The COP26 brought global attention to pressing environmental issues such as carbon emissions, financial development, urbanization, and renewable energy production. This paper employs a nonlinear ARDL model to examine the asymmetric impact of financial development and urbanization on environmental pollution in China from 1970 to 2021. By utilizing the framework of renewable energy within Solow growth model, we assess the effects on environmental quality. The results demonstrate that the financial development and urbanization contribute positively to enhancing renewable energy production that will contribute to controlling emissions level. However, the short-term projections reveal a positive relationship between urbanization, economic growth, and renewable energy production in China. Our findings provide valuable insights for addressing environmental pollution in China and offer precise guidelines for carbon policy. Additionally, we present specific policy recommendations to support the objective of sustainable development.
Research Article
Advancing China's sustainable future: Financial development, carbon emissions, urbanization, and renewable energy production under the Paris Agreement
https://doi.org/10.21203/rs.3.rs-3243879/v1
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urbanization
financial development
renewable energy
CO2 emission
economic growth
The COP26 focused international attention on serious environmental concerns including as carbon emissions, financial development, urbanization, and renewable energy production. One of the primary issues addressed was the reduction of carbon emissions, as governments saw the critical need to battle climate change. Countries promised to establish stricter legislation and policies to minimize their carbon footprint, shifting to cleaner energy sources and sustainable practices through coordinated efforts. The conference also emphasized the significance of financial development in advancing climate action. Governments, organizations, and the business sector have committed to raising funds to support renewable energy projects, sustainable infrastructure, and technological innovation. Moreover, COP26 emphasized the role of urbanization in sustainable development. Participants acknowledged the need for well-planned, eco-friendly cities that prioritize public transportation, energy-efficient buildings, and green spaces. Lastly, renewable energy production emerged as a critical topic during the conference, with nations pledging to increase their capacity and investment in renewable energy sources like solar, wind, and hydroelectric power. COP26 marked a crucial milestone in addressing these interconnected issues, promoting a future of sustainable development and environmental preservation. Financial development, carbon emissions, urbanization, and renewable energy are interconnected and their associations have significant implications for sustainable development. Financial development plays a crucial role in providing the necessary financial development and support for investments in renewable energy projects, promoting the transition to cleaner energy sources and reducing carbon emissions (Chang 2015; Song et al. 2021; Usman et al. 2022). Urbanization, on the other hand, can both contribute to increased carbon emissions through energy-intensive activities, and also provide opportunities for sustainable urban planning and infrastructure development that can enhance energy efficiency and reduce emissions (Jiang and Young 2008; Satterthwaite 2009; Zote 2010). The adoption of renewable energy sources is essential for mitigating carbon emissions, enhancing energy security, and fostering sustainable economic growth (IEA 2022; Sovacool 2017). Recognizing and effectively managing the associations between financial development, carbon emissions, urbanization, and renewable energy is crucial for achieving a sustainable and low-carbon future.
China's remarkable growth rate since the 2008 financial crisis has garnered significant attention, making it the second-fastest growing economy globally (Wang and Yao 2003; Dong et al. 2018). This extraordinary growth has been achieved across all economic sectors through industrialization and urbanization, aligning with China's pursuit of growth patterns in the era of economic globalization. While this rapid growth has improved living standards since the implementation of the first reforms, it has also resulted in pollution due to the extensive use of traditional energy resources, such as fossil fuels (Luqman et al. 2019, 2021). Consequently, the question of how to address pollution amidst rapid urbanization has become imperative for the government as China strives to expedite its urbanization efforts. China, as the world's top carbon emitter, has experienced significant urbanization and industrialization, contributing to 25 to 30 percent of global carbon emissions, surpassing the country's own population (Lingyan et al. 2021). The "China Statistical Yearbook 2020" reports a substantial increase in urbanization from 26.41% in 1990 to 62.71% in 2019, with projections suggesting it will reach 70 to 80% by 2030–2050, as stated in the "National Population Development Plan (2016–2030)." However, despite these estimates, there is still room for further development. China has entered the intermediate stage of rapid urbanization, leading to improved living conditions for citizens and an increase in energy consumption and household carbon emissions due to higher incomes. The interconnectedness of urbanization and industrialization is widely acknowledged (Shahbaz and Lean 2012; Han et al. 2022), as industrialization provides a strong economic foundation for urbanization, creating jobs, wealth, and supply. However, the fast migration from rural to urban areas poses resource, environmental, and infrastructural challenges, such as housing, employment, and transportation (Ahmed and Le 2021). This dilemma not only drives job creation but also escalates energy demand due to increased fuel consumption in urban transportation, causing significant environmental impacts.
China's growth is heavily reliant on non-environmental industries, leading to urban environmental degradation, soil erosion, deforestation, energy resource depletion, and biodiversity loss compared to other countries (Xu et al. 2021; Luqman et al. 2022). Researchers in various fields have emphasized the paradox between industrialization and ecological impact, aiming to foster environmentally friendly growth. Addressing this challenge necessitates the introduction of a social-environmental dilemma that promotes technological innovation for resource conservation, reuse, and recycling (Ozturk 2017). China, like other emerging nations, faces high pollution levels due to carbon-intensive operations in the energy sector, reliance on fossil fuels, and rapid industrialization and urbanization. Concerningly, there are no indications that carbon emissions are approaching their peak (Anwar et al. 2020). Resolving the conflict between fossil fuel usage, economic activity, and environmental degradation is crucial for promoting ecologically sustainable development (Bladon et al. 2018; Nathaniel et al. 2019). In addition, Fossil fuel consumption accounts for 70% of China's carbon emissions associated with economic activity. The expanding urbanization and industrialization in China pose challenges in controlling ecological issues, energy conservation, and emissions reduction. To address these environmental challenges effectively, it is crucial to introduce green transformation and promote sustainable development of the ecological environment through vigorous efforts to foster ecological growth models.
This study makes a valuable contribution to the existing literature by examining the interplay between financial development, renewable energy production, and environmental sustainability. By employing CO2 emissions as a measure of environmental pollution, the study provides a comprehensive assessment of China's environmental state. It recognizes the pressing issue of the conflict between human activities and the natural environment, resulting in environmental degradation and ecological imbalances (Rafique et al. 2022). In addition to investigating the influence of urbanization, economic growth, and environmental pollution on renewable energy production, the study goes further by considering the role of financial development. This inclusion is crucial as financial development plays a pivotal role in driving investments and innovations in the renewable energy sector (Polat et al. 2015; Pan et al. 2019; Deng et al. 2022). Although, the role of financial development along with other growth factors has been studied in the literature for different nations by applying different methods. However, in the case of China, the role of financial development along with renewable energy production is limited. Therefore, this study explores how financial development can facilitate the transition towards renewable energy, contributing to reducing environmental impact. By employing the advanced econometric methodology of NARDL model, the study ensures reliable and robust estimates(Shin et al. 2014) (Shin et al., 2014). The findings of this research will contribute to the existing literature by shedding light on the mechanisms through which financial development can support the growth and integration of renewable energy production. This understanding will be instrumental in formulating effective policies that promote sustainable energy practices and support China's transition towards a low-carbon and environmentally friendly economy.
This study is organized as follows. Section 2, titled "Literature Review," provides an overview of previous research on the effects of financial development, urbanization, energy consumption. Section 3, titled "Methodology and Data," presents the methodology and data employed in this study. In Section 4, titled "Results and Discussion," the empirical study's findings are summarized and discussed. Finally, Section 5, titled "Conclusion and Policy," provides recommendations based on study’s findings.
Numerous academics have investigated the links between energy and the environment in various situations, with varying results due to changes in time scales, geographical locations, and econometric methodologies (Popp et al. 2010; Pukšec et al. 2017; Abid et al. 2020). Furthermore, scientists have conducted considerable research on the elements that contribute to environmental contamination on a national, regional, and worldwide scale (Kirikkaleli and Adebayo 2021). The link between urbanization, industry, electricity consumption, and environmental pollution, on the other hand, remains equivocal, with little agreement among scholars in the case of China (Hsu et al. 2021; Li et al. 2021b; Si et al. 2021). As a result, the purpose of this part is to offer a thorough overview and evaluation of the literature on the influence of urbanization and energy usage on environmental deterioration across several time dimensions.
2.1 Urbanization and Environment
The significance of urbanization has grown in accordance with its rising economic and social importance, making it an important indicator of the development of a country (Nathaniel et al. 2019). It is clear that urbanization and its effects on the ecological environment have been the focus of much research in the field of regional environmental science. However, many nations are facing major environmental difficulties as a result of the rising rate of urbanization (Jiang and Young 2008). According to recent studies and expert ideas, as urbanization levels continue to grow, the ecological environment is under stress. There is a risk of ecological collapse if this pressure surpasses the environment's ability to sustain it.
Hence, prioritizing environmental protection is critical in order to reduce pollutant emissions and enhance economic and environmental sustainability (Ali et al. 2019; Danish et al. 2020). In their study on the causes of environmental pollution, Huang et al. (2021) discovered that urbanization adds to environmental deterioration. Mrabet et al. (2019) found that a 1% increase in urbanization results in a 0.58% increase in emissions and a 7.61% decrease in inefficient emissions in China. Han et al. (2022) revealed that the link between urbanization and environmental contamination is complicated. They discovered that when urbanization falls below a particular threshold, environmental pollution increases, and vice versa, implying that lower levels of urbanization may assist reduce environmental pollution in industrialized countries. On the other hand, some researchers argue that there is a linear relationship between urbanization and environmental pollution. They suggest that urbanization can lead to the development of public infrastructure, transportation systems, and industrial agglomerations, which can subsequently reduce energy consumption, costs associated with pollutant treatment, and pollution emissions (Han et al. 2022; Nihayah et al. 2022). Additionally, some scholars support Environmental Kuznets Curve (EKC) to examine this relationship but have not reached a consensus. For example, Mighri and AlSaggaf (2023) and Xing et al. (2023) observed an inverted U-shaped curve between urbanization and pollution emissions in China in favor of EKC hypothesis. Chen et al. (2023) also found a nonlinear relationship, demonstrating a stepwise increase. However, Ke et al. (2022) found that an increase in urbanization did not worsen environmental quality. Thus, there are differing theories and perspectives on the relationship between urbanization and environmental pollution.
2.2 Energy and Environment
Electricity plays a vital role in sustainable economic growth and improving living standards, serving as a fundamental industry and an essential component of modern civilization. However, CO2 emissions resulting from electricity generation significantly contribute to environmental degradation and can constitute a substantial portion of the carbon footprint associated with daily activities, commercial production, construction, and urban development (Du et al., 2019). Therefore, it is crucial to acknowledge the pollution emissions from the power sector when addressing environmental issues and to understand the impact of the power industry on environmental sustainability (Lee and Lee, 2022). In recent years, researchers have conducted numerous studies to explore the links between energy and environment. For example, Wang et al. (2019) found that energy generation significantly contributes to the acceleration of environmental degradation when examining factors influencing environmental quality. This finding is consistent with the research conducted by Wang et al. (2018), Li et al. (2021), Lingyan et al. (2021), and Luqman and Soytas (2022). Furthermore, concerned scholars have investigated the environmental impact of electricity generation in terms of the energy mix, aiming to address environmental deterioration more effectively.
Through an examination of the energy mix's environmental implications for power generation in France, Marques et al. (2016) discovered that nuclear energy production effectively reduces pollutant emissions. This finding is supported by Usman's research (Mehmood, 2022) on the top 10 nuclear-powered nations. Similarly, Sadorsky (2011) found that incorporating non-fossil fuels in the energy mix for power generation can moderately reduce pollutant emissions and improve environmental quality. Michael and Jahangir (1990) conducted a study on 25 African nations from 1980 to 2016, revealing that while conventional energy production contributes to environmental degradation, hydroelectric power generation has a positive impact. On the other hand, Hishan et al. (2020) provided evidence suggesting minimal impacts of fossil fuel on environment in South American nations. In a study focused on European countries, Al-Mulali et al. (2015) found no evidence to support the notion that renewable energy production is reducing pollutions level. Therefore, based on these findings, we can draw certain conclusions regarding the theory at hand.
Financial development and environment
Numerous studies have attempted to investigate the relationship between financial development and carbon emissions at both the national and corporate levels. Financial development has several components, including the growth of the banking sector, the development of the stock market, and access to financial services, all of which can impact economic activity and environmental results.
Several studies have been conducted at the national level on financial development and carbon emissions( Hsu et al. 2021). For example, in a sample of industrialized and developing nations, Brunnschweiler (2010) discovered a positive association between financial growth, as assessed by the size of the banking sector, and carbon emissions. Similarly, Shahbaz et al. (2019) discovered a positive relationship between financial development, as assessed by financial market depth, and carbon emissions in emerging nations.
Numerous studies have delved into the intricate mechanisms that link financial development and carbon emissions, shedding light on the diverse pathways through which these two factors interact. In their research, Pan et al. (2019) put forth the argument that financial development tends to foster the growth of energy-intensive industries. As a consequence, this phenomenon leads to a surge in carbon emissions as these industries heavily rely on fossil fuels and emit significant amounts of greenhouse gases. These opposing perspectives emphasize the complexities of the link between financial development and carbon emissions. While De Juan et al. highlights the potential drawbacks of financial development in terms of encouraging energy-intensive industries and exacerbating carbon emissions, Huang et al. provide a more optimistic perspective, emphasizing the potential for financial development to drive the transition to more environmentally friendly methods.
Chen et al. (2022) adopt a different approach, claiming that financial growth may play a critical role in boosting the adoption of environmentally friendly technologies. According to their research, increased access to financial resources, along with supporting regulations and incentives, enables firms to invest in and deploy environmentally friendly and sustainable technology. Companies that adopt these cleaner technologies may efficiently reduce their carbon footprint and contribute to a more ecologically sustainable future.
Significant attention has been paid to the effect of financial development on firm environmental sustainability and carbon emissions. Researchers have conducted the firm-level analysis to study the link between financial development and environmental impacts. Notably, many scholars have made significant contributions to this field of study (Gao et al. 2020; Zhang et al. 2020; Li et al. 2021a, 2023). Zhang et al. (2020) performed a thorough investigation and identified a substantial relationship between enterprises' access to external finance and their environmental behavior. They discovered that organizations with more access to external finance were more likely to invest in green projects and activities. As a result, these ecologically conscientious businesses had fewer carbon emissions, showing a link between financial success and environmental performance.
Utilizing this as a foundation, Li et al. (2023) shed light on the impact of financial restrictions in molding enterprises' carbon-intensive operations. Their research found that organizations with limited resources were more likely to engage in carbon-intensive operations. This research emphasizes the importance of financial resources in enabling businesses to implement sustainable practices and lower their carbon footprint. These studies provide useful insights into the literature by digging into the subtle interplay between financial development, financial restrictions, and business environmental behavior. Understanding how financial considerations impact corporate environmental performance is critical for policymakers, investors, and other stakeholders interested in promoting sustainable practices and reducing carbon emissions.
Through these contrasting perspectives, researchers have deepened our understanding of the nuanced ways in which financial development can influence carbon emissions. By considering these insights, policymakers, and stakeholders can make informed decisions and develop strategies that harness the positive aspects of financial development while effectively addressing the environmental challenges posed by carbon emissions.
3.1 Data
This study utilizes yearly data covering the time frame from 1970 to 2021 for China. The data pertaining to financial development, urbanization, renewable energy consumption, CO2 emissions, and economic growth is obtained from the World Development Indicators (WDI) database (Table 1). Descriptive statistics for these variables are presented in Table 2, highlighting their non-normality and asymmetric distribution. These findings align with previous studies, such as Hsu et al. (2021b). In order to employ both linear and nonlinear autoregressive distributed lag (ARDL) models, it is essential for the variables to exhibit either 0 or 1 level of integration, as suggested in the literature (Shin et al., 2014).
|
Variables |
Description |
Source |
|---|---|---|
|
lu |
Urban population ages 15–64, male |
WDI |
|
lfd |
Real domestic credit to the private sector (US$) |
WDI |
|
ly |
GDP (current US$) |
WDI |
|
lre |
Renewable energy production (% of total final energy production) |
WDI |
|
lco2 |
CO2 emissions from solid fuel consumption (% of total) |
WDI |
|
Variables |
N |
Std. Dev. |
min |
max |
kurtosis |
skewness |
|---|---|---|---|---|---|---|
|
lco2 |
62 |
6.76 |
68.926 |
95.935 |
2.431 |
.547 |
|
lu |
62 |
.144 |
8.281 |
8.705 |
1.834 |
− .491 |
|
lk |
62 |
.905 |
9.864 |
12.871 |
1.86 |
.323 |
|
ly |
62 |
.797 |
10.674 |
13.249 |
1.863 |
.399 |
|
lre |
62 |
.184 |
1.055 |
1.533 |
1.246 |
− .13 |
| Source: Authors evaluation | ||||||
|
Variables |
(1) |
(2) |
(3) |
(4) |
(5) |
|---|---|---|---|---|---|
|
(1) lfd |
1.000 |
||||
|
(2) lu |
0.642 |
1.000 |
|||
|
(3) ly |
-0.540 |
-0.495 |
1.000 |
||
|
(4) lre |
-0.545 |
-0.487 |
0.999 |
1.000 |
|
|
(5) lco2 |
-0.405 |
-0.704 |
0.687 |
0.679 |
1.000 |
|
Source: Authors’ evaluation |
|||||
3.2 Methodology
The ARDL model has previously been utilized for co-integration analysis but yielded insufficient findings. However, Ahmad et al. (2022) introduced a nonlinear format within this framework, offering promising results. In light of the occurrence of various financial crises, we have opted to employ the nonlinear ARDL model in our research to challenge the prevailing notion. The proposed model of Shin et al. (2014) allows us to address its effectiveness. The expected functional farm of our model is expressed as follows:
$$re={y}^{{\alpha }_{1}}{\text{f}\text{d}}^{{{\alpha }}_{2}}{ur}^{{\alpha }_{3}}{\text{c}\text{o}2}^{{{\alpha }}_{4}}{e}^{u}$$
1
After specification, our model can be as follows
$$lre={\alpha }_{1 }ly+{\alpha }_{2 }lfd+{\alpha }_{3 }lur+{\alpha }_{4}lco2+u$$
2
In Eq. (2), ly, lre, lfd, lur, and lco2 represent the variables for growth, renewable energy, financial development, urbanization, and CO2 emissions, respectively. The error term parameter is denoted by u. To examine nonlinear cointegration, the NARDL model will be applied within the ECM framework. In our case, the Nonlinear-ECM model is expressed as follow:
In Eq. (3), the short-run analysis allows us to examine the immediate impacts of the dependent variable on the explanatory variables. The short and long-term asymmetries of all variables are examined using the Wald test. The lag lengths p and q through Akaike information criterion. Finally, the positive and negative association of each independent variable are expressed as follows:
$${x}_{t}^{+}={\sum }_{j=1}^{t}△{x}_{j}^{+}={\sum }_{j=1}^{t}{max}\left(△{x}_{j},0\right)$$
4
$${x}_{t}^{-}={\sum }_{j=1}^{t}△{x}_{j}^{-}={\sum }_{j=1}^{t}{min}\left(△{x}_{j},0\right)$$
5
Where, \({x}_{t}\)represents the independent variables\({ \text{l}\text{f}\text{d}}_{t}{, \text{l}\text{y}}_{t}{, {, \text{l}\text{u}\text{r}}_{t} \text{a}\text{n}\text{d} \text{l}\text{c}\text{o}2}_{t}\).
Before testing for cointegration, we examine the unit root characteristics of the series. The ARDL/NARDL techniques can be applied on the assumption that the variables are integrated in order 1 or 0. However, these techniques are not suitable for a series of order 2 or I(2) (Luqman and Antonakakis 2021; Luqman and Soytas 2022). Therefore, this paper conducts the ADF and PP unit root tests (Dickey and Fuller 1979; Phillips and Perron 1988) and the results are reported in Table 4.
|
level |
1st Difference |
|||
|---|---|---|---|---|
|
P-P |
ADF |
P-P |
ADF |
|
|
lfd |
1.34 |
1.47 |
4.31* |
4.54* |
|
lre |
2.36 |
2.31 |
3.97** |
4.12* |
|
lu |
2.54 |
2.61 |
5.25* |
5.31* |
|
ly |
2.31 |
2.27 |
5.43* |
5.47* |
|
lco2 |
2.76 |
3.12 |
4.56* |
4.43* |
| Note: * and ** denote that the variables are significant at 1% and 5%. | ||||
The outcomes indicate that none of the underlying factors are of order I(2). Considering the trend and intercept assumptions, the PP test results show that all series are stationary at the second difference. Prior to running the regression models, we assess whether the data series exhibit linearity or nonlinearity. Using the Bound test for independence proposed by Pesaran et al. (2001), we confirm the presence of nonlinear patterns in the variables under consideration. The findings in Table 5 reveal that each underlying variable is nonlinearly dependent across all embedding dimensions. We employ the FPSS test recommended by Shin et al. (2014) and find that the FPSS values in Table 5 are statistically significant at the 1% level, as per Pesaran et al. (2001). Thus, we conclude that the long-term asymmetry exists in the relationship between China's lre, ly, lur, lfd, and lco2.
The Wald test has been utilized to identify the long and short-run asymmetric relationship. The results provided in Table 6 show that for all variables, the null hypothesis (that there is no asymmetry in either the long- or short-run coefficients, respectively) is rejected. This result suggests that renewable energy production responds asymmetric and nonlinear manner with all variables under investigation. In line with this, our empirical results support the applicability of the selected model.
In the short-run analysis reported in Table 7, a statistically significant positive shock to financial development(lf) is observed, indicating an inelastic relationship with renewable energy production (lre) with a coefficient of 1.27. This finding suggests that China's short-term financial development will increase by 1.07% for every 1% rise in renewable energy production at lag 1 (Wu et al. 2022).
Furthermore, a positive shock to urbanization (lur) exhibits a positive and significant short-run impact on renewable energy production (lre) at lag 0. The relationship is inelastic and substantial at the 1% level, indicating that urbanization can lead to a 2.57% increase in renewable energy production in the short term for every 1% increase at lag 0. Similar results have been found for Pakistan Jafri et al. 2021).
Conversely, short-term negative shocks to CO2 emissions (lco2) are negatively associated with past negative shocks to renewable energy production at lag 1. This result suggests that increasing the utilization of renewable energy in productive activities can lead to a reduction in CO2 emissions in China, thereby benefiting environmental pollution reduction in the short run. These findings contrast with the results of Asif et al. (2020) as they found a negative relationship between CO2 emissions and growth in Pakistan.
Our results recommend that renewable energy be utilized to promote economic growth in China, as it can help address energy shortages. However, caution should be exercised in effectively deploying renewable energy (lre) across different industrial sectors through appropriate channels. Additionally, in terms of economic growth (ly), positive shocks significantly and positively influence renewable energy production (lre) in short-run, with a coefficient of 1.53 at lag 1. This result conflicts with the findings of Luqman et al. (2021) but aligns with the findings of Baz et al. (2021).
Overall, our study provides compelling evidence for emphasizing the importance of promoting renewable energy use for sustainable development. This finding implies that renewable energy production exhibits asymmetric and nonlinear behavior. Consequently, our empirical results support the application of the asymmetric NARDL model. Subsequently, we conduct diagnostic tests to evaluate the authenticity of our proposed model.
The findings presented in Table 8 provide insights into the long-term relationship between urbanization (lur) and renewable energy production (lre) in China. It has been noted that the impact of urbanization on renewable energy production is favorable and inelastic and statistically significant. In this case, a 1% change in urbanization rises 1.31% change in renewable energy production in China. We report that urbanization has a positive influence on renewable energy sector. Our results are in line with previous studies conducted in Europe (Al-Mulali et al. 2015). However, it is noteworthy that our findings contradict the results of Ke et al. (2022). In the case of China, they discovered a negative relationship between positive shocks in renewable energy output and urbanization. This disparity underlines the need for more study to better understand the complicated dynamics of urbanization and renewable energy generation in various circumstances.
Table 8 shows that increasing renewable energy production has a considerable, positive, and inelastic long-term influence on financial development. China's financial development is expected to expand by 6% for every 1% increase in renewable energy generation, according to the predicted long-run coefficient. This conclusion is consistent with previous research on the Pakistani economy (Kim and Park 2016; Miao et al. 2022; Usman et al. 2022). It contradicts the findings of Baz et al. (2021). As a result, any positive shock to China's renewable energy production is predicted to stimulate financial development and development. Our findings give solid evidence that a rise in renewable energy output has a considerable, positive, and inelastic long-term influence on financial development. This discovery is consistent with past studies in the subject. Ji and Zhang (2019)found that an increase in renewable energy consumption positively influenced financial development, indicating a beneficial impact of renewable energy on the financial sector. This supports our finding of a positive long-term impact of renewable energy production on financial development. Additionally, Al-mulali and Binti Che Sab (2012) conducted a study on South Asian economies and found a positive association between renewable energy consumption and financial development, indicating that renewable energy plays a significant role in promoting financial development in the region. This aligns with our findings of a positive impact of renewable energy production on financial development. By referencing these studies, we provide robust empirical support for our findings regarding the positive and inelastic long-term impact of an increase in renewable energy production on financial development. These studies contribute to the existing body of literature, strengthening the validity and reliability of our research conclusions.
Table 8 displays the coefficients of economic growth (ly) in relation to renewable energy production (lre), revealing diverse signs and magnitudes. These findings indicate that lre asymmetrically affects economic growth. This implies that policymakers and government officials should prioritize renewable energy sources in order to mitigate environmental damage.
To achieve this, it is crucial to promote the generation of power from renewable sources and focus on implementing the latest energy-saving technologies. Additionally, facilitating licensing processes, business establishment, acquisitions, and grid connections for investors is important. Failure to promote renewable energy production can have a substantial negative impact on long-term economic growth, as indicated by our results. These findings support the findings of Pao and Fu (2013); Luqman et al. (2019) and Saidi and Omri (2020), who identified a negative correlation between positive shocks in renewable energy consumption and economic growth in China.
However, our results differ from those of Apergis et al. (2010); Saidi and Ben Mbarek (2016), who observed a positive long-term connection between positive shocks in renewable energy production and economic growth. To achieve sustainable growth in the long run, it is essential for the government and policymakers to monitor financial development investments and support relevant policies. It is worth noting that a negative shock to economic growth significantly and positively affects China's long-term energy production. Consequently, a decrease in lre would lead to an increase in long-term economic growth. These findings align with similar observations made regarding the Indian economy by Aydin and Turan (2020).
Figure 2 illustrates the significant asymmetry in the response of renewable energy production (lre) to shocks in urbanization (lur), financial development (lfd), economic growth (ly), and CO2 emissions (lco2). Each graph in Fig. 2 confirms this asymmetry. The empirical findings reveal that the cumulative effects of a relaxation or negative change in lre outweigh those of a contraction or positive change in lre. Notably, positive shocks to lre have a slight positive impact on ly. These results demonstrate the interconnected relationship between lre, lfd, lur, lco2, and ly in China.
|
Dependent variable lre |
F-Statistic |
Critical values of (Pesaran et al., 2001) |
Outcome |
|
|
I(0 |
I(1) |
|||
|
Linear ARDL |
2.69 |
2.03 |
3.13 |
Not Co-integrated |
|
Nonlinear ARDL |
4.74 |
Co-integrated |
||
|
Variable |
WLR |
WSR |
|---|---|---|
|
F-statistic |
F-statistic |
|
|
ly |
1.602** |
0.79* |
|
lur |
0.073* |
0.54* |
|
lfd |
0.91* |
1.37* |
|
lco2 |
0.98* |
0.84* |
| Note: *, ** denote for 1% and 5% significance level. Wsr and WLR denote for short and long−run asymmetries. | ||
|
Estimated coefficient (Adj-R2 = 0.62) |
|||
|---|---|---|---|
|
Explanatory variable |
Coefficient (standard error) |
Explanatory variable |
Coefficient (standard error) |
|
lre (-1) |
-0.209(-2.01) |
Dlre (-1) |
-0.0773(-0.39) |
|
lfd+ (-1) |
-1.271*(-2.46) |
Dlfd+ (-1) |
1.074*(2.18) |
|
lfd−(-1) |
-0.588(-0.72) |
Dlfd−(-1) |
0.451(0.60) |
|
lur+(-1) |
2.578*(2.53) |
Dlur+(-1) |
-3.766(-0.42) |
|
lur−(-1) |
-9.484(-0.21) |
Dlur−(-1) |
8.418(0.07) |
|
lco2+(-1) |
-0.0862(-0.13) |
Dlco2+(-1) |
-0.0373(-0.70) |
|
lco2−(-1) |
0.0122*(2.72) |
Dlco2−(-1) |
-0.0434(-0.73) |
|
ly+(-1) |
1.531*(2.69 |
Dly+(-1) |
-0.364(-0.23) |
|
ly−(-1) |
2.716*(2.18) |
Dly−(-1) |
-0.670(-1.15) |
|
C |
0.402(1.54) |
...... |
……. |
| Note: * and ** denote that the variables are statically significant at 1% and 5% level. | |||
|
Explanatory Variable |
Long-run effect [+] |
Long-run effect [-] |
||
|---|---|---|---|---|
|
Coefficient |
F-statistic |
Coefficient |
F-statistic |
|
|
lfd |
6.07** |
4.88 |
2.81 |
0.69 |
|
lur |
1.31** |
4.904 |
4.31 |
.045 |
|
ly |
7.31** |
3.111 |
-2.97** |
3.96 |
|
lco |
-0.04 |
0.06 |
-0.06 |
2.05 |
| Note: * and ** denote for 1% and 5% significance level. | ||||
|
Test |
statistics |
P-value |
|---|---|---|
|
Durbin Watson |
2.27 |
0.00 |
|
Jarque-Bera test on normality (chi2) |
476.6 |
0.00 |
|
Breusch/Pagan heteroskedasticity |
144.1 |
0.07 |
|
Ramsey RESET test (F) |
102.3 |
0.00 |
Source: authors evaluations.
This empirical study examines the asymmetric impacts of renewable energy production on the relationship between financial development, urbanization, CO2 emissions, and growth in China. We employ the traditional NARDL method to capture the potential asymmetric effects of these factors on renewable energy production. The findings reveal that renewable energy production in China responds to each independent variable in asymmetric and nonlinear manner, by applying NARDL model.
Our study demonstrates the short and long-run impacts of positive shocks in financial development, urbanization, CO2 emissions, and economic growth on renewable energy production. We find that both positive and negative shocks in economic growth have significant detrimental effects on renewable energy production over the long term. However, negative shocks in economic growth only have a short-term impact on renewable energy production. Additionally, we observe that the magnitude of the impact from a positive shift in economic growth on renewable energy production is greater in the long run compared to the impact from a negative shock. Overall, this study provides novel insights into the asymmetric dynamics between renewable energy production and its influencing factors in China.
The empirical results of this study have significant policy implications. Investing in renewable energy is a strategic long-term approach that aligns with China's 2030 agenda. Such a policy would facilitate the production of affordable, reliable, and sustainable energy, thereby supporting long-term sustainable development. China's heavy reliance on oil resources underscores the need to shift investments towards renewable energy products to increase global energies scenario. Policymakers should actively promote the diversification of China's energy sources to reduce dependence on oil and mitigate greenhouse gas emissions.
Under the COP26 framework, several policy suggestions can be put forth to address the challenges of carbon emissions, financial development, urbanization, and renewable energy production. First and foremost, it is essential to establish ambitious targets and enforceable regulations for carbon emission reduction. Governments should collaborate to implement carbon pricing mechanisms, promote renewable energy subsidies, and incentivize energy-efficient practices. Additionally, financial institutions can play a crucial role by integrating climate-related risks and opportunities into their decision-making processes, thereby directing investments towards sustainable projects and technologies. To tackle urbanization challenges, policies should prioritize sustainable urban planning and development, emphasizing compact and walkable cities, efficient public transportation systems, and green infrastructure. This can be achieved through zoning regulations, incentives for green building practices, and the preservation of green spaces. Lastly, to boost renewable energy production, governments can introduce policies such as feed-in tariffs, tax incentives, and simplified permitting processes to encourage investment in renewable energy projects. Furthermore, research and development funding should be increased to drive innovation in renewable technologies. By implementing these comprehensive policy suggestions, COP26 can pave the way for a greener, more sustainable future. Furthermore, taking these actions will not only foster economic growth and job creation but also contribute to China's long-term objectives to achieve Vision 2030. Policymakers should encourage the renewable energy sector to foster public-private partnership. Lastly, promoting investment in renewable energy sources is crucial to address environmental degradation and the depletion of conventional energy sources. In conclusion, this study emphasizes the importance of implementing policies that support renewable energy investment in China. These policies will have far-reaching benefits, including sustainable development, reduced reliance on oil, economic growth, job creation, and environmental preservation.
Data availability
All data used in this study are available on request.
Author contribution
JZ: methodology, data collection, conceptualization, TCC: writing—original draft preparation, and reviewing.
Declarations Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Funding
This paper is funded by Research Project of Tianjin Education Commission: Design and Research of Cross-cultural Communication Experience Based on Virtual Interaction (No.: 2021SK012).
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