agbanike et al. (2019), and Ullah et al. (2020). However, there is no agreement regarding the findings, and the subject is open to debate. ...
This study investigates the Granger causal interplays between renewable energy consumption, WTI crude oil prices, and CO2 emissions in the USA using monthly data between January 1986 and May 2022. The study applies quantile-based techniques, namely, the quantile unit root test developed by Galvao (2009), the quantile cointegration test proposed by Xiao (2009), and the novel Granger causality-in-quantiles test suggested by Troster (2018). The results suggest that the series display a unit root across different quantiles and that the cointegration relationships exhibit heterogeneous behavior across quantiles. Regarding the causal linkages, the findings show: (i) a unidirectional causality from renewable energy consumption to oil prices, mainly at the lowest or highest quantiles of the distribution, (ii) a bidirectional causality between oil prices and CO2 emissions
mainly in the middle and extreme quantiles, but there is evidence of causality from oil prices to CO2 emissions across the quantiles than in the reverse direction, and (iii) a unidirectional causality from renewable energy consumption to CO2 emissions at the lowest to medium and the highest quantiles. These findings have important implications for policy-makers.
... In spite of various environmental policies implemented to different industries, China is considered the main carbon emitter (Guo et al., 2019). Existing literature of Wu et al. (2021) and Agbanike et al. (2019) affirms the role of TOUR industry in enhancing GLOB in the world. Hence the role of the said variables is important to explore for China. ...
The environmental problem has become a worldwide issue that must be frequently examined. Thus, this study investigates the relation of tourism, natural resources, globalization, and foreign direct investment on the ecological footprint of the USA, the UK, Pakistan, China, and India by using annual data from 1995 to 2020. The study applied Zivot and Andrews (1992) test to demonstrate the stationarity properties of the series, and an autoregressive distributed lag (ARDL) approach was employed to estimate the long-run and short-run dynamics. The long-run findings disclose that tourism has a significantly positive effect on China and Pakistan, but a significantly negative impact on India. The outcomes further suggest that foreign direct investment increases environmental degradation in India and China in both long and short periods, but contributes to improving the UK’s ecosystem. Besides, globalization in China tends to save its environment. Natural resources in the long run also harm the ecosystems of Pakistan, China, and the USA. The error correction term is negatively significant for all countries. The reliability of the model is investigated through diagnostic tests. The selected model is stable as the critical value of CUSUM and CUSUMSQ lie within the 5% significance level.
... Thus, 'technology-tourism-climate' needs to be re-evaluated by comprehensive measures, consistent estimates, and improved estimation systems. The research report by Agbanike et al. (2019) investigated that given variables are cointegrated, and unidirectional causalities were found in the research. In addition, it was highlighted that renewable energy, tourism development, and foreign direct investment (FDI) contribute to reduced greenhouse gas emissions. ...
This study demonstrates the linkages between green technological innovations, sustainable tourism, financial development, economic growth, and ecological sustainability using China's regional data from 2000 to 2019. The study applies the novel estimation technique, Quantile Autoregressive Distributive Lag (QARDL) approach to examine long-run and short-run relationships between the stated variables. The initial findings confirm non-linearity in the data verified through J-B test statistics. It approves the implication of QARDL estimation for exploring ecological sustainability trends over the study period. The study outcomes confirm that tourism and green technology innovation assists in reducing ecological footprints in China in the long run. Moreover, financial development and economic growth reflect a direct role towards more ecological footprints; therefore, the sustainability dimension has been missing both in financial development and growth. Furthermore, the results in the short run cover the same phenomenon and confirm that ecological innovations and tourism would help in sustaining the natural environment. The study outcomes demonstrate that government officials in China should specifically implement long-term policies to support the natural environment from adverse shocks of more financial development and economic growth.
... The travel industry's CO 2 emissions have been measured using a variety of monetary models in order to indicate environmental change (Zhao et al., 2020;Peng et al., 2021a;Zhao et al., 2021) (Balsalobre-Lorente, et al., 2020. For the most part, the econometric models focused on the direct link between the travel industry's growth and climate change Agbanike et al., 2019). It is becoming increasingly clear that environmental change, particularly in high-emanation areas, will have a significant impact on the tourism industry's long-and medium-term prospects (Lemieuxa, 2010). ...
The aim of this research is to examine the potential influence of FDI inflows and tourism industry on carbon dioxide emissions in China using System GMM models for a sample period of 1980–2019. Using FMOLS and DOLS models, this research examines the long-term relationship between the variables, as well as the long-term association among components. Co-joining the boards of FMOLS and DOLS models shows a general correlation between the investigation elements and CO2 emissions in China. FDI, tourism sector, and environment-friendly electricity use have all been major contributors to rising CO2 emissions in China for a long time. Using System GMM, FMOLS, and DOLS models in China, we examined the influence of the travel sector on carbon dioxide emissions as well as environment-friendly electricity usage and foreign direct investment. The government of China is being pushed to attract more foreign direct investment in order to improve the system and expand the transportation industry. As a reasonable responsibility to an unnatural climate change, methods for developing the movement business and theories relating to the movement business should be adopted.
... Also, in this case, we can see that the effect (positive correlation, i.e., warm colour) is mainly concentrated in the frequency range of 32-64. This result is derived from the relationship between oil price and electricity consumption (Agbanike et al., 2019). ...
This paper investigates how oil price, COVID-19, and global energy innovation can affect carbon emissions under time- and frequency-varying perspectives. We contribute to the literature by being the first research to document the relationship between these variables in the short and long run (dynamically) at different frequencies in a multivariate context, thus providing a more detailed picture of the forces driving CO2 emissions. For this purpose, we use a novel methodology, i.e., the wavelet local multiple correlation (WLMC) recently developed by Polanco-Martínez et al. (2020). The results provide fresh evidence of long-run asymmetric dynamic correlations, highlighting how the oil price plays a key role in the dynamics of CO2 emissions. Moreover, we find that, during the long period, there is a strong negative co-movement between CO2 and the global energy innovation index, i.e., more investment in clean energy induces less emission. Supported by our findings, this research suggests crucial policy implications and insights for the governments worldwide in their efforts to revive their economies amidst the pandemic and environmental uncertainties.
