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This study investigates the impact of financial stability on environmental degradation in Turkey, controlling for economic growth, renewable energy consumption, and primary energy consumption between 1990 and 2019. The study employs various statistical methodologies, including LS Unit Root, Fourier ARDL, DOLS, and FMOLS tests. The findings reveal an inverse relationship between financial stability and environmental degradation. Both economic growth and primary energy consumption are found to exacerbate environmental degradation. This study recommends that policymakers incorporate financial stability into policies aimed at reducing CO2 emissions. Furthermore, it emphasizes the importance of investing in renewable energy infrastructure and the transportation sector to effectively mitigate environmental degradation. [ABSTRACT FROM AUTHOR]

Iceland aims to achieve carbon neutrality by 2040 and to cut carbon emissions by 40% by 2030 under the Paris Agreement. Iceland’s major policy instrument for reaching its emissions reduction and carbon neutrality objectives is a Climate Action Plan, which was amended in 2020 and included 48 initiatives. Therefore, the research investigates the impact of carbon intensity, economic growth, globalization, and energy productivity on consumption-based emissions in Iceland from 1995Q1 to 2019Q4. The Fourier Autoregressive Distributed Lag Model (FARDL) is used in this study to investigate the ramifications of a long-term association. Long-run estimations demonstrate that Iceland’s environmental quality is deteriorating due to carbon intensity and economic development. It implies that increasing the carbon intensity and economic growth is environmentally damaging. Furthermore, economic expansion has a significant impact on environmental sustainability. Increased energy production also decreases consumption-based emissions, which contributes significantly to Iceland’s sustainable environment. Globalization has a positive and significant influence. A 1% rise in globalization, in particular, enhances consumption-based emissions over time. The finding is crucial for policy preferences and might be used to implement robust policy measures to address environmental challenges. [ABSTRACT FROM AUTHOR]

[Display omitted] • We assessed the effect of technological innovation and structural change on carbon emissions in Turkey. • We applied the novel dynamic ARDL and frequency domain causality techniques. • We found that technological innovation enhances the quality of the environment. • We also found nonrenewable energy use and economic growth contribute to environmental degradation. • We found no support for the EKC hypothesis in Turkey. Climate change and environmental degradation have become the most complex and contentious global concerns in recent decades, despite growing worldwide accords demanding that these serious issues must be addressed urgently. Thus, we assessed the effect of technological innovation, economic growth, structural change, and nonrenewable energy use on CO 2 emissions in Turkey using a yearly dataset spanning between 1980 and 2019. The current paper utilized the ARDL bounds test, dynamic ARDL, and Breitung Candelon causality tests to assess these interrelationships. The outcomes of both the ARDL bounds and Bayer and Hanck cointegration tests affirmed evidence of cointegration among the variables. Furthermore, the outcomes of the dynamic ARDL disclosed that economic growth and nonrenewable energy use contribute to the degradation of the environment, while technological innovation stimulates the quality of the environment. Using the approach suggested by Itkonen (2012), the current paper does not confirm the EKC hypothesis. Lastly, the outcomes of the Breitung Candelon causality revealed a feedback causality association between nonrenewable and CO 2 emissions, while a unidirectional causality exists from technological innovation, economic growth, and structural change to CO 2 emissions. Based on the above findings, we propose that the government of Turkey should restructure its energy sector to address both carbon emissions and production losses by boosting the use of eco-friendly and efficient technologies in the process of production, while also shifting to a more services-based economy. [ABSTRACT FROM AUTHOR]

Risks associated with climate change can have an injurious impact on the economy as well as the financial system as a whole. There is a possibility that certain risks, such as losses to financial intermediaries and disruptions in the functioning of financial markets, can aggravate vulnerabilities in the financial system under certain conditions, including sudden increases in the prices of large asset classes. Using the dataset for Norway between 1995 and 2018, this study investigates how financial stability affects environmental degradation in Norway while controlling openness in trade, ecological clean energy, and economic growth. Findings from the results demonstrate that (i) financial stability causes a reduction in environmental degradation; (ii) growth causes carbon emissions to climb significantly; and (iii) renewable energy has been favorable for emissions in Norway. Lastly, surprisingly, trade openness causes a decline in carbon emissions. The study recommends that since financial stability in Norway reduces environmental degradation by incorporating climate-related risks into the financial stability monitoring framework, it can contribute to lowering carbon emissions to a greater extent. Norway's policymakers should conduct detailed analyses of the role of global emissions in long-term petroleum policy and the economic viability of selected climate policy scenarios before implementing such a policy. Moreover, policymakers should be updated on the financial system's vulnerabilities, considering climate-related shocks are likely to affect all financial systems. In addition, policymakers should encourage the use of sustainable energy to raise the availability of reliable, affordable, and sustainable energy to everyone. [ABSTRACT FROM AUTHOR]

The impact of financial reforms and financial development on an economy has received considerable attention over the recent past. According to McKinnon and Shaw, financial liberalization policy and, in particular, interest rate deregulation is a means for achieving high economic growth by boosting savings and investments. This paper aims to investigate the long‐run relationship between financial liberalization and economic growth in Liberian as articulated by McKinnon and Shaw's theory. The study employed time series data spanning from 1980 to 2016 and dataset was sourced from World Development Indicators databases. The dataset was estimated using econometric techniques of Combined Co‐integration test, Dynamic Ordinary Least Squares, and robustness check of Fully Modified Ordinary Squares, and Canonical Co‐integration Regression, respectively. Results reveal, positive and significant coefficient of financial liberalization variables, thus supporting the McKinnon and Shaw hypotheses. Also, found long‐run Combined Co‐integration among the estimated models. Policy recommendation includes that policymakers should refrain from policy that will adversely affect deposit interest rates considering its immense impact on savings mobilization, gross investment, and economic growth. Furthermore, improving competition will compel deposit‐taking institutions to raise deposit interest rates in a bid to attract more depositors, thus reducing interest rates spread. [ABSTRACT FROM AUTHOR]

Countries encounter conflicting policy options in reaching fast development goals due to high resource use, rapid economic expansion, and environmental degradation. Thus, the present research examined the connection between CO2 emissions and urbanization, globalization, hydroelectricity, and economic expansion in China utilizing data spanning the period between 1985 and 2018. The novel quantile-on-quantile (QQ) and quantile regression (QR) approaches were applied to assess this interconnection. The QQ approach is characterized by its ability to incorporate quantile regression fundamentals and non-parametric estimation research. As a result, the method appears to transform the quantile of one parameter into another. The QQ outcomes revealed that in all quantiles (0.1–0.95), gross domestic product (GDP), urbanization, and globalization trigger CO2 emissions in China, while in each quantile (0.1–0.985), hydroelectricity consumption mitigates CO2 emissions. The QR outcomes also affirmed the outcomes of the QQ regression estimates. Policies are suggested based on these findings. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the effect of financial development and renewable energy consumption on consumption‐based CO2 emissions in Chile while controlling for economic growth and electricity consumption. Based on the aim of the paper, autoregressive distributed lag (ARDL) bounds with Kripfganz and Schneider's (2018) approximations, fully modified ordinary least square (FMOLS), dynamic ordinary least square (DOLS), and gradual shift causality tests are applied in this study. The outcomes clearly reveal that while financial development and renewable energy consumption reduce the consumption‐based CO2 emissions in Chile, economic growth and electricity consumption increase consumption‐based carbon emissions. The gradual shift causality test provides consistent results with ARDL, FMOLS, and DOLS estimators. Therefore, policymakers in Chile should dynamically encourage the research and development of low‐carbon technologies and renewable energy investments while imported nonrenewable energy sources level should be targeted, and especially those sectors which are more energy‐intensive and causing to increase in consumption‐based CO2 emissions. [ABSTRACT FROM AUTHOR]

South Africa is one of Africa's most polluted countries, with rising CO2 emissions posing a threat. South Africa must discover ways of minimizing pollution and take necessary steps before it is too late in order to achieve sustainable growth. For this purpose, this research assesses the ecological consequences of globalization, nonrenewable energy use, economic growth and renewable energy consumption in South Africa. The study leverages on the non-linearity advantages of the novel quantile on quantile regression (QQR) method for a robust analysis as opposed to the use of conventional linear approaches, thereby overcoming conspicuous shortfalls in extant studies, while offering a detailed explanation of the overall dependency structure between CO2 emissions and globalization, nonrenewable energy use and renewable energy use using a dataset covering the period between 1970 and 2018. The outcomes suggest that nonrenewable energy use, globalization, and economic growth contribute to environmental degradation in the majority of the quantiles, while the effect of renewable energy use on CO2 is not strong at all quantiles. The study highlights that economic expansion, nonrenewable energy use and globalization play key roles in in mitigating environmental sustainability in South Africa, while renewable energy is not sufficient to meet environmental requirements. [ABSTRACT FROM AUTHOR]

This study investigates the correlation between government expenditures and economic growth by applying the wavelet coherence approach for the period of 1960Q2 – 2019Q3 in the United States. Two main concepts regarding the correlation between government expenditures and economic growth are the renowned Keynesian approach, which argues that government expenditures lead economic growth, and Wagner's Law, which advocates the opposite. Our results indicate that economic growth leads government expenditures in the long run, whereas government expenditures only enhance economic growth in the short run and in periods of recession. [ABSTRACT FROM AUTHOR]

This research examines the factor of causality between the variables of economic growth and carbon emissions in China, by conducting full, and sub-sample Granger causality tests for the period of 1965 to 2019. The full-sample Granger causality test is not considered to be authentic, and is rather unstable, as indicated by the parameter stability tests. Therefore, we consider the time variation using a causality test, and the results indicate that the causality exists from the Gross Domestic Product (GDP) growth to the Carbon Dioxide (CO2) emissions. This development essentially suggests that economic growth is critical for China's environment. It also implies that carbon emissions are mainly determined by the increase in economic growth, at some specific period in time. Thus, in this regard, the use of renewable energy sources should be encouraged by policymakers, in order to deal with rise in the energy demand, and promote industrial upgrading, so as to slow down the rate degradation that the environment have been experiencing. However, our empirical results indicate that CO2 emissions are not the Granger reason to GDP. In this case, the government can formulate more conservative reduction policies that pertain to carbon emissions, and will therefore, not impede the economic growth. [ABSTRACT FROM AUTHOR]

To minimize the awful situation confronting the entire globe, the global warming danger has raised the intensity of consciousness from all areas of life. Therefore, the research assesses the impact of CO2 emissions and energy use on economic performance and considers trade openness, urbanization, and agriculture in Indonesia utilizing data covering the period from 1965 to 2019. The current research employed the dynamic ordinary least square (DOLS) and autoregressive distributed lag (ARDL) tests to capture the long-run association between these economic indicators. Furthermore, the gradual shift and wavelet coherence tests are utilized to capture the direction of causality. The ARDL bound test discloses a long-run interconnection among the variables of interest. The outcomes of the ARDL and DOLS depict that CO2 emissions, agriculture, energy use, and urbanization trigger economic growth. Moreover, the wavelet coherence test findings revealed a positive correlation between economic growth and urbanization, CO2 emissions, agriculture, and energy consumption. Furthermore, there is evidence of a weak and positive correlation between economic growth and trade openness. The gradual shift causality test outcomes disclosed that economic growth can predict urbanization and energy consumption, while agriculture can predict economic growth. These outcomes have far-reaching significance for economic growth and the selected variables in Indonesia. [ABSTRACT FROM AUTHOR]

This paper aims to investigate coal consumption and environmental sustainability in South Africa by examining the role of financial development and globalization by using a dataset covering the period from 1980 to 2017. The study utilized the Auto-regressive Distributed Lag Model (ARDL) approach in addition to the Bayer and Hank combined co-integration, fully modified Ordinary least squares (FMOLS), and Dynamic ordinary least Squares (DOLS). The study further utilized the frequency domain causality test to capture the causal linkage between the series. The advantage of the frequency domain causality is that it can capture causal linkages between series at different periods. The Bayer and Hanck co-integration and ARDL bounds tests reveal co-integration among the series. The empirical findings based on the ARDL long-run estimation reveal that a 1% increase in coal consumption increases environmental degradation by 1.077%, while a 1% increase in financial development decreases the environmental degradation by 0.973%. Furthermore, a 1% increase in economic growth decreases environmental quality by 1.449%. The outcomes of the FMOLS and DOLS approaches also provide supportive evidence for the ARDL long-run results. Furthermore, the results of the frequency domain causality test reveal that at a significance level of 1%, coal consumption Granger causes CO2 emissions at different frequencies, while financial development Granger causes CO2 emissions in the long run and short run at a significance level of 10%. In terms of policy suggestions, South Africa should embrace policies that encourage energy consumers to shift toward renewable energy. Furthermore, financial reforms should be implemented to curb environmental degradation. [ABSTRACT FROM AUTHOR]

Following the United Nations Sustainable Development Goals (UN-SDGs), which place emphasis on relevant concerns that encompass access to energy (SDG-7) and sustainable development (SDG-8), this research intends to re-examine the relationship between urbanization, CO2 emissions, gross capital formation, energy use, and economic growth in South Korea, which has not yet been assessed using recent econometric techniques, based on data covering the period between 1965 and 2019. The present study utilized the autoregressive distributed lag (ARDL), dynamic ordinary least square (DOLS), and fully modified ordinary least squares (FMOLS) methods, while the gradual shift and wavelet coherence techniques are utilized to determine the direction of the causality. The ARDL bounds test reveals a long-run linkage between the variables of interest. Empirical evidence shows that CO2 emissions trigger economic growth. Thus, based on increasing environmental awareness across the globe, it is necessary to change the energy mix in South Korea to renewables to enable the use of sustainable energy sources and establish an environmentally sustainable ecosystem. Moreover, the energy-induced growth hypothesis is validated. This result is supported by the causality analysis, which shows a one-way causality running from energy consumption to GDP in South Korea. This suggests that South Korea cannot embark on conservative energy policies, as such actions will damage economic progress. Additionally, a unidirectional causality is seen from CO2 emissions and energy consumption to economic growth. These findings have far-reaching consequences for GDP growth and macroeconomic indicators in South Korea. [ABSTRACT FROM AUTHOR]

The present study aims to explore the long‐run and causal effect of financial development and renewable energy consumption on environmental sustainability while controlling technological innovation and economic growth within the global framework. In line with the aim of the study, the fully modified OLS (FMOLS), dynamic OLS (DOLS), canonical cointegrating regression (CCR), Bayer and Hanck cointegration, and frequency‐domain causality tests are employed. Empirical evidence confirms the existence of a long‐run linkage among the variables. The present study also finds that in the long run, global financial development and global renewable energy consumption have a long‐run significant positive effect on environmental sustainability, while economic growth increases carbon emission flaring around the world. Within the global framework, the study, therefore, recommends that in order to increase environmental quality, global policy‐makers should further consider the roles of renewable energy and financial development by implementing reform energy policies in both developed and developing countries. [ABSTRACT FROM AUTHOR]

This study aims to investigate the relationship between CO2 emissions in China and its prospective determinants, namely economic growth, globalization, financial development, and natural resources during the period from 1980 to 2017. We present more detailed analyses across multiple econometric approaches within a multivariate system, e.g., the Bayer‐Hanck combined cointegration approach, the ARDL bounds test approach, ARDL estimates in short run and long run, robustness check by cointegration regressions (i.e., FMOLS, DOLS, CCR), and Granger causality approach in the frequency domain. Our results show that economic growth and natural resources have a positive impact on CO2 emissions in China, although globalization contributes to improving its environmental quality. Meanwhile, there is no statistical evidence that CO2 emissions in China could be affected by financial development. The causality analysis reveals that globalization, economic growth and natural resources all lead to CO2 emissions in the long run, while financial development only causes the short‐run CO2 emissions, which further demonstrate our findings. Such findings are meaningful for policymakers to achieve the sustainable development in China. [ABSTRACT FROM AUTHOR]

This novel research looked into the role of public-private partnership investment in energy in affecting Pakistan's long-term environmental sustainability. Employing time series data from 1992 to 2018 and utilizing the autoregressive distributive lag model (ARDL) model, we found a long-term equilibrium association of ecological footprint with public-private partnership investment in energy, technological innovation, economic growth, and trade openness. Our outcomes showed a significant positive association between public-private partnership investment in energy and ecological footprint in the long-run and the short-run, specifying that the increase in public-private partnership investment in energy affects the environmental sustainability of Pakistan. Similarly, our study confirmed that technological innovation, economic growth, and trade openness increase the ecological footprint in Pakistan. It demonstrates that these factors are unfavorable to the sustainable environment in Pakistan. Furthermore, robustness check findings are analogous to the results of ARDL estimates, utilizing dynamic ordinary least squares and fully modified ordinary least squares. On the basis of the research conclusions, a multi-pronged sustainable development goal (SDG) model was proposed that addresses SDG 8 and SDG 13 while incorporating SDG 17 as a medium. [ABSTRACT FROM AUTHOR]

This empirical study assesses the effect of CO2 emissions, urbanization, energy consumption, and agriculture on Thailand's economic growth using a dataset between 1970 and 2018. The ARDL and the frequency domain causality (FDC) approaches were applied to assess these interconnections. The outcome of the bounds test suggested a long-term association among the variables of investigation. The ARDL outcomes reveal that urbanization, agriculture, energy consumption, and CO2 emissions positively trigger Thailand's economic growth. Additionally, the frequency domain causality test was used to detect a causal connection between the series. The main benefit of this technique is that it can detect a causal connection between series at different frequencies. To the understanding of the authors, this is the first study in the case of Thailand that will apply the FDC approach to capture the causal linkage between GDP and the regressors. The outcomes of the causality test suggested that CO2 emissions, urbanization, energy consumption, and agriculture can predict Thailand's economic growth in the long term. These outcomes have far-reaching implications for economic performance and Thailand's macroeconomic indicators. [ABSTRACT FROM AUTHOR]

It is widely accepted that CO2 emissions are the primary cause of climate change and environmental destruction. China, the world's biggest carbon emitter, is the subject of this research. Utilizing the wavelet tools (wavelet correlation, wavelet coherence, multiple wavelet coherence, and partial wavelet coherence), the present study intends to capture the time-frequency dependence between CO2 emissions and renewable energy, economic growth, trade openness, and energy usage in China between 1965 and 2019. The advantage of the wavelet tools is that they can differentiate between short, medium, and long-run dynamics over the period of study. Furthermore, the study utilized the gradual shift causality test to capture the causal interconnection between CO2 emissions and the regressors. The findings from Bayer and Hanck showed a long-run relationship among the variables of interest. Furthermore, the findings from the wavelet coherence test revealed a positive relationship between CO2 emissions and economic growth and energy usage at all frequencies. Although there is a weak negative relationship between renewable energy and CO2 emissions in the short run, there is no significant co-movement between CO2 emissions and trade openness. The outcomes of the partial and multiple wavelet coherence also give credence to the outcomes of the wavelet coherence test. Lastly, the gradual shift causality test revealed a one-way causality from energy usage and economic growth to CO2 emissions. Based on the findings, suitable policy suggestions were proposed. [ABSTRACT FROM AUTHOR]

This paper assesses the linkage between CO2 emissions and economic growth while taking into account the role of energy consumption, agriculture, and trade openness in India. Using data covering the period between 1965 and 2019, the Bayer and Hanck cointegration and Gradual shift causality tests are applied to assess these economic indicators relationships'. Furthermore, we employed the wavelet coherence test. The advantage of the wavelet coherence test is that it differentiates between short-, medium-, and long-run dynamics over the entire sampling period. To the best of the authors' understanding, the present paper is the first to apply wavelet analysis to investigate this relationship by incorporating agriculture as a determinant of environmental degradation. The empirical outcomes show that all variables appear to be highly correlated with CO2 emissions with the exemption of trade openness. This is further affirmed by the Gradual shift causality test, which shows that agriculture and energy consumption are crucial determinants of CO2 emissions in India. Accordingly, adequate policy measures are proposed based on these findings. [ABSTRACT FROM AUTHOR]

Environmental sustainability is an important issue for current scholars and policymakers in the East Asian and Pacific region. The causal and long-run effects of technological innovation, public–private partnership investment in energy, and renewable energy consumption on environmental sustainability in the East Asian and Pacific regions have not been comprehensively explored while taking into account the role of economic growth using quarterly data for the period 1992–2015. Therefore, the present study aims to close this literature gap using econometric approaches, namely Bayer–Hanck cointegration, autoregressive distributed lag (ARDL), dynamic ordinary least square (DOLS), and fully modified ordinary least square (FMOLS) tests. Furthermore, the study utilizes the frequency domain causality test to capture the causal impact of public–private partnership investment in energy, renewable energy consumption, technological innovation, and economic growth on CO2 emissions. The advantage of the frequency domain causality test is that it can capture the causality between short-term, medium-term, and long-term variables. The outcomes of the ARDL, FMOLS and DOLS show that renewable energy consumption and technological innovation mitigate CO2 emissions, while public–private partnership investment in energy and economic growth increase CO2 emissions. Moreover, the frequency causality test outcomes reveal that technological innovation, public–private partnership investment in energy, and renewable energy consumption cause CO2 emissions, particularly in the long-term. Thus, as a policy recommendation, the present study recommends promoting renewable energy consumption by focusing more on technological innovation in the East Asia and Pacific regions. [ABSTRACT FROM AUTHOR]

The present study aims to shed some light on the causal link between the Service Sector Index in the Turkish stock market and economic growth using a wavelet coherence approach. Thus, the present study determines whether the Service Sector Index leads to economic growth in Turkey and/or vice versa. Based on our aim, we use the wavelet coherence approach, which allows us to capture long-run and short-run causal linkages between the Service Sector Index and economic growth in Turkey, since the approach combines both time domain causality and frequency domain causality tests. The findings from wavelet coherence reveal that there is one-way causality running from the Service Sector Index to economic growth in Turkey at different frequencies and different periods between 1997 and 2017. [ABSTRACT FROM AUTHOR]