Promoting Environmental Sustainability: The Role of Renewable Energy Systems and Environmental Taxes

Abstract

This study examines the effects of renewable energy consumption and environmental taxes on CO₂ emissions in OECD countries from 1990 to 2022, employing the cross-sectional autoregressive distributed lag (CS-ARDL) approach. The findings reveal that both renewable energy consumption and environmental taxes significantly reduce CO₂ emissions in both the short and the long term, emphasizing their crucial roles in climate change mitigation and sustainability promotion. Furthermore, this study identifies that industrialization and urbanization contribute to increased emissions, whereas foreign direct investment aids in emission reduction through the facilitation of green technology transfer. Economic growth is initially associated with higher emissions, but this trend reverses as economies mature and adopt sustainable practices. These results highlight the importance of continuous investment in renewable energy infrastructure and the implementation of robust environmental tax policies to achieve long-term sustainability goals. The integration of environmental considerations into economic and urban planning, along with leveraging foreign direct investment for technological advancements, is imperative for balancing economic growth with the necessity to reduce carbon emissions and effectively address climate change. This research provides a better understanding of the diverse factors influencing CO₂ emissions and offers critical insights for policymakers.

1. Introduction

Environmental sustainability has become a critical focus for policymakers, especially in OECD countries, where the shift from fossil fuels to renewable energy sources is imperative. The pressing need to address climate change, alongside the finite nature of non-renewable resources and escalating global energy demands, necessitates the development of comprehensive strategies to curtail CO₂ emissions. To meet this challenge, nation states and international organizations have implemented a broad array of measures, ranging from regulatory frameworks to financial incentives. Among these, renewable energy systems and environmental tax policies have emerged as pivotal instruments. Research by Saidi and Omri [1], Raihan et al. [2], and Zafar et al. [3] underscores the dual advantages of renewable energy in fostering economic growth, while simultaneously reducing carbon footprints. These studies reinforce the strategic significance of renewable energy adoption and fiscal measures in achieving long-term sustainability objectives. Environmental protection taxes, such as carbon taxes, are key tools in this effort, creating economic disincentives for high-carbon activities. However, these are not the only financial instruments in play; subsidies for renewable energy projects, feed-in tariffs, and carbon trading schemes have also been widely adopted to incentivize the transition to low-carbon technologies. International agreements, such as the Paris Agreement, further exemplify the global commitment to reducing greenhouse gas emissions, fostering collaboration among nations to achieve shared environmental goals. The transition to renewable energy not only mitigates environmental degradation but also stimulates economic development through job creation and technological innovation. This dual benefit is particularly pertinent for OECD countries, which are at the forefront of implementing stringent environmental regulations and advancing green technologies. The efficacy of environmental tax policies further complements these efforts by providing financial incentives for reducing emissions and promoting cleaner production practices. This study builds upon these efforts by examining the specific impacts of renewable energy consumption and environmental taxes on CO₂ emissions within OECD countries. By focusing on these two critical factors, the research aims to contribute to the broader discourse on how financial and policy tools can be optimized to achieve environmental sustainability. This integrated approach aligns with global sustainability goals and enhances the resilience of economies against the adverse effects of climate change. The growing body of empirical evidence highlights the necessity for OECD countries to adopt and expand renewable energy infrastructure and robust environmental tax frameworks, thereby ensuring a sustainable and economically viable future.

The critical importance of policy interventions is further supported by the environmental Kuznets curve hypothesis, which posits that economic development initially exacerbates environmental degradation but ultimately leads to environmental improvement as economies mature and adopt cleaner technologies. Empirical evidence from OECD countries, as documented by researchers such as Chen et al. [4], Wolde-Rufael and Mulat-Weldemeskel [5], and Aydin and Bozatli [6], demonstrates that well-designed environmental taxes can significantly reduce CO₂ emissions. These studies highlight the effectiveness of fiscal policies in creating economic incentives for emission reductions and promoting sustainable practices across various sectors. Additionally, the integration of foreign direct investment plays a crucial role in facilitating the transfer of green technologies, thereby contributing to emission reduction efforts. Foreign direct investment not only brings capital but also introduces advanced technologies and sustainable practices that can help host countries achieve their environmental goals. This study aims to provide a comprehensive analysis of the multifaceted influences on CO₂ emissions, with a particular focus on renewable energy consumption and environmental taxes. By examining these factors within the OECD context, the research seeks to enhance the understanding of how these variables interact and impact CO₂ emissions. The findings are expected to inform policymakers on the most effective strategies for integrating renewable energy and environmental taxes to achieve significant and sustained reductions in carbon emissions.

Therefore, this study aims to conduct a comprehensive examination of the impact of renewable energy consumption and environmental taxes on CO₂ emissions in OECD countries from 1990 to 2022. Utilizing the cross-sectional autoregressive distributed lag approach, this research endeavors to capture the intricate short-term and long-term dynamics of these relationships. By incorporating control variables such as industrialization, urbanization, foreign direct investment, and economic growth, this study provides a nuanced analysis of the multifaceted factors influencing CO₂ emissions. The primary objective is to elucidate the pivotal roles of renewable energy and environmental taxes in mitigating climate change and fostering environmental sustainability. This analysis aims to inform policymakers on devising effective strategies that reconcile economic growth, with the imperative to reduce carbon emissions. This research is poised to contribute significant insights to the policy discourse on sustainable development within the OECD framework, aligning with the thematic emphasis on promoting environmental sustainability through the integration of renewable energy systems and fiscal measures. By offering a detailed understanding of these dynamics, this study seeks to support the formulation of policies that ensure long-term sustainability and environmental resilience.

Based on the comprehensive analysis presented in this study, several novel contributions significantly enhance the understanding of the impact of renewable energy consumption and environmental taxes on CO₂ emissions in OECD countries. Firstly, this study reveals that renewable energy consumption markedly reduces CO₂ emissions in both the short and the long term. This finding advances the work of Padhan et al. [7] and Nan et al. [8], who primarily demonstrated long-term effects without extensively covering immediate impacts. This research underscores the dual benefits of renewable energy policies, highlighting their efficacy in achieving both rapid and sustained reductions in emissions. Secondly, this study offers a detailed analysis of environmental taxes, demonstrating their substantial role in emission reduction across various time horizons. This extends the findings of Albulescu et al. [9] and Hussain et al. [10], who focused predominantly on long-term effects, by illustrating that environmental taxes are equally critical in the short term. This emphasizes the necessity of immediate policy interventions alongside long-term strategies to effectively mitigate emissions. Finally, this research uniquely integrates the effects of foreign direct investment on CO₂ emissions, showing a significant negative relationship that facilitates green technology transfer. This finding builds on the insights of Alshubiri and Elheddad [11] and Ganda [12], who explored the broader economic impacts of foreign direct investment but did not specifically link it to environmental outcomes. By emphasizing foreign direct investment’s role in promoting cleaner industrial practices, this study provides a more comprehensive view of how international investments can drive environmental sustainability. These contributions not only deepen the existing knowledge base but also offer practical insights for policymakers. They make a compelling case for the strategic integration of renewable energy, environmental taxes, and foreign direct investment to achieve sustainable development goals in OECD countries, thereby aligning with the overarching objective of fostering environmental sustainability.

2. Literature Review

Renewable energy has been widely recognized as a critical strategy for reducing CO₂ emissions and mitigating climate change. Studies by Taşkın et al. [13], Dogru et al. [14], and Cao et al. [15] underscore that renewable energy not only lowers carbon emissions but also fosters economic growth. These studies highlight the dual benefits of renewable energy, particularly within the context of OECD countries, where technological advancements and economic structures facilitate the transition to cleaner energy sources. Dong et al. [16] and Li and Haneklaus [17] argue that increased renewable energy consumption results in significant reductions in CO₂ emissions, a finding corroborated by more recent research by Jebli et al. [18], Yu et al. [19], and Kirikkaleli et al. [20]. This body of research consistently confirms that renewable energy is essential for achieving environmental sustainability, suggesting that renewable energy policies should be a priority for OECD countries aiming to reduce their carbon footprint while promoting economic growth. The adoption of renewable energy technologies is influenced by various factors, including government policies, market conditions, and technological advancements. Research by Cantarero [21], Lu et al. [22], and Qadir et al. [23] indicates that supportive policies and financial incentives play a critical role in accelerating the deployment of renewable energy systems. These studies underscore the importance of policy interventions in overcoming barriers to renewable energy adoption, such as high initial costs and market uncertainties. Integrating renewable energy into the energy mix requires substantial investments in infrastructure and technology, as well as coordinated efforts across different sectors of the economy. This holistic approach is necessary to maximize the environmental and economic benefits of renewable energy.

Environmental taxes are recognized as an effective mechanism for reducing CO₂ emissions by creating financial incentives to decrease carbon output. Research by Karmaker et al. [24], Wang and Yu [25], and Bashir et al. [26] demonstrates that well-designed environmental taxes can significantly lower emissions by encouraging businesses and individuals to adopt cleaner technologies and practices. These studies illustrate that environmental taxes not only reduce emissions but also generate revenue that can be reinvested in sustainable projects, thereby creating a positive feedback loop for environmental improvement. The efficacy of environmental taxes is heavily dependent on their design and implementation, as highlighted by Ahmed [27], Yirong [28], and Dogan et al. [29], who found that stringent environmental tax policies are more successful in achieving substantial emission reductions. The dynamic relationship between environmental taxes and CO₂ emissions is further examined in studies by Al Shammre et al. [30], Shafi et al. [31], and Saqib et al. [32]. These researchers emphasize the importance of regular adjustments to tax rates to sustain their effectiveness over time. They also underscore the role of complementary policies, such as subsidies for renewable energy and investments in green infrastructure, in enhancing the overall impact of environmental taxes. By addressing both the demand and supply sides of the energy market, environmental taxes can drive a comprehensive transition to a low-carbon economy. This holistic approach ensures that the benefits of environmental taxes are maximized, promoting long-term environmental sustainability.

Understanding the impact of renewable energy and environmental taxes on CO₂ emissions necessitates the consideration of other influential factors, such as industrialization, urbanization, foreign direct investment, and economic growth. Studies by Liu et al. [33], Rehman et al. [34], and Raihan [35] indicate that industrialization and urbanization are associated with increased emissions due to higher energy consumption and transportation needs. These findings align with the broader literature, which suggests that economic development often leads to elevated emissions in the absence of stringent environmental regulations. However, research by Yu et al. [36], Shah et al. [31], and Yang et al. [37] emphasizes that advanced stages of industrialization, characterized by cleaner technologies and more efficient processes, can mitigate these adverse environmental impacts. The role of foreign direct investment in reducing CO₂ emissions is explored in studies by Khan et al. [38], Chien et al. [39], and Lee et al. [40]. These researchers argue that foreign direct investment can facilitate the transfer of green technologies and promote sustainable industrial practices. This positive impact of foreign direct investment on environmental sustainability is particularly relevant for OECD countries, which frequently receive substantial foreign investments. By creating favorable conditions for green investments, policymakers can leverage foreign direct investment to achieve their environmental goals. Finally, the relationship between economic growth and CO₂ emissions is examined within the framework of the environmental Kuznets curve hypothesis. Studies by Begum et al. [41], Nair et al. [42], and Amara and Qiao [43] suggest that while emissions initially increase with economic growth, they eventually decline as economies mature and adopt more sustainable practices. This implies that achieving sustainable development requires integrating environmental considerations into economic planning and leveraging technological advancements to decouple economic growth from carbon emissions.

In conclusion, this literature review underscores the critical importance of renewable energy and environmental taxes in mitigating CO₂ emissions within OECD countries. While significant progress has been made, the review also reveals a gap in the comprehensive understanding of how these factors interact with other influential variables, such as industrialization, urbanization, foreign direct investment, and economic growth, in determining emissions levels. This study addresses this gap by formulating the research problem as follows: what are the dynamic interactions between renewable energy consumption, environmental taxes, and other socioeconomic factors in influencing CO₂ emissions across OECD countries? To answer this question, this study employs the CS-ARDL approach, which allows for a better analysis of both short-term and long-term effects. The findings are expected to inform the development of more effective policy strategies aimed at achieving environmental sustainability and economic growth in tandem. Based on the literature review and research objectives, the following hypotheses are proposed:

Hypothesis 1 (H₁). 

Renewable energy consumption has a significant negative impact on CO₂ emissions in OECD countries.

Hypothesis 2 (H₂). 

Environmental taxes are effective in reducing CO₂ emissions in OECD countries.

Hypothesis 3 (H₃). 

The relationship between renewable energy consumption and CO₂ emissions varies between the short term and the long term.

Hypothesis 4 (H₄). 

The effectiveness of environmental taxes on CO₂ emission reduction is more pronounced in the long term compared to the short term.

3. Research Methodology

3.1. Variables

The dependent variable is environmental sustainability, which is increasingly a priority for policymakers, particularly in OECD countries, where the transition to renewable energy systems and the implementation of environmental taxes are becoming more prevalent. Among the various indicators of environmental sustainability, CO₂ emissions stand out as a crucial measure, directly reflecting a nation’s environmental and economic well-being. The significance of CO₂ emissions as a representative indicator in OECD countries is reinforced by several key theoretical and empirical studies. Firstly, the environmental Kuznets curve hypothesis offers a fundamental framework, proposing that as an economy develops, environmental degradation initially increases and then decreases, forming an inverted U-shape. This hypothesis implies that OECD countries, being at more advanced stages of development, are well-positioned to reduce CO₂ emissions through effective policies and technological advancements in renewable energy systems (Mahmood et al., [44]; Lau et al., [45]; Ullah et al., [46]). Secondly, empirical research underscores the effectiveness of renewable energy adoption in reducing CO₂ emissions. Studies by Perone [47] and Ferhi and Kamel [48] explore the relationship between renewable energy consumption and economic growth in OECD countries. Their findings indicate that the increased use of renewable energy sources significantly mitigates CO₂ emissions without compromising economic performance, highlighting the dual benefits of renewable energy systems in promoting both environmental sustainability and economic growth. Thirdly, the impact of environmental taxes on reducing CO₂ emissions is well-documented. Research conducted by Ghazouani et al. [49] and Noubissi et al. [50] examines the effect of carbon taxes on CO₂ emissions in European OECD countries. Their studies demonstrate that appropriately designed fiscal measures are effective in incentivizing reductions in carbon output and promoting a shift to cleaner energy sources. These findings suggest that environmental taxes can serve as powerful tools for reducing CO₂ emissions and advancing environmental sustainability. In summary, these theoretical and empirical insights affirm the critical role of CO₂ emissions as a key indicator of environmental sustainability in OECD countries. The integration of renewable energy systems and environmental taxes represents a comprehensive strategy for addressing climate change, reducing carbon footprints, and ensuring long-term sustainable development. Consequently, CO₂ emissions are utilized as a dependent variable in this study to assess environmental sustainability.

The independent variable is the influence of renewable energy and environmental taxes on CO₂ emissions in OECD countries, which is a pivotal topic in environmental economics. The environmental Kuznets curve hypothesis serves as a theoretical basis, suggesting that while economic development initially exacerbates environmental degradation, it ultimately fosters improvement as economies advance and embrace cleaner technologies. Empirical evidence substantiates this hypothesis, demonstrating the critical role of renewable energy and environmental taxes in curbing CO₂ emissions. Research conducted by Saidi and Omri [51] and Mohammed Idris et al. [52] reveals a significant inverse relationship between renewable energy consumption and CO₂ emissions in OECD countries. These studies highlight that the adoption of renewable energy not only reduces emissions but also bolsters economic growth, thus facilitating sustainable development. In parallel, investigations by Köppl and Schratzenstaller [53] and Nadiri et al. [54] focus on the impact of carbon taxes on CO₂ emissions in European OECD countries. Their findings indicate that carbon taxes effectively incentivize reductions in carbon emissions and promote a shift towards renewable energy sources. These results underscore the potential of well-structured environmental taxes to significantly mitigate CO₂ emissions. Together, these studies underscore the indispensable role of renewable energy adoption and environmental taxes in reducing CO₂ emissions within OECD countries. They confirm the importance of these measures in achieving environmental sustainability and addressing climate change. In this study, both renewable energy and environmental taxes are employed as independent variables to analyze their impact on CO₂ emissions.

The control variables: in examining CO₂ emissions in OECD countries, the inclusion of control variables such as green finance, industrialization, foreign direct investment, urbanization, and economic growth is imperative for an accurate analysis. Methodologically, controlling for these variables enhances the robustness and reliability of the analysis, mitigating omitted variable bias and improving the precision of estimations. Green finance, as elucidated by Umar and Safi [55] and Jin et al. [56], significantly contributes to reducing CO₂ emissions by directing investments towards sustainable projects and advanced technologies. Industrialization, though historically linked to increased emissions, reveals a more complex relationship. Mentel et al. [57], Dehdar et al. [58], and Ghazouani [59] indicate that advanced industrialization stages in OECD countries often incorporate cleaner technologies and more efficient processes, potentially reducing emissions. Foreign direct investment presents mixed effects on CO₂ emissions. Studies by Xie et al. [60], Christoforidis and Katrakilidis [61], and Apergis et al. [62] suggest that while industrial expansion can elevate emissions, it also facilitates the transfer of green technologies that can mitigate these emissions. Urbanization, as analyzed by Amin et al. [63] and Gierałtowska et al. [64], typically leads to higher emissions due to increased energy consumption and transportation needs, though efficient urban planning can mitigate some of these impacts. Economic growth, examined within the framework of the environmental Kuznets curve by Ridzuan et al. [65] and Boukhelkhal [66], initially drives CO₂ emissions upward but eventually promotes reductions as economies advance and prioritize environmental sustainability. In summary, these control variables are vital for a comprehensive econometric analysis as they encompass a broad spectrum of factors influencing CO₂ emissions. Their inclusion provides a more nuanced understanding of the efficacy of renewable energy and environmental taxes in reducing emissions within OECD countries. Thus, they are employed as control variables in this study to enhance the analytical rigor. To provide a clearer understanding of the variables used in this study, the basic information of these variables is detailed in

Table 1. Results of variable description.

Variable	Form	Definition
Carbon dioxide emissions	ca	CO2 emissions (kt) in log
Renewable energy	re	Renewable energy consumption (% of total final energy consumption)
Environmental tax	en	Environmental taxes are environmentally related tax revenues (% of GDP)
Green finance	gr	Proportion of green credit extended to the private sector as a percentage of GDP
Industrialization	in	Proportion of industrial value added as a percentage of GDP
Foreign direct investment	$\mathrm{f}\mathrm{d}\mathrm{i}$	Foreign direct investment, net inflows (% of GDP)
Urbanization	$\mathrm{u}\mathrm{r}$	Proportion of the total population residing in urban areas
Economic growth	$\mathrm{e}\mathrm{c}$	GDP (constant 2015 USD; unit: billion USD) in log

Note: The data utilized in this study are sourced from the World Bank and OECD data.

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3.2. Model

This study explores the impact of renewable energy and environmental taxes on CO₂ emissions in OECD countries over the period from 1990 to 2022. To provide a comprehensive understanding of the practices across these countries, the analysis delves into various environmental taxes, such as carbon and energy taxes, highlighting differences in their scope, application, and effectiveness. Additionally, this study examines country-specific practices, particularly focusing on regions such as the Nordic countries, which have pioneered progressive environmental tax policies. The modeling framework, grounded in well-established theories of environmental economics and supported by empirical research, benefits from these detailed insights. For instance, Neves et al. [67], Rafique et al. [68], and Zhu et al. [69] underscore the pivotal role of policy interventions in mitigating carbon emissions, particularly emphasizing the efficacy of environmental taxes as tools for emission reduction. In parallel, the analysis covers predominant renewable energy technologies—such as solar, wind, hydro, and biomass—examining how different countries have adopted these technologies based on their unique resources and policy frameworks. Research by Jahanger et al. [70], Mirzapour et al. [71], and Ali and Meo [72] demonstrates that the adoption of these renewable energy sources substantially decreases CO₂ emissions without impeding economic growth. Finally, a comparative analysis identifies patterns and lessons across countries, offering insights into the practical implementation of these measures and their implications for environmental sustainability. The convergence of these insights from policy impact studies and renewable energy research informs the construction of the econometric model detailed in Equation (1):

$${\mathrm{c}\mathrm{a}}_{\mathrm{i},\mathrm{t}}={\mathrm{a}}_0+{\mathrm{a}}_1{\mathrm{r}\mathrm{e}}_{\mathrm{i},\mathrm{t}}+{\mathrm{a}}_2{\mathrm{e}\mathrm{n}}_{\mathrm{i},\mathrm{t}}+{\mathrm{a}}_3{\mathrm{g}\mathrm{r}}_{\mathrm{i},\mathrm{t}}+{\mathrm{a}}_4{\mathrm{i}\mathrm{n}}_{\mathrm{i},\mathrm{t}}+{\mathrm{a}}_5{\mathrm{f}\mathrm{d}\mathrm{i}}_{\mathrm{i},\mathrm{t}}+{\mathrm{a}}_6{\mathrm{u}\mathrm{r}}_{\mathrm{i},\mathrm{t}}+{\mathrm{a}}_7{\mathrm{e}\mathrm{c}}_{\mathrm{i},\mathrm{t}}+{\mathsf{ϵ}}_{\mathrm{i},\mathrm{t}}.$$

(1)

In Equation (1), i denotes the country, while t represents the year. The term ${\mathrm{a}}_0$ signifies the constant or intercept of the model. The coefficients to be estimated are denoted by $[{\mathrm{a}}_1,{\mathrm{a}}_7]$, which quantify the relationship between the dependent and independent variables in the analysis. The error term, represented by $\mathsf{ϵ}$, captures the white noise, accounting for random variations and ensuring the robustness of the model. These components collectively facilitate a rigorous examination of the factors affecting CO₂ emissions across different OECD countries over the specified period. To evaluate the dataset, descriptive statistics and correlation analyses are initially conducted. This preliminary step is crucial for assessing data normality and determining the strengths and weaknesses of the relationships among variables. Additionally, the presence of cross-sectional dependency was examined using the cross-sectional dependence test, which is particularly suitable for cross-sectional data. Addressing cross-sectional dependency is essential to ensuring the validity and reliability of the econometric model. The cross-sectional dependence test equation is presented in Equation (2):

$${\mathrm{c}\mathrm{s}\mathrm{d}}_{\mathrm{i},\mathrm{t}}=\sqrt{{\displaystyle \frac{\mathrm{i}\mathrm{t}(\mathrm{t}-1)}{2}}}\widetilde{{\mathsf{\rho }}_{\mathrm{t}}}.$$

(2)

In Equation (2), $\tilde{\mathsf{\rho }}$ denotes the pairwise correlation coefficient, $\mathrm{t}$ indicates the time dimension, and $\mathrm{i}$ represents the cross-sectional units. Furthermore, the researchers employed the cross-sectionally augmented Im–Pesaran–Shin unit root test to assess the stationarity of the variables. Conducting the cross-sectionally augmented Im–Pesaran–Shin test is critical, as it ensures the suitability of the variables for subsequent econometric modeling. The cross-sectionally augmented Im–Pesaran–Shin test, which accounts for cross-sectional dependence, enhances the robustness of the analysis by verifying that the data do not contain unit roots. The mathematical formulation of the cross-sectionally augmented Im–Pesaran–Shin test is provided in Equation (3):

$$\Delta {\mathrm{w}}_{\mathrm{i},\mathrm{t}}={\mathrm{b}}_{\mathrm{i}}+{\mathrm{b}}_{\mathrm{i}}{\mathrm{z}}_{\mathrm{i},\mathrm{t}-1}+{\mathrm{b}}_{\mathrm{i}}\widetilde{{\mathrm{z}}_{\mathrm{t}-1}}+{\sum }_{\mathrm{j}=0}^{\mathrm{n}}{\mathrm{b}}_{\mathrm{i}\mathrm{j}}\Delta \widetilde{{\mathrm{w}}_{\mathrm{t}-1}}+{\sum }_{\mathrm{j}=0}^{\mathrm{n}}{\mathrm{b}}_{\mathrm{i}\mathrm{j}}\Delta {\mathrm{w}}_{\mathrm{i},\mathrm{t}-1}+{\mathsf{ϵ}}_{\mathrm{i},\mathrm{t}}.$$

(3)

In Equation (3), $\tilde{\mathrm{w}}$ represents the average value across the cross-sectional units. This parameter is integral to the analysis, as it provides a measure of the central tendency within the cross-sectional data, allowing for a more comprehensive understanding of the dataset’s overall characteristics.

$${\mathrm{w}}_{ı,\mathrm{t}}={\mathrm{b}}_1\widetilde{{\mathrm{c}\mathrm{a}}_{ı,\mathrm{t}}}+{\mathrm{b}}_2\widetilde{{\mathrm{r}\mathrm{e}}_{ı,\mathrm{t}}}+{\mathrm{b}}_3\widetilde{{\mathrm{e}\mathrm{n}}_{ı,\mathrm{t}}}+{\mathrm{b}}_4\widetilde{{\mathrm{g}\mathrm{r}}_{ı,\mathrm{t}}}+{\mathrm{b}}_5\widetilde{{ı\mathrm{n}}_{ı,\mathrm{t}}}+{\mathrm{b}}_6\widetilde{{\mathrm{f}\mathrm{d}ı}_{ı,\mathrm{t}}}+{\mathrm{b}}_7\widetilde{{\mathrm{u}\mathrm{r}}_{ı,\mathrm{t}}}+{\mathrm{b}}_8\widetilde{{\mathrm{e}\mathrm{c}}_{ı,\mathrm{t}}}.$$

(4)

Consequently, the cross-sectionally augmented Im–Pesaran–Shin test is formulated as shown in Equation (4), where CADF denotes the cross-sectionally augmented Dickey–Fuller test. Additionally, previous studies have implemented the Westerlund and Edgerton [73] cointegration test to assess cointegration. This step is essential for selecting the appropriate econometric model. The Westerlund and Edgerton test is particularly advantageous due to its robust handling of cross-sectional dependence and its ability to accommodate structural breaks. Furthermore, it has the capability to examine regime shifts and distinguish between shifts and no-shift breaks within the structure. The test equation is presented in Equation (5):

$$\mathrm{l}\mathrm{l}\mathrm{o}\mathrm{g}(\mathrm{L})={\mathrm{c}}_0-{\displaystyle \frac{{\sum }_{\mathrm{i}=1}^{\mathrm{n}}\left[\mathrm{t}\mathrm{l}\mathrm{o}\mathrm{g}\right({\mathsf{\sigma }}_{\mathrm{i},\mathrm{t}}^2)}{2}}-{\displaystyle \frac{{\sum }_{\mathrm{t}=1}^{\mathrm{t}}{\mathsf{ϵ}}_{\mathrm{i},\mathrm{t}}^2}{{\mathsf{\sigma }}_{\mathrm{i},\mathrm{t}}^2}}.$$

(5)

Previous studies have also utilized the cross-sectional autoregressive distributed lag approach to examine the relationships among the variables under investigation. This method is advantageous due to its ability to address endogeneity, cross-sectional dependence, and slope heterogeneity. While the autoregressive distributed lag approach is widely employed for panel data analysis, it fails to adequately account for cross-sectional dependence errors. The cross-sectional autoregressive distributed lag method, developed by Chudik and Pesaran [74], effectively addresses these issues and is particularly well-suited for handling cross-sectional dependence. It is based on stringent assumptions that enhance its robustness and reliability. The mathematical formulation of the cross-sectional autoregressive distributed lag approach is presented in Equation (6):

$$\Delta {\mathrm{y}}_{\mathrm{i},\mathrm{t}}={\mathrm{c}}_{\mathrm{i}}+{\sum }_{\mathrm{j}=1}^{\mathrm{n}}{\mathrm{c}}_{\mathrm{i}\mathrm{j}}\Delta {\mathrm{y}}_{\mathrm{i},\mathrm{t}-1}+{\sum }_{\mathrm{j}=0}^{\mathrm{n}}{\mathrm{c}}_{\mathrm{i}\mathrm{j}}^{~}{\mathrm{e}\mathrm{x}\mathrm{v}}_{\mathrm{s}\mathrm{i},\mathrm{i},\mathrm{t}}+{\sum }_{\mathrm{j}=0}^{\mathrm{n}}{\mathrm{c}}_{\mathrm{i}\mathrm{j}}^{~}\widetilde{{\mathrm{c}\mathrm{s}\mathrm{a}}_{ı,\mathrm{t}-1}}+{\mathsf{ϵ}}_{\mathrm{i},\mathrm{t}}.$$

(6)

Consequently, previous studies have formulated the cross-sectional autoregressive distributed lag equation using the constructs under investigation. This formulation leverages the cross-sectional autoregressive distributed lag approach to capture the dynamic relationships among the variables while addressing endogeneity, cross-sectional dependence, and slope heterogeneity, as detailed in Equation (7):

$$\begin{gathered} \Delta {\mathrm{c}\mathrm{a}}_{\mathrm{i},\mathrm{t}}={\mathrm{d}}_{\mathrm{i}}+{\sum }_{\mathrm{j}=1}^{\mathrm{n}}{\mathrm{d}}_{\mathrm{i},\mathrm{j}}\Delta {\mathrm{c}\mathrm{a}}_{\mathrm{i},\mathrm{t}-1}+{\sum }_{\mathrm{j}=0}^{\mathrm{n}}\widetilde{{\mathrm{d}}_{ı,ȷ}}{\mathrm{r}\mathrm{e}}_{\mathrm{s},\mathrm{i},\mathrm{t}}+{\sum }_{\mathrm{j}=0}^{\mathrm{n}}\widetilde{{\mathrm{d}}_{ı,ȷ}}\Delta {\mathrm{e}\mathrm{n}}_{\mathrm{s},\mathrm{i},\mathrm{t}}+ \\ {\sum }_{\mathrm{j}=0}^{\mathrm{n}}\widetilde{{\mathrm{d}}_{ı,ȷ}}{\mathrm{g}\mathrm{r}}_{\mathrm{s},\mathrm{i},\mathrm{t}}+{\sum }_{\mathrm{j}=0}^{\mathrm{n}}\widetilde{{\mathrm{d}}_{ı,ȷ}}{\mathrm{i}\mathrm{n}}_{\mathrm{s},\mathrm{i},\mathrm{t}}+{\sum }_{\mathrm{j}=0}^{\mathrm{n}}\widetilde{{\mathrm{d}}_{ı,ȷ}}{\mathrm{f}\mathrm{d}\mathrm{i}}_{\mathrm{s},\mathrm{i},\mathrm{t}}+{\sum }_{\mathrm{j}=0}^{\mathrm{n}}\widetilde{{\mathrm{d}}_{ı,ȷ}}{\mathrm{u}\mathrm{r}}_{\mathrm{s},\mathrm{i},\mathrm{t}}+{\sum }_{\mathrm{j}=0}^{\mathrm{n}}\widetilde{{\mathrm{d}}_{ı,ȷ}}{\mathrm{e}\mathrm{c}}_{\mathrm{s},\mathrm{i},\mathrm{t}}+ \\ {\sum }_{\mathrm{j}=0}^{\mathrm{n}}\widetilde{{\mathrm{d}}_{ı,ȷ}}\widetilde{{\mathrm{s}\mathrm{c}\mathrm{a}}_{ı,\mathrm{t}-1}}+{\mathsf{ϵ}}_{\mathrm{i},\mathrm{t}}. \end{gathered}$$

(7)

4. Results and Discussion

4.1. Basic Statistical Analysis

Performing a correlation analysis is crucial for this study, as it elucidates the relationships between the examined variables. By evaluating the correlation coefficients, the analysis reveals the strength and direction of the associations among CO₂ emissions, renewable energy consumption, environmental taxes, and control variables, including green finance, industrialization, foreign direct investment, urbanization, and economic growth. This analysis is imperative for identifying multicollinearity, which can compromise the reliability of the regression results. Furthermore, understanding these interrelationships aids in validating theoretical expectations and informs the interpretation of the econometric model’s findings. The outcomes of the correlation analysis thus provide a foundational basis for ensuring the robustness and credibility of this study’s conclusions. The detailed results are presented in

Table 2. Results of correlation test.

Variable	$\mathbf{c}\mathbf{a}$	$\mathbf{r}\mathbf{e}$	$\mathbf{e}\mathbf{n}$	$\mathbf{g}\mathbf{r}$	$\mathbf{i}\mathbf{n}$	$\mathbf{f}\mathbf{d}\mathbf{i}$	$\mathbf{u}\mathbf{r}$	$\mathbf{e}\mathbf{c}$
ca	1.000
re	−0.329 ***	1.000
en	−0.237 **	0.103	1.000
gr	−0.194 **	0.097 **	0.195	1.000
in	0.243 ***	0.159	−0.118 **	0.213 *	1.000
fdi	−0.113 *	0.303	−0.106 ***	−0.245	0.467 **	1.000
ur	0.259 ***	0.143 *	−0.094	0.187	0.231	0.106	1.000
ec	0.502 **	0.238 ***	−0.173 ***	0.432 ***	0.386 ***	0.268 **	0.211 **	1.000

Note: * 10% significance level; ** 5% significance level; *** 1% significance level.

.

The results detailed in Table 2 reveal distinct relationships between CO₂ emissions and several independent variables. Renewable energy, environmental tax, green finance, and foreign direct investment are negatively correlated with carbon dioxide emissions. Conversely, industrialization, urbanization, and economic growth exhibit a positive correlation with CO₂ emissions. These findings extend and align with existing theories and empirical research within the OECD context. The negative correlation between renewable energy and CO₂ emissions underscores the efficacy of renewable energy sources in reducing greenhouse gas emissions. This observation aligns with studies demonstrating that the increased adoption of renewable technologies, such as solar and wind power, significantly decreases reliance on fossil fuels, thus lowering overall carbon emissions in OECD countries. Similarly, the inverse relationship between environmental taxes and CO₂ emissions highlights the effectiveness of fiscal measures in pollution control. Environmental taxes, such as carbon taxes, provide financial incentives for industries to lower their carbon footprint by adopting cleaner technologies and sustainable practices. Numerous OECD studies corroborate this finding, indicating that well-implemented environmental taxes can substantially reduce carbon emissions. Green finance also shows a negative relationship with CO₂ emissions, suggesting that investments directed towards environmentally sustainable projects contribute to emission reductions. Mechanisms such as green bonds and sustainable investment funds finance projects that enhance energy efficiency, promote renewable energy adoption, and support other eco-friendly initiatives. This is consistent with OECD’s green growth strategy, indicating that expanding green finance can significantly contribute to long-term environmental sustainability.

The negative association between foreign direct investment and CO₂ emissions implies that foreign investments, particularly those involving advanced technologies and sustainable practices, can aid in reducing emissions. This relationship is particularly relevant for OECD countries, where stringent environmental regulations and the transfer of green technologies through foreign direct investment can lead to cleaner industrial processes and reduced emissions. Conversely, the positive correlation between industrialization and CO₂ emissions reflects the traditional view that industrial activities, particularly in their early stages, tend to increase carbon output due to heavy reliance on fossil fuels. This presents a significant challenge for OECD countries, which must balance industrial growth with environmental sustainability. Urbanization’s positive relationship with CO₂ emissions can be attributed to the increased energy consumption and transportation needs associated with growing urban populations. As cities expand, the demand for energy and transportation infrastructure rises, often leading to higher emissions. This finding emphasizes the necessity for OECD countries to focus on sustainable urban planning and the development of green infrastructure to mitigate the environmental impacts of urbanization. Lastly, the positive correlation between economic growth and CO₂ emissions is indicative of the environmental Kuznets curve phenomenon, wherein emissions initially rise with economic growth before eventually declining as economies mature and prioritize environmental sustainability.

Furthermore, performing a cross-sectional dependency test is vital for this study to identify and mitigate potential correlations between cross-sectional units that may introduce bias into the econometric model’s outcomes. Within the OECD context, economic and environmental policies, along with external shocks, frequently have interconnected effects across various countries. Detecting cross-sectional dependency enables the model to account for these interdependencies, thereby enhancing the precision and reliability of the empirical results. This procedure is crucial for validating the model’s assumptions and ensuring that the derived conclusions are robust and accurately represent the genuine relationships among the variables under investigation.

Table 3. Results of cross-sectional dependency test.

Variable	Statistical Value
ca	5.035 ***
re	7.871 ***
en	8.122 ***
gr	5.664 ***
in	8.716 ***
fdi	6.663 ***
ur	5.141 ***
ec	4.538 ***

Note: *** 1% significance level.

delineates the results of the cross-sectional dependency test, revealing statistically significant values for all the variables analyzed. The high levels of significance indicate a pronounced cross-sectional dependence throughout the dataset. This suggests that economic and environmental factors in OECD countries are highly interconnected, thereby necessitating the incorporation of cross-sectional dependencies within the econometric model. Addressing these dependencies enhances the robustness of the model, ensuring that the estimated impacts of renewable energy, environmental taxes, and other control variables on CO₂ emissions are accurately captured and not distorted by unaccounted interdependencies among the nations.

Based on the findings in Table 3, the employment of the cross-sectional Im–Pesaran–Shin (CIPS) and modified cross-sectional Im–Pesaran–Shin (M-CIPS) unit root tests in this study is thoroughly justified, as they proficiently account for cross-sectional dependence within the panel data of OECD countries. These tests are indispensable for confirming the stationarity of the variables, which is a crucial prerequisite for sound econometric modeling. The CIPS test, through its cross-sectional augmentation, addresses potential biases stemming from cross-sectional dependencies, while the M-CIPS test further reinforces robustness by integrating multiple cross-sectional averages. Together, these tests provide a comprehensive assessment of the data’s stationarity, thereby ensuring the validity and reliability of the ensuing econometric analyses and conclusions. The detailed results are presented in

Table 4. Results of unit root test.

Variable	CIPS Test		M-CIPS Test
	Level	1st Level	Level	1st Level
ca	−1.277	−2.968 ***	−1.007	−3.813 ***
re	−1.693	−4.117 ***	−1.647	−5.093 ***
en	−2.719 ***	−3.515 ***	−3.013 ***	−4.453 ***
gr	1.401	4.933 ***	1.357	5.739 ***
in	−1.329	−7.323 ***	−1.442	−7.946 ***
fdi	1.158	6.849 ***	1.163	6.334 ***
ur	−4.964 ***	−7.425 ***	−4.117 ***	−7.082 ***
ec	0.937	6.148 ***	1.061	6.464 ***

Note: *** 1% significance level.

.

Table 4 delineates the outcomes of the CIPS and M-CIPS unit root tests, demonstrating that all variables achieve stationarity upon first differencing, as indicated by the significant test statistics. These results confirm the absence of unit roots in the dataset, thereby fulfilling the stationarity prerequisite essential for reliable econometric modeling. Consequently, these findings ensure the robustness and validity of subsequent analyses, facilitating an accurate investigation of the relationships between CO₂ emissions and the independent variables under examination, including renewable energy, environmental taxes, and other control variables within the OECD countries’ context.

Thus, the results presented in

Table 5. Results of cointegration test.

Test Method	Without Break	Mean Shift	Regime Shift
${\mathrm{Z}}_{\mathsf{\phi }}\left(\mathrm{n}\right)$	−8.259 ***	−7.973 ***	−7.764 ***
p-value	0.000	0.000	0.000
${\mathrm{Z}}_{\mathsf{\tau }}\left(\mathrm{n}\right)$	−7.505 ***	−7.106 ***	−7.291 ***
p-value	0.000	0.000	0.000

Note: *** 1% significance level. ca = f(re, en, gr, in, fdi, ur, ec).

offer essential insights into the long-term equilibrium relationships among the variables examined in this study. Following the confirmation of stationarity from the unit root tests, it is imperative to assess cointegration to ascertain the existence of a stable, long-term relationship between CO₂ emissions and the independent variables, including renewable energy, environmental taxes, and other control variables. The application of the Westerlund and Edgerton test is appropriate, as it accommodates structural breaks and cross-sectional dependence, thereby enhancing the robustness and reliability of the econometric model. These findings affirm the model’s capability to capture the long-term dynamics and interactions among the variables within the context of OECD countries. The detailed results are presented in Table 5.

Table 5 presents the results of the cointegration tests, which indicate significant long-term relationships among the variables under study. The test statistics for the Westerlund and Edgerton cointegration test, with and without structural breaks, are all highly significant, confirming that CO₂ emissions, renewable energy, environmental taxes, and other control variables share a stable long-term equilibrium relationship in the context of OECD countries. This suggests that despite short-term fluctuations, these variables move together in the long run, validating the econometric model’s capacity to accurately capture and analyze these long-term interactions.

4.2. Long- and Short-Run Effects Analysis

Based on the results presented in Section 4.1, the application of the CS-ARDL approach in this study is both appropriate and well-founded due to its robust capability to address endogeneity, cross-sectional dependence, and slope heterogeneity among the constructs examined. The CS-ARDL method is particularly well-suited for analyzing panel data from OECD countries, as it effectively captures the dynamic relationships and interactions among CO₂ emissions, renewable energy, environmental taxes, and other control variables. By accounting for the complexities and interdependencies inherent in the data, the CS-ARDL approach ensures a comprehensive and reliable analysis, thereby enhancing the validity and robustness of this study’s findings. The detailed results are presented in

Table 6. Results of long- and short-run effects analyses.

Variable	Long-Run Effects
re	−0.258 *** (−5.474)
en	−0.175 *** (−4.369)
gr	−0.126 ** (−2.129)
in	0.418 *** (7.296)
fdi	−0.101 * (−1.857)
ur	0.506 *** (2.897)
ec	0.671 *** (3.855)
Cross-sectional dependency statistics	0.069 (0.788)
Variable	Short-Run Effects
re	−0.292 *** (−5.611)
en	−0.169 *** (−4.263)
gr	−0.141 ** (−2.051)
in	0.453 *** (6.947)
fdi	−0.065 * (−1.785)
ur	0.528 *** (3.168)
ec	0.806 *** (3.629)
ect−1	−0.032 *** (−3.092)

Note: * 10% significance level; ** 5% significance level; *** 1% significance level; t-values in the parentheses.

.

Table 6 presents the findings of the long- and short-run effects analyses using the CS-ARDL approach, revealing the significant long-run negative impacts of renewable energy and environmental taxes on CO₂ emissions, with coefficients of −0.258 and −0.175, respectively. These results are consistent with theoretical expectations and align with the existing literature, such as the studies by Hsu et al. [75], Hao et al. [76], Sharif et al. [77], and Bozatli and Akca [78], which, similarly, demonstrate the efficacy of renewable energy adoption and environmental taxes in reducing carbon emissions. The negative coefficients indicate that increased consumption of renewable energy and higher revenues from environmental taxes contribute to substantial long-term reductions in CO₂ emissions, emphasizing the importance of sustainable energy policies and fiscal measures in combating climate change. In the short run, renewable energy and environmental taxes continue to exhibit negative effects on CO₂ emissions, with coefficients of −0.292 and −0.169, respectively. This consistency between the short- and long-term effects underscores the immediate and enduring impact of these variables on emission reductions. The immediate effect of renewable energy reflects its rapid potential to replace fossil fuels, while the effect of environmental taxes suggests a swift incentive for cleaner production practices and technological innovations.

The analysis of the control variables shows diverse impacts on CO₂ emissions. Both industrialization and urbanization exhibit positive coefficients in the long and short run, indicating that these factors contribute to increased emissions. These findings are consistent with previous studies by Liu and Bae [79], Voumik and Sultana [80], and Afriyie et al. [81]. In contrast, foreign direct investment demonstrates a negative impact on emissions, supporting the hypothesis that foreign direct investment facilitates the transfer of green technologies, as noted by Ali et al. [82], Le et al. [83], and Wang and Huang [84]. Economic growth shows a positive correlation with CO₂ emissions, particularly in the short run, which aligns with the environmental Kuznets curve hypothesis, suggesting that emissions initially rise with economic growth before eventually declining. A comparison with existing literature highlights both consistencies and deviations in findings. While the negative impacts of renewable energy and environmental taxes are well-documented, this study offers a nuanced understanding by distinguishing between short- and long-term effects. The positive impact of industrialization and urbanization on emissions aligns with existing literature, whereas the negative impact of foreign direct investment underscores the potential for green technology transfers, an aspect sometimes overlooked in other studies.

In conclusion, the results presented in Table 6 emphasize the crucial role of renewable energy and environmental taxes in reducing CO₂ emissions over both short and long-term horizons. The robust methodology and congruence with environmental economic theories and empirical findings validate these results. Additionally, the impacts of the control variables provide a comprehensive understanding of the various factors influencing emissions, thereby reinforcing the complexity of achieving environmental sustainability in OECD countries. At the same time, the four hypotheses put forward in this paper have also been firmly supported and proved.

4.3. Discussion

This study provides a detailed examination of the long-term and short-term impacts of renewable energy consumption and environmental taxes on CO₂ emissions within OECD countries. The analysis reveals that both renewable energy and environmental taxes have significant negative effects on carbon emissions over the long run, underscoring their critical roles in emission reduction strategies. These results are consistent with previous research by Bashir et al. [26], Yunzhao [85], and Xie and [86], which similarly affirm the effectiveness of renewable energy initiatives and fiscal measures in mitigating carbon emissions. The findings suggest that increased adoption of renewable energy and the implementation of environmental taxes lead to a decrease in CO₂ emissions, highlighting the importance of sustainable energy policies and fiscal measures in addressing climate change. The immediate negative effects of these variables in the short term further emphasize their importance, as they provide both immediate and sustained benefits in reducing emissions. This consistency between short- and long-term effects highlights the necessity for continued investment in renewable energy infrastructure and the development of comprehensive environmental tax policies to achieve enduring environmental sustainability in OECD countries.

Conversely, the control variables exhibit varied impacts on CO₂ emissions, reflecting the complexity of environmental outcomes influenced by economic activities. Both industrialization and urbanization are associated with positive coefficients in both the long and short run, suggesting that these processes contribute to higher emissions. These results align with findings from Sarkodie et al. [87] and Zheng et al. [88], which indicate that industrial growth and urban expansion typically lead to increased energy consumption and emissions. In contrast, foreign direct investment is shown to have a negative impact on emissions, supporting the notion that foreign direct investment can facilitate the transfer of green technologies and promote cleaner industrial practices. This observation is corroborated by studies from Zheng et al. [89], Ghorbal et al. [90], and Saadaoui et al. [91]. Furthermore, the positive correlation between economic growth and CO₂ emissions, particularly in the short run, supports the environmental Kuznets curve hypothesis, suggesting that emissions initially rise with economic growth before declining as economies mature and adopt more sustainable practices. These findings emphasize the need to integrate environmental considerations into economic and urban planning to mitigate the adverse effects of industrialization and urbanization, while leveraging foreign direct investment for technological advancements. Collectively, the results from this study offer a comprehensive understanding of the multifaceted influences on CO₂ emissions, highlighting the pivotal roles of renewable energy and environmental taxes alongside the complex impacts of other economic factors in OECD countries.

5. Conclusions

This study’s findings reveal significant quantitative impacts of renewable energy consumption and environmental taxes on CO₂ emissions within OECD countries. Specifically, the long-run analysis demonstrates that a 1% increase in renewable energy consumption leads to a 0.258% reduction in CO₂ emissions, while a 1% increase in environmental tax revenues corresponds to a 0.175% decrease in emissions. These results are statistically significant and align with the broader literature on the efficacy of green policies. Furthermore, the short-run analysis corroborates these findings, with a 1% rise in renewable energy consumption and environmental taxes resulting in reductions of 0.292% and 0.169% in CO₂ emissions, respectively. This study also highlights the contrasting effects of industrialization and urbanization, which are associated with increases in CO₂ emissions both in the short and long run, underscoring the challenges faced by OECD countries in balancing economic growth with environmental sustainability. These numerical findings not only validate the theoretical framework but also provide concrete evidence to inform policymakers about the potential impacts of renewable energy and environmental taxes on reducing carbon emissions. This study underscores the necessity of continued investment in renewable energy infrastructure and the implementation of well-designed environmental tax policies to achieve long-term sustainability goals.

Based on this study’s conclusions, several policy implications are proposed to enhance environmental sustainability in OECD countries. First, the significant negative impact of renewable energy consumption on CO₂ emissions underscores the necessity for policies that foster the adoption and expansion of renewable energy sources. Governments should bolster subsidies, tax incentives, and grants for renewable energy projects. Increasing investment in research and development for renewable technologies is crucial for enhancing efficiency and reducing costs. Additionally, the establishment of clear regulatory frameworks can stimulate private sector investment in renewable energy. Second, the negative correlation between environmental taxes and CO₂ emissions indicates that environmental tax policies are effective instruments for emission reduction. Policymakers should design and implement comprehensive carbon tax schemes that accurately reflect the social cost of carbon emissions. The revenue generated from these taxes should be reinvested into sustainable initiatives, such as green infrastructure, public transportation, and energy efficiency programs. Regular assessments and adjustments of tax rates are essential to maintain their effectiveness in achieving emission reduction targets. Third, the positive effects of industrialization and urbanization on emissions highlight the challenges associated with sustainable growth. Urban planning policies should prioritize green building standards, the development of sustainable public transportation systems, and the preservation of green spaces. Industrial policies should promote the adoption of cleaner production technologies and practices. Implementing stringent environmental regulations and providing incentives for businesses to adopt green technologies can mitigate the adverse environmental impacts of industrialization and urbanization. Finally, the negative impact of foreign direct investment on emissions suggests that international investments play a vital role in facilitating the transfer of green technologies. Countries should create favorable conditions for attracting foreign direct investment in sectors that promote environmental sustainability. This includes developing clear and stable regulatory environments, offering incentives for foreign companies that introduce clean technologies, and fostering international partnerships for technology transfer and innovation. Strengthening intellectual property rights can also encourage foreign investors to share their advanced green technologies. By implementing these policies, OECD countries can effectively balance economic growth with the imperative to reduce carbon emissions and combat climate change. These integrated approaches are essential for achieving long-term sustainability goals and ensuring a resilient and environmentally sound future.

Of course, several research limitations exist in this paper, which also suggest the potential paths for future investigation. Firstly, this study relies on available data from OECD countries, which may contain gaps or inconsistencies that could affect the robustness of the results. Future research should aim to incorporate more comprehensive and higher-resolution datasets, potentially including non-OECD countries to provide a broader comparative analysis. Additionally, the use of more recent and frequent data collection could enhance the accuracy and reliability of the findings. Secondly, although this study considers several key variables, such as renewable energy, environmental taxes, industrialization, urbanization, foreign direct investment, and economic growth, other potentially influential factors, such as technological innovation, political stability, and public awareness, are not included. Future research should expand the scope of variables to include additional factors that could influence CO₂ emissions. Incorporating variables such as technological advancements, governance quality, and social awareness could provide a more holistic understanding of the determinants of emissions. Thirdly, the CS-ARDL approach, while robust, may have limitations in capturing the dynamic complexities of CO₂ emissions due to potential non-linearities and interactions between variables. Future research should explore the application of advanced econometric techniques, such as machine learning models or non-linear dynamic models, to better capture these complexities and interactions. This could provide deeper insights into the relationships and help identify more effective policy interventions. Finally, this study may not fully account for temporal and spatial variations across OECD countries, potentially overlooking regional differences and temporal dynamics that influence CO₂ emissions. Future studies should incorporate spatial econometric models to account for regional heterogeneity and spatial dependencies. Additionally, temporal analysis could be enhanced by considering time-series models that capture the evolution of relationships over different periods, thereby providing a more nuanced understanding of how these relationships change over time. By addressing these limitations, future research can build on the findings of this study to provide more detailed and comprehensive insights into the factors influencing CO₂ emissions and the effectiveness of various policy measures. This will aid policymakers in designing more targeted and effective strategies for achieving environmental sustainability.